Files
shockbot/agents/opencode.ts
T
Colin McDonnell ddbc610569 review prompt: friendly green callouts + per-section severity emojis (#756)
* review prompt: friendly green callouts + per-section severity emojis

- Replace `[!NOTE]` informational tier and the no-callout minor-suggestions
  tier with friendly green blockquotes (`> ` / `> 💡`). The two loud
  tiers (`[!CAUTION]` / `[!IMPORTANT]`) keep their GitHub admonitions.
- Add a per-`##`-section severity-emoji rule (🚨/⚠️/💡/ℹ️) for
  cross-cutting review concerns that don't anchor to a line and would
  otherwise be buried in summary content.
- Drop the `<br/>` between summary sections — heading + blank line
  carries enough visual spacing.
- Skip the post-run learnings-reflection turn for `IncrementalReview`.
  It's the lowest-novelty mode (delta review against existing PR with
  prior summary already loaded) and almost never produces durable
  learnings — reflection there costs ~$0.50-0.80/run for nothing.
- Surface real error info on `agent-browser` skill install failures
  (exit code + stdout + stderr + spawn error). The skills CLI uses a
  TUI that prints errors to stdout, so the prior stderr-only logging
  silently swallowed every failure.

* review prompt: per-bullet severity emoji + bullets-only sections

Section headings are plain again (no leading severity emoji). Severity
moves to individual bullets so a section that mixes a 🚨 and a 💡 isn't
mislabeled by either. Section bodies are now bullets only — paragraph
prose under a heading is harder to scan and tends to bury the
actionable point.

Bullets can carry indented continuation content (sub-bullets, code
fences, blockquotes) by indenting two spaces under the parent.

* review prompt: cap section length + identifier discipline

Bound each summary section to at most 4 bullets at most 2 lines each,
and explicitly call out identifier-heavy prose as an anti-pattern. The
reader is often a manager or non-author; identifier-dense paragraphs
('foo calls bar.fetch which dispatches to baz via qux...') are
unreadable for them. Default to plain-language behavior descriptions,
name an identifier only when it's the subject of an actionable concern
or a public surface a reader would recognize, target 2-3 backtick
tokens per bullet.

Move the deep-explanation pattern from open blockquote to a default-
collapsed details/summary so depth doesn't dominate the visible body.

* review prompt: hard cap on bullet identifier density + worked rewrite example

Soft 'aim for 2-3 tokens' guidance was ignored — first big-PR e2e
showed 12 of 19 actionable bullets exceeded the target (avg 4.8 tokens,
several over 8). Promote to a hard cap of 3 backticked tokens per
bullet and pair with a concrete bad/good rewrite the agent can pattern-
match against. Also tighten the per-bullet length cap from ~240 to
~200 chars and explicitly call it 'hard cap, not target'.

* review prompt: tighten bullet length cap to 160 chars, dramatize the worked example

V2 e2e test: token discipline improved (4.8 -> 3.3 avg, 12/19 -> 6/14
violations) but length got worse (235 -> 286 chars, 13/14 over the 200
cap). The agent compensated for fewer identifiers with more prose.

Two changes: (1) tighten the cap from ~200 chars to 160 chars / 1
visual line and call out wrap-to-multiple-lines as the failure mode;
(2) rewrite the worked example so the good version is genuinely half
the length of the bad one, not just lower token count. The example was
the thing the agent pattern-matches against; making the good version
~130 chars vs the bad version's ~290 chars sets the right shape.

* review prompt: drop fixed bullet-count cap, keep length + identifier caps

Per user feedback — section length should be governed by content, not
an arbitrary count. Soft guidance ('past ~6, ask whether to split') is
fine; the hard '≤ 4 bullets per section' rule was the wrong shape.
Length cap (160c) and identifier cap (3 backtick tokens) stay; those
target the actual scanability problem.

* review prompt: drop ## subsystem sections, flat 'Issues found' list

Per-section structure forced every concern into a subsystem frame and
made the body read like a series of mini-essays. Replace with two
parts: (1) TL;DR + Key changes as the dispassionate overview, (2) flat
'### Issues found' list ordered by severity, intermixed across files
and subsystems. Per-bullet rules (≤160c, ≤3 backtick tokens, severity
emoji prefix, optional indented continuation) carry over unchanged.

* review prompt: full v6 structure — preamble + cross-cutting H3s + nitpicks

Replaces the flat 'Issues found' bullet list with the iterated v6 shape:

- Preamble is a bolded inline 'Reviewed changes' lead-in plus bullets
  plus a collapsed 'Review metadata' block (mode/files/commits/refs/
  reviewed commits list/prior pullfrog review/staleness note).
- Each cross-cutting concern gets a '### emoji Title' section. The
  visible problem write-up is human-friendly and DESCRIBES THE PROBLEM
  ONLY — no asks, no suggested fixes, no 'the right thing to do is'.
- Each section carries a collapsed 'Technical details' block wrapped
  in a 4-backtick markdown fence (so it can hold its own 3-tick code
  fences cleanly, agent-readable, one-click copyable). Standard four
  inner sections: Affected sites, Required outcome, optional Suggested
  approach, optional Open questions for the human.
- '### ℹ️ Nitpicks' at the bottom for body-only nits that don't
  inline; simple bullets, no technical-details collapse.
- Anti-paragraph-wall rule: never two successive plain paragraphs in
  visible '### ' sections; alternate prose with structure.
- Inline-vs-body discipline: anything that anchors to a single line
  goes inline, body is for cross-cutting only.
- Drops legacy '### Key changes', '### Issues found', '<b>TL;DR</b>',
  and the '<sub>Summary</sub>' line.

* model effort: bump Gemini + GPT to high effort; drop Gemini Pro→Flash subagent

E2E review eval against a substantive billing-module diff surfaced two
related quality gaps:

1. Gemini Pro at thinkingLevel=medium (#663's CI-timeout fix) reviewed
   the diff only, took the 0-lens path, and missed a catastrophic
   camelCase/snake_case service-vs-schema mismatch. Bumping back to
   high — review work is exactly the wrong shape for the medium/high
   tradeoff #663 was optimizing for; the per-turn TTFT cost is worth
   paying when reasoning IS the value.

2. GPT had no reasoningEffort override, defaulting to upstream medium.
   Same diff, similar shallow result vs Claude. Adding reasoningEffort:
   high for the curated direct-OpenAI slugs, mirroring the Gemini
   pattern (Anthropic separately uses --effort high via the Claude
   Code CLI flag in claude.ts).

3. Gemini Pro's subagentModel was 'gemini-flash' — but Google has no
   in-between tier between Pro and Flash, and Flash is a meaningful
   capability cliff for review work. Dropping the override so subagents
   inherit Pro. Cost stays reasonable since Gemini Pro is already the
   cheapest of the flagship trio.

Other providers unchanged: Anthropic opus→sonnet and OpenAI gpt→gpt-5.4
remain (each is a one-tier drop to a still-capable sibling).

* model effort: revert orchestrator override, set explicit high on reviewfrog subagent

Reshape the effort design after eval:

- Drop the explicit Gemini and GPT model-level overrides — orchestrators
  now run at upstream defaults (Gemini high, GPT-5.x medium). Gemini's
  upstream IS high, so this is a no-op there; GPT goes back to upstream
  medium for orchestrator-level routing work.
- Add explicit 'high' on the reviewfrog subagent via agent.options.
  OpenCode merge order is base ← model.options ← agent.options ← variant
  per session/llm.ts:141, so the subagent always runs at high regardless
  of which orchestrator dispatched it. Both thinkingConfig.thinkingLevel
  (Gemini) and reasoningEffort (GPT) keys included; irrelevant keys are
  ignored per provider.
- Bump providers-live timeouts (12min job / 10min step, from 8/6) to
  budget for Gemini's TTFT variance at high effort. #663's 4min timeout
  was sized for the medium-effort override that's now removed.

* model effort: restore Gemini explicit high override (no-override path breaks)

Bare 'rely on upstream default' for Gemini failed in e2e — removing the
model-level provider config produced 'Function call is missing a
thought_signature' API errors on every gemini-pro run. Even though
upstream opencode's options() returns the same thinkingLevel: high we
were explicitly setting, opencode's resolution path differs subtly
between the two cases. v2's explicit override worked; v3's removal
broke. Reproducible across two consecutive runs.

Restoring the explicit Gemini override (back to v2 design). GPT
orchestrator stays UN-overridden — at upstream default (medium) — since
removing that override didn't trigger the same failure pattern and the
reviewfrog subagent agent.options high override compensates for the
extra depth GPT loses at medium.

* diag: remove reviewfrog agent.options to isolate Gemini thought_signature failure

v3 (no Gemini orch override) failed with thought_signature error. v4
(restored Gemini orch override at v2-equivalent) ALSO failed, even
though the orchestrator config matches v2. The variable between v2
(working) and v4 (failing) is the new reviewfrog agent.options block.
Removing it to confirm — if Gemini works again, the agent.options
addition is the culprit and we need a different shape for it.

* opencode-ai: bump 1.1.56 → 1.15.0 + clean up gemini effort config

opencode-ai@1.1.56 was published 2026-02-10 (3 months old). The Google
API tightened thought_signature validation 24-48h ago (per
https://discuss.ai.google.dev/t/gemini-thought-signature-patch/122555),
and the bug class hits opencode's session→prompt serializer for MCP
tool-call parts (anomalyco/opencode#4832, #8321). Latest stable bumps
us through ~3 months of fixes; needed for Gemini-direct to stop dying
with 'thought_signature is missing' on every multi-turn run.

Companion cleanup: the gemini provider override in opencode.ts had
30-line block of comments, four unused constants, and a 6-line
Object.fromEntries map for two entries. Replaced with one source-of-
truth helper that loops modelAliases, filters provider==='google',
strips the 'google/' prefix, and returns the override map. Adding any
future Google alias to the registry now flows through automatically.

Test added: action/agents/opencode.test.ts asserts the helper covers
every direct-Google alias, strips the prefix correctly, and pins every
entry to thinkingLevel high — catches drift in helper logic without
hardcoding the API ids the test would have to update in lockstep
with the registry.

* fix(workflow): tolerate listJobsForWorkflowRun 404 in resolveRun

PR #750 (docker testing rewrite) replaced the per-call env allowlist
with full process.env passthrough into the test container. That now
leaks GITHUB_RUN_ID + GITHUB_JOB into runs whose MCP token is scoped
to a DIFFERENT repo (e.g. providers-live smoke runs the action against
pullfrog/test-repo with pullfrog/app's run ID). The unconditional
listJobsForWorkflowRun call 404s and crashes the entire run, breaking
every providers-live job on main since #750 landed.

jobId is purely cosmetic (deep-links 'View workflow run' footer to a
specific job vs the run-level URL). Wrapping the API call in try/catch
so a 404 logs a debug message and falls through to undefined jobId is
the right fix — the failure mode is exactly what graceful degradation
is for, and the alternative (filter the env vars at the docker boundary)
re-introduces the kind of allowlist #750 was getting rid of.

* opencode-ai: pin 1.14.51 instead of 1.15.0 (effect refactor breaks JSON output)

opencode 1.15.0 (May 15) ships a major architectural refactor onto
@effect — the run command boots an in-process server via
@opencode-ai/sdk/v2 and the JSON event emission path through that SDK
client doesn't surface on stdout the way our parser expects (CI run
on 1.15.0 produced 0 stdout events but the agent still completed).
Local invocation also hangs at the in-process server boot.

The Gemini thought_signature fixes (the original reason for bumping)
landed earlier in the 1.14.x line, so 1.14.51 (May 14) gets us the
upstream fix without the Effect rewrite. Defer the 1.15.x bump until
we're ready to rewire our parser/spawn around the new SDK.

* opencode-ai: revert to 1.1.56; gha: filter outer-CI workflow-run vars at the docker boundary

Two related changes for the docker testing harness's ergonomics:

1. Revert opencode-ai 1.14.51 → 1.1.56. The 1.14+ line ships an Effect
   refactor (the SDK-v2 client + in-process server architecture) that
   our --format json parser doesn't speak — even the 1.14.51 release,
   pre-dating the 1.15.0 Effect rename, produced 0 stdout events on
   our skill-invoke smoke. There's no clean pre-Effect version that
   ships the Gemini thought_signature fix; that fix needs a separate
   workstream once we're ready to rewire the parser onto SDK v2.

2. Filter outer-CI workflow-run identifiers (GITHUB_RUN_ID, GITHUB_JOB,
   GITHUB_WORKFLOW, GITHUB_ACTION, GITHUB_REF, GITHUB_SHA, etc.) from
   gha.ts's --env-file passthrough. PR #750's full-process.env design
   leaks pullfrog/app's CI run identifiers into runs that act against
   a different repo (e.g. pullfrog/test-repo); any code path inside
   the action that uses them as keys (most notably resolveRun's
   listJobsForWorkflowRun lookup) 404s. Filtering them here means
   the action sees undefined and skips the lookup, complementing the
   defensive try/catch in resolveRun (commit addc76d4). GITHUB_REPOSITORY
   and GITHUB_TOKEN are NOT filtered — those are genuinely needed.

Companion to addc76d4 (resolveRun 404 tolerance). The two together
make this class of bug 'either fix would have caught it' rather than
'silently breaks the entire test matrix'.

* fix(deps): sync pnpm-lock.yaml with opencode-ai 1.1.56 manifest revert

Forgot to refresh the lockfile after reverting the manifest in 02c6d8c1.
CI's frozen-lockfile install was failing with 'lockfile: 1.14.51,
manifest: 1.1.56' mismatch.
2026-05-16 04:58:31 +00:00

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/**
* OpenCode agent — secure harness around OpenCode CLI.
*
* transparently wraps OpenCode with a security layer:
* - bash: "deny" via OPENCODE_CONFIG_CONTENT (agent cannot shell out)
* - OPENCODE_PERMISSION: filesystem sandbox — deny all external paths except /tmp
* - MCP ShellTool provides restricted shell (filtered env, no secrets)
* - MCP server injected alongside project config (not replacing)
* - ASKPASS handles git auth separately (token never in subprocess env)
*
* the agent process itself gets full env (needs LLM API keys, PATH, etc.).
* security is enforced at the tool layer, not the process layer.
*/
import { execFileSync } from "node:child_process";
import { mkdirSync, writeFileSync } from "node:fs";
import { join } from "node:path";
import { performance } from "node:perf_hooks";
import { pullfrogMcpName } from "../external.ts";
import { BEDROCK_MODEL_ID_ENV, modelAliases } from "../models.ts";
import type { ToolState } from "../toolState.ts";
import { getIdleMs, markActivity } from "../utils/activity.ts";
import { type AgentDiagnostic, formatAgentHangBody } from "../utils/agentHangReport.ts";
import { formatJsonValue, log } from "../utils/cli.ts";
import { installFromNpmTarball } from "../utils/install.ts";
import { findProviderErrorMatch } from "../utils/providerErrors.ts";
import { addSkill, installBundledSkills } from "../utils/skills.ts";
import {
DEFAULT_MAX_RETAINED_BYTES,
SPAWN_ACTIVITY_TIMEOUT_CODE,
SpawnTimeoutError,
spawn,
TailBuffer,
} from "../utils/subprocess.ts";
import { ThinkingTimer } from "../utils/timer.ts";
import type { TodoTracker } from "../utils/todoTracking.ts";
import { getDevDependencyVersion } from "../utils/version.ts";
import {
PULLFROG_BUS_EVENT_TYPE,
PULLFROG_OPENCODE_PLUGIN_FILENAME,
PULLFROG_OPENCODE_PLUGIN_SOURCE,
} from "./opencodePlugin.ts";
import {
buildLearningsReflectionPrompt,
runPostRunRetryLoop,
shouldRunReflection,
} from "./postRun.ts";
import { REVIEWER_AGENT_NAME, REVIEWER_SYSTEM_PROMPT } from "./reviewer.ts";
import { formatWithLabel, ORCHESTRATOR_LABEL, SessionLabeler } from "./sessionLabeler.ts";
import {
type AgentResult,
type AgentRunContext,
type AgentUsage,
agent,
logTokenTable,
MAX_STDERR_LINES,
} from "./shared.ts";
import { deriveSubagentModels } from "./subagentModels.ts";
async function installOpencodeCli(): Promise<string> {
return await installFromNpmTarball({
packageName: "opencode-ai",
version: getDevDependencyVersion("opencode-ai"),
executablePath: "bin/opencode",
installDependencies: true,
});
}
// ── config ─────────────────────────────────────────────────────────────────────
type OpenCodeConfig = {
mcp?: Record<string, unknown>;
permission?: Record<string, unknown>;
provider?: Record<string, unknown>;
agent?: Record<string, unknown>;
experimental?: Record<string, unknown>;
model?: string;
enabled_providers?: string[];
[key: string]: unknown;
};
// NOTE: OpenCode's per-call `max_tokens` defaults to 32_000. We previously
// overrode this via `OPENCODE_EXPERIMENTAL_OUTPUT_TOKEN_MAX = 5000` in #616
// to lower OpenRouter's per-call upfront budget reservation — back when the
// `ROUTER_PER_RUN_LIMIT_USD = 25` per-run key cap meant that reservation was
// a hard gate that could lock low-balance accounts out of starting a run.
//
// That gate is gone (see `app/api/proxy-token/route.ts` ~line 422 — "Per-run
// key budget … is decoupled from wallet balance"); the router now mints
// keys with `keyLimitCents = balance + buffer` ($50 / $5 / $0). The override
// no longer materially helps, and as a hard per-call output truncation it
// actively hurt: a single `create_pull_request_review` tool_use with many
// inline comments would truncate mid-stream past 5K output tokens, the JSON
// was unparseable, and the tool never invoked. We hit this on PR #710's
// verify-downshift PR. Removed in #710 — using OpenCode's 32K default.
//
// If you need to re-cap output for some reason, set
// `OPENCODE_EXPERIMENTAL_OUTPUT_TOKEN_MAX` in the action env. OpenCode's
// top-level `limit.output` config field has no read site (silently dropped
// on merge in session/llm.ts), so the env var is the only working knob.
/**
* Build the `provider.google.models[id].options` map that pins every direct-Google
* Gemini alias to `thinkingLevel: "high"`. Sourced from the model registry so
* adding/renaming a Google alias in `action/models.ts` flows through automatically.
*/
export function geminiHighThinkingOverrides(): Record<string, { options: object }> {
return Object.fromEntries(
modelAliases
.filter((a) => a.provider === "google")
.map((a) => [
a.resolve.replace(/^google\//, ""),
{ options: { thinkingConfig: { thinkingLevel: "high" } } },
])
);
}
function buildSecurityConfig(ctx: AgentRunContext, model: string | undefined): string {
const config: OpenCodeConfig = {
permission: {
bash: "deny",
edit: "allow",
read: "allow",
webfetch: "allow",
external_directory: "allow",
skill: "allow",
},
mcp: {
[pullfrogMcpName]: { type: "remote", url: ctx.mcpServerUrl },
},
agent: (() => {
const cfg = buildReviewerAgentConfig(model);
const reviewerModel = (cfg[REVIEWER_AGENT_NAME] as { model?: string })?.model ?? "(inherit)";
log.info(`» subagent models: reviewfrog=${reviewerModel}`);
return cfg;
})(),
// opt into opencode's experimental `batch` tool (added in
// anomalyco/opencode PR #2983, opt-in via `experimental.batch_tool`). it
// exposes a single `batch` tool that runs 1-25 independent tool calls
// (read/grep/glob/bash/etc.) concurrently in one assistant turn, which
// collapses the dominant grep→20×read pattern into a single round trip.
// edits are explicitly disallowed inside the batch upstream. paired with
// the "Parallel tool execution" guidance in utils/instructions.ts so the
// model actually reaches for it. see wiki/prompt.md.
experimental: { batch_tool: true },
// gemini-3 thinking pinned to high for review depth; gpt and anthropic
// effort set elsewhere (gpt: upstream default, anthropic: --effort flag in claude.ts).
provider: { google: { models: geminiHighThinkingOverrides() } },
};
if (model) {
config.model = model;
const slashIndex = model.indexOf("/");
if (slashIndex > 0) {
config.enabled_providers = [model.slice(0, slashIndex).toLowerCase()];
}
}
return JSON.stringify(config);
}
/**
* Read-only `reviewfrog` subagent for lens-based review.
*
* Non-mutative + non-recursive — enforced by the prose system prompt in
* reviewer.ts.
*
* Per-subagent `model:` override is driven by the registry in
* `action/models.ts` via each alias's `subagentModel` field — see
* `deriveSubagentModels` for the reverse-lookup. Currently wired:
* Anthropic opus → sonnet, OpenAI gpt-pro → gpt and gpt → gpt-5.4,
* Google gemini-pro → gemini-flash. Other providers (xai, deepseek,
* moonshot) and already-cheap tiers inherit (no override) — either the
* absolute savings are too small to justify or there's no clean
* cheaper-but-capable sibling.
*/
function buildReviewerAgentConfig(orchestratorModel: string | undefined): Record<string, unknown> {
const overrides = deriveSubagentModels(orchestratorModel);
return {
[REVIEWER_AGENT_NAME]: {
description:
"Read-only review subagent for lens-based code review (correctness, security, billing-subsystem, etc.). " +
"Reads only — no writes, no state-changing shell or MCP calls, no nested subagent dispatch.",
mode: "subagent",
prompt: REVIEWER_SYSTEM_PROMPT,
...(overrides.reviewer !== undefined ? { model: overrides.reviewer } : {}),
},
};
}
// ── model auto-select fallback ──────────────────────────────────────────────────
//
// steps 12 of model resolution (PULLFROG_MODEL env, slug resolution) are handled
// by resolveModel() in utils/agent.ts before the agent runs. this fallback only
// handles step 3: auto-select via `opencode models`.
function getOpenCodeModels(cliPath: string): string[] {
try {
const output = execFileSync(cliPath, ["models"], {
encoding: "utf-8",
timeout: 30_000,
env: process.env,
});
return output
.split("\n")
.map((line) => line.trim())
.filter(Boolean);
} catch (error) {
log.debug(
`» failed to run \`opencode models\`: ${error instanceof Error ? error.message : String(error)}`
);
return [];
}
}
const AUTO_SELECT_WARNING =
"select a model explicitly in the Pullfrog console (https://pullfrog.com/console) to avoid this.";
function autoSelectModel(cliPath: string): string | undefined {
const availableModels = getOpenCodeModels(cliPath);
const availableSet = new Set(availableModels);
if (availableSet.size > 0) {
log.debug(`» opencode models (${availableSet.size}): ${availableModels.join(", ")}`);
// skip hidden aliases (internal subagent-tier targets like opencode/gpt-5.4) —
// they should never surface as a user-facing orchestrator pick. mirrors the
// selectable-list filter in components/ModelSelector.tsx and action/commands/init.ts.
const match =
modelAliases.find((a) => !a.hidden && a.preferred && availableSet.has(a.resolve)) ??
modelAliases.find((a) => !a.hidden && availableSet.has(a.resolve));
if (match) {
log.info(
`» model: ${match.resolve} (auto-selected${match.preferred ? " — preferred" : ""} curated match)`
);
log.warning(`» model auto-selected. ${AUTO_SELECT_WARNING}`);
return match.resolve;
}
log.info(
`» opencode has ${availableSet.size} models but none match curated aliases — letting OpenCode auto-select`
);
}
log.warning(`» no model resolved. letting OpenCode auto-select. ${AUTO_SELECT_WARNING}`);
return undefined;
}
// ── NDJSON event types ─────────────────────────────────────────────────────────
interface OpenCodeInitEvent {
type: "init";
timestamp?: string;
session_id?: string;
model?: string;
[key: string]: unknown;
}
interface OpenCodeMessageEvent {
type: "message";
timestamp?: string;
role?: "user" | "assistant";
content?: string;
delta?: boolean;
[key: string]: unknown;
}
interface OpenCodeTextEvent {
type: "text";
timestamp?: string;
sessionID?: string;
part?: { id?: string; type?: string; text?: string; [key: string]: unknown };
[key: string]: unknown;
}
interface OpenCodeStepStartEvent {
type: "step_start";
timestamp?: string;
sessionID?: string;
part?: { id?: string; type?: string; [key: string]: unknown };
[key: string]: unknown;
}
interface OpenCodeStepFinishEvent {
type: "step_finish";
timestamp?: string;
sessionID?: string;
part?: {
id?: string;
type?: string;
reason?: string;
cost?: number;
tokens?: {
input?: number;
output?: number;
reasoning?: number;
cache?: { read?: number; write?: number };
};
[key: string]: unknown;
};
[key: string]: unknown;
}
/**
* tool-part state, mirroring opencode's `ToolState` (anomalyco/opencode
* `session/message-v2.ts`). error parts carry the reason on `error`,
* completed parts on `output` — reading the wrong field is what caused
* the silent `(no error message)` log in #662.
*
* Named `ToolPartState` locally (not `ToolState`) so it doesn't shadow the
* action-wide `ToolState` imported above.
*/
type ToolPartState =
| { status: "pending" | "running"; input?: unknown }
| { status: "completed"; input?: unknown; output: string }
| { status: "error"; input?: unknown; error: string };
interface OpenCodeToolUseEvent {
type: "tool_use";
timestamp?: number;
sessionID?: string;
part?: {
id?: string;
callID?: string;
tool?: string;
state?: ToolPartState;
};
[key: string]: unknown;
}
interface OpenCodeToolResultEvent {
type: "tool_result";
timestamp?: number;
sessionID?: string;
part?: { callID?: string; state?: ToolPartState };
tool_id?: string;
status?: "success" | "error";
output?: string;
[key: string]: unknown;
}
interface OpenCodeResultEvent {
type: "result";
timestamp?: string;
status?: "success" | "error";
stats?: {
total_tokens?: number;
input_tokens?: number;
output_tokens?: number;
duration_ms?: number;
tool_calls?: number;
};
[key: string]: unknown;
}
interface OpenCodeErrorEvent {
type: "error";
timestamp?: string;
sessionID?: string;
// opencode emits the error message under `error.data.message`, not at the
// top level. see anomalyco/opencode packages/opencode/src/cli/cmd/run.ts.
error?: {
name?: string;
data?: { message?: string; [key: string]: unknown };
[key: string]: unknown;
};
[key: string]: unknown;
}
/**
* Envelope event emitted by our `.opencode/plugin/pullfrog-events.ts` (the
* source lives in `opencodePlugin.ts`). The plugin subscribes to opencode's
* bus via `bus.subscribeAll()` and re-emits non-orchestrator
* `message.part.updated` events on stdout so subagent activity surfaces here.
*
* `bus_event.properties.part` matches the same `Part` shape that opencode's
* `cli/cmd/run.ts` uses to drive its own emit() calls, so we can route the
* inner part through the existing `tool_use` / `step_start` / `step_finish`
* / `text` handlers by synthesizing the equivalent OpenCode-style event.
*/
interface OpenCodeBusEnvelopeEvent {
type: "pullfrog_bus_event";
bus_event?: {
type?: string;
properties?: {
part?: {
sessionID?: string;
type?: string;
time?: { end?: number | string };
state?: { status?: string };
[key: string]: unknown;
};
[key: string]: unknown;
};
[key: string]: unknown;
};
[key: string]: unknown;
}
type OpenCodeEvent =
| OpenCodeInitEvent
| OpenCodeMessageEvent
| OpenCodeTextEvent
| OpenCodeStepStartEvent
| OpenCodeStepFinishEvent
| OpenCodeToolUseEvent
| OpenCodeToolResultEvent
| OpenCodeResultEvent
| OpenCodeErrorEvent
| OpenCodeBusEnvelopeEvent;
// ── runner ──────────────────────────────────────────────────────────────────────
type RunParams = {
label: string;
cliPath: string;
args: string[];
cwd: string;
env: Record<string, string | undefined>;
toolState: ToolState;
todoTracker?: TodoTracker | undefined;
onActivityTimeout?: (() => void) | undefined;
onToolUse?: ((event: { toolName: string; input: unknown }) => void) | undefined;
};
async function runOpenCode(params: RunParams): Promise<AgentResult> {
const startTime = performance.now();
let eventCount = 0;
let finalOutput = "";
let accumulatedTokens = { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 };
// per-step `part.cost` sums across the whole session. sourced from models.dev
// inside opencode — present for every supported provider (Anthropic, OpenAI,
// Google, xAI, DeepSeek, Moonshot, OpenRouter sub-providers, etc.).
let accumulatedCostUsd = 0;
let tokensLogged = false;
const toolCallTimings = new Map<string, number>();
let currentStepId: string | null = null;
let currentStepType: string | null = null;
let stepHistory: Array<{ stepId: string; stepType: string; toolCalls: string[] }> = [];
// per-session labeler so parallel subagent log lines can be differentiated.
// the orchestrator's task tool_use events seed the labeler; the next
// previously-unseen sessionID consumes the head of the pending-label queue.
// upstream opencode's `cli/cmd/run.ts` filters subagent events out of its
// NDJSON stream (`part.sessionID !== sessionID`), so we ship a per-run
// plugin (`action/agents/opencodePlugin.ts`, written into the tmpdir at
// setup) that re-emits non-orchestrator `message.part.updated` events. those
// arrive here as `pullfrog_bus_event` envelopes and feed the labeler with
// real data per subagent session.
const labeler = new SessionLabeler();
function eventLabel(event: Record<string, unknown>): string {
const sid = event.sessionID ?? event.session_id;
return labeler.labelFor(typeof sid === "string" ? sid : null);
}
function withLabel(label: string, message: string): string {
return label === ORCHESTRATOR_LABEL ? message : formatWithLabel(label, message);
}
// one ThinkingTimer per session — sharing a single timer across sessions
// conflated cross-session interleaving (parent thinks → child tool_call,
// or child returns → parent dispatches next) as parent thinking time. each
// timer formats its log lines through the session label so the "thought
// for X" attribution is visible in the merged stream.
const thinkingTimers = new Map<string, ThinkingTimer>();
function timerFor(label: string): ThinkingTimer {
let t = thinkingTimers.get(label);
if (!t) {
const formatLine = (line: string) =>
label === ORCHESTRATOR_LABEL ? line : formatWithLabel(label, line);
t = new ThinkingTimer(formatLine);
thinkingTimers.set(label, t);
}
return t;
}
// tracks per-task dispatch metadata so the matching tool_result can log a
// labeled "» subagent finished: lens=X duration=Ys" line. this is the most
// useful per-lens observability available given that subagent-internal
// events aren't streamed.
//
// matching strategy is hybrid because opencode does NOT reliably emit a
// tool_result with a callID equal to the originating tool_use.callID for
// the `task` tool (verified empirically in T3 — 5 task dispatches recorded
// here, 0 finish lines fired, yet aggregation succeeded so results did
// arrive on the stream). we keep an exact-match Map for the fast path, and
// also a FIFO queue for the fallback path where the callID mismatches.
// the queue + map share entries by reference so popping one removes both.
interface TaskDispatch {
label: string;
startedAt: number;
toolUseCallID: string;
}
const taskDispatchByCallID = new Map<string, TaskDispatch>();
const pendingTaskDispatches: TaskDispatch[] = [];
// every non-task tool_use callID we've observed. lets us tell, on a
// tool_result, whether its callID belongs to a known non-task tool (in
// which case we never fall back to FIFO) or is unrecognised (in which case
// a long-output result is a strong "this is probably a task result with a
// mismatched callID" signal).
const knownNonTaskCallIDs = new Set<string>();
function emitSubagentFinished(
dispatch: TaskDispatch,
status: string,
output: unknown,
matchKind: "exact" | "fifo"
) {
const subagentDuration = performance.now() - dispatch.startedAt;
const outputStr = typeof output === "string" ? output : "";
const outputPreview = outputStr.length > 120 ? `${outputStr.slice(0, 120)}` : outputStr;
const matchSuffix = matchKind === "fifo" ? " [fifo-matched]" : "";
log.info(
`» subagent finished: ${dispatch.label} (${(subagentDuration / 1000).toFixed(1)}s, status=${status})${matchSuffix}` +
(outputPreview ? `${outputPreview.replace(/\n/g, " ")}` : "")
);
taskDispatchByCallID.delete(dispatch.toolUseCallID);
const idx = pendingTaskDispatches.indexOf(dispatch);
if (idx >= 0) pendingTaskDispatches.splice(idx, 1);
}
function buildUsage(): AgentUsage | undefined {
const totalInput =
accumulatedTokens.input + accumulatedTokens.cacheRead + accumulatedTokens.cacheWrite;
return totalInput > 0 || accumulatedTokens.output > 0
? {
agent: "pullfrog",
inputTokens: totalInput,
outputTokens: accumulatedTokens.output,
cacheReadTokens: accumulatedTokens.cacheRead || undefined,
cacheWriteTokens: accumulatedTokens.cacheWrite || undefined,
costUsd: accumulatedCostUsd > 0 ? accumulatedCostUsd : undefined,
}
: undefined;
}
const handlers = {
init: (event: OpenCodeInitEvent) => {
// bind this sessionID to a label so subsequent events (tool_use,
// tool_result, text, message) route to the right prefix. for the
// first session this is "orchestrator"; for subagents it pops from
// the pending-dispatch queue.
const label = labeler.labelFor(event.session_id ?? null);
log.debug(
withLabel(
label,
`» ${params.label} init: session_id=${event.session_id || "unknown"}, model=${event.model || "unknown"}`
)
);
log.debug(withLabel(label, `» ${params.label} init event (full): ${JSON.stringify(event)}`));
// only reset run-wide state on the orchestrator's init — child sessions
// emit their own init events and we don't want them to clobber the
// parent's accumulated counters.
if (label === ORCHESTRATOR_LABEL) {
finalOutput = "";
accumulatedTokens = { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 };
accumulatedCostUsd = 0;
tokensLogged = false;
} else {
log.info(`» ${params.label} subagent init: ${label} (session ${event.session_id || "?"})`);
}
},
message: (event: OpenCodeMessageEvent) => {
const label = eventLabel(event);
if (event.role === "assistant" && event.content?.trim()) {
const message = event.content.trim();
if (event.delta) {
log.debug(
withLabel(
label,
`» ${params.label} thinking: ${message.substring(0, 300)}${message.length > 300 ? "..." : ""}`
)
);
} else {
log.debug(
withLabel(
label,
`» ${params.label} message (${event.role}): ${message.substring(0, 100)}${message.length > 100 ? "..." : ""}`
)
);
// same reasoning as `text` handler — only orchestrator's non-delta
// assistant message is the run output; subagent reports stay scoped
// to the box / debug log.
if (label === ORCHESTRATOR_LABEL) {
finalOutput = message;
}
}
} else if (event.role === "user") {
log.debug(
withLabel(
label,
`» ${params.label} message (${event.role}): ${event.content?.substring(0, 100) || ""}${event.content && event.content.length > 100 ? "..." : ""}`
)
);
}
},
text: (event: OpenCodeTextEvent) => {
if (event.part?.text?.trim()) {
const message = event.part.text.trim();
const label = eventLabel(event);
const boxTitle = label === ORCHESTRATOR_LABEL ? params.label : `${params.label} [${label}]`;
log.box(message, { title: boxTitle });
// only the orchestrator's final text is the run's "output" — children
// emit their own text on report-back, which would clobber the parent's
// final answer if we accepted any text into finalOutput.
if (label === ORCHESTRATOR_LABEL) {
finalOutput = message;
}
}
},
step_start: (event: OpenCodeStepStartEvent) => {
const stepType = event.part?.type || "unknown";
const stepId = event.part?.id || "unknown";
currentStepId = stepId;
currentStepType = stepType;
stepHistory.push({ stepId, stepType, toolCalls: [] });
},
step_finish: async (event: OpenCodeStepFinishEvent) => {
const stepId = event.part?.id || "unknown";
const eventTokens = event.part?.tokens;
if (eventTokens) {
accumulatedTokens.input += eventTokens.input || 0;
accumulatedTokens.output += eventTokens.output || 0;
accumulatedTokens.cacheRead += eventTokens.cache?.read || 0;
accumulatedTokens.cacheWrite += eventTokens.cache?.write || 0;
}
// step_finish.part.cost is a per-step delta (not a running total) —
// OpenCode emits varying per-event values that sum to the session cost.
// verified empirically across Anthropic, OpenAI, Gemini, xAI, DeepSeek,
// Moonshot, and OpenRouter (see pullfrog-baseline/opencode-*.log).
// guard against NaN/Infinity — a single poison value would make the
// running total un-recoverable for the rest of the session.
if (typeof event.part?.cost === "number" && Number.isFinite(event.part.cost)) {
accumulatedCostUsd += event.part.cost;
}
if (currentStepId === stepId) {
currentStepId = null;
currentStepType = null;
}
},
tool_use: (event: OpenCodeToolUseEvent) => {
const toolName = event.part?.tool;
const toolId = event.part?.callID;
if (!toolName || !toolId) {
log.info(
`» tool_use event missing toolName or toolId: ${JSON.stringify(event).substring(0, 500)}`
);
return;
}
// when the orchestrator dispatches a subagent via the `task` tool, push
// a label for the upcoming child session so its events are attributable.
// record BEFORE label lookup: this event's session is the parent (whose
// label is already bound); the dispatch label is for the next new
// sessionID that appears.
if (toolName === "task") {
// may have been pre-registered via the plugin's early task-dispatch
// announcement (`pullfrog_bus_event` handler). dedupe on callID so
// we don't record the same dispatch twice (which would corrupt the
// FIFO label queue).
if (!taskDispatchByCallID.has(toolId)) {
const taskInput = (event.part?.state?.input ?? {}) as {
description?: string;
subagent_type?: string;
prompt?: string;
};
const dispatchedLabel = labeler.recordTaskDispatch(taskInput);
// dual-index by callID (fast path) AND in a FIFO queue (fallback path
// for when opencode's task tool_result carries a different callID).
const dispatch: TaskDispatch = {
label: dispatchedLabel,
startedAt: performance.now(),
toolUseCallID: toolId,
};
taskDispatchByCallID.set(toolId, dispatch);
pendingTaskDispatches.push(dispatch);
log.info(
`» dispatching subagent: ${dispatchedLabel}` +
(taskInput.subagent_type ? ` (subagent_type=${taskInput.subagent_type})` : "")
);
}
} else {
// remember non-task callIDs so a later tool_result with that callID
// is correctly identified as not-a-task (and we don't FIFO-pop a
// pending task by mistake).
knownNonTaskCallIDs.add(toolId);
}
const label = eventLabel(event);
if (stepHistory.length > 0) {
stepHistory[stepHistory.length - 1]!.toolCalls.push(toolName);
}
if (params.onToolUse) {
params.onToolUse({
toolName,
input: event.part?.state?.input,
});
}
timerFor(label).markToolCall();
const inputFormatted = formatJsonValue(event.part?.state?.input || {});
const toolCallLine =
inputFormatted !== "{}" ? `» ${toolName}(${inputFormatted})` : `» ${toolName}()`;
log.info(withLabel(label, toolCallLine));
if (event.part?.state?.status === "completed" && event.part.state.output) {
log.debug(withLabel(label, ` output: ${event.part.state.output}`));
}
// surface tool errors at info level. opencode emits tool parts at
// status="error" through the same `tool_use` event the CLI's run-loop
// (and our injected plugin for subagent parts) emits — without this
// branch the only signal in the user's logs is `» <tool>(...)` with
// no indication the call failed.
if (event.part?.state?.status === "error") {
log.info(withLabel(label, `» tool call failed: ${event.part.state.error}`));
}
// agent's explicit MCP report_progress takes priority over todo tracking
if (toolName.includes("report_progress") && params.todoTracker) {
log.debug("» report_progress detected, disabling todo tracking");
params.todoTracker.cancel();
}
// parse todowrite events for live progress tracking
if (toolName === "todowrite" && params.todoTracker?.enabled) {
params.todoTracker.update(event.part?.state?.input);
}
},
tool_result: (event: OpenCodeToolResultEvent) => {
const toolId = event.part?.callID || event.tool_id;
const state = event.part?.state;
const status = state?.status ?? event.status ?? "unknown";
const payload =
state?.status === "completed"
? state.output
: state?.status === "error"
? state.error
: event.output;
const label = eventLabel(event);
timerFor(label).markToolResult();
// surface subagent completion at info level — opencode otherwise hides
// per-task timing in debug-only logs, so a parallel multi-lens fan-out
// looks like N dispatches followed by a long quiet gap then a single
// assistant turn. with this line you can see each lens finishing.
//
// matching is hybrid: exact callID first; FIFO fallback when the
// tool_result's callID is unrecognised. opencode does not consistently
// surface matching callIDs for the `task` tool, so the FIFO path is the
// one that fires in practice. we only fall through to FIFO when the
// callID is brand-new (not in `knownNonTaskCallIDs`) so genuinely
// non-task tool_results never accidentally pop a pending task.
if (taskDispatchByCallID.size > 0 || pendingTaskDispatches.length > 0) {
if (toolId && taskDispatchByCallID.has(toolId)) {
const dispatch = taskDispatchByCallID.get(toolId);
if (dispatch) emitSubagentFinished(dispatch, status, payload, "exact");
} else {
const callIDIsKnownNonTask = toolId ? knownNonTaskCallIDs.has(toolId) : false;
if (!callIDIsKnownNonTask && pendingTaskDispatches.length > 0) {
const dispatch = pendingTaskDispatches[0]!;
emitSubagentFinished(dispatch, status, payload, "fifo");
}
}
}
if (toolId) {
const toolStartTime = toolCallTimings.get(toolId);
if (toolStartTime) {
const toolDuration = performance.now() - toolStartTime;
toolCallTimings.delete(toolId);
const stepContext = currentStepId ? ` (step=${currentStepType || "unknown"})` : "";
log.debug(
withLabel(
label,
`» ${params.label} tool_result${stepContext}: id=${toolId}, status=${status}, duration=${Math.round(toolDuration)}ms`
)
);
if (payload) {
log.debug(withLabel(label, ` output: ${payload}`));
}
if (toolDuration > 5000) {
log.info(
withLabel(
label,
`» tool call took ${(toolDuration / 1000).toFixed(1)}s - may indicate network latency`
)
);
}
}
}
if (status === "error") {
log.info(withLabel(label, `» tool call failed: ${payload ?? "(no error message)"}`));
} else if (payload) {
log.debug(withLabel(label, `tool output: ${payload}`));
}
},
error: (event: OpenCodeErrorEvent) => {
// opencode emits a `type=error` event when a provider call fails (e.g.
// 401 Invalid authentication credentials). the underlying CLI still
// exits 0 because the error was returned cleanly by the LLM SDK, so
// unless we capture this event the run is reported as success.
agentErrorEvent = event;
const errorName = event.error?.name || "unknown";
const errorMessage = event.error?.data?.message || event.error?.name || JSON.stringify(event);
log.info(`» ${params.label} error event: ${errorName}: ${errorMessage}`);
},
result: async (event: OpenCodeResultEvent) => {
const status = event.status || "unknown";
const duration = event.stats?.duration_ms || 0;
const toolCalls = event.stats?.tool_calls || 0;
log.info(
`» ${params.label} result: status=${status}, duration=${duration}ms, tool_calls=${toolCalls}`
);
if (event.status === "error") {
log.info(`» ${params.label} failed: ${JSON.stringify(event)}`);
} else {
// the final `result` event only carries input_tokens/output_tokens and
// no cache breakdown — accumulatedTokens (summed across step_finish
// events) is strictly more accurate, so we prefer it unconditionally.
log.info(`» run complete: tool_calls=${toolCalls}, duration=${duration}ms`);
if (
(accumulatedTokens.input > 0 ||
accumulatedTokens.output > 0 ||
accumulatedTokens.cacheRead > 0 ||
accumulatedTokens.cacheWrite > 0) &&
!tokensLogged
) {
logTokenTable({ ...accumulatedTokens, costUsd: accumulatedCostUsd });
tokensLogged = true;
}
}
},
[PULLFROG_BUS_EVENT_TYPE]: async (event: OpenCodeBusEnvelopeEvent) => {
// surface subagent activity that opencode's CLI run-loop discards (it
// filters `part.sessionID !== sessionID`). our injected plugin
// (action/agents/opencodePlugin.ts) re-emits non-orchestrator
// `message.part.updated` bus events; here we synthesize the equivalent
// CLI-style event for each known part type and dispatch through the
// existing handlers so labeling, attribution, and logging all reuse the
// same code path as the orchestrator's events. mirrors the dispatch
// logic in opencode-ai's `cli/cmd/run.ts` `loop()` function.
const busEvent = event.bus_event;
if (!busEvent || busEvent.type !== "message.part.updated") return;
const part = busEvent.properties?.part;
if (!part || typeof part.sessionID !== "string") return;
const sessionID = part.sessionID;
const partType = part.type;
// early task dispatch: the orchestrator's task tool fires bus events at
// status=running BEFORE the subagent's first message.part.updated, but
// the CLI's run-loop only emits the matching tool_use NDJSON event at
// status=completed (after the subagent finishes). without
// pre-registering the dispatch label here, the labeler binds the
// subagent's sessionID to a generic `subagent#N` fallback before the
// CLI's tool_use ever fires recordTaskDispatch. dedupe against
// taskDispatchByCallID so the late tool_use handler doesn't double-add.
if (partType === "tool") {
const status = part.state?.status;
const partWithToolFields = part as {
tool?: string;
callID?: string;
state?: { status?: string; input?: unknown };
};
// only running (not pending) — at pending state.input is still {}.
// by running, the LLM has filled in description/subagent_type/prompt.
// mirrors the same check in the plugin source.
const isOrchestratorTaskDispatch =
partWithToolFields.tool === "task" && status === "running";
if (isOrchestratorTaskDispatch) {
const callID = partWithToolFields.callID;
if (typeof callID === "string" && !taskDispatchByCallID.has(callID)) {
const taskInput = (partWithToolFields.state?.input ?? {}) as {
description?: string;
subagent_type?: string;
prompt?: string;
};
const dispatchedLabel = labeler.recordTaskDispatch(taskInput);
const dispatch: TaskDispatch = {
label: dispatchedLabel,
startedAt: performance.now(),
toolUseCallID: callID,
};
taskDispatchByCallID.set(callID, dispatch);
pendingTaskDispatches.push(dispatch);
log.info(
`» dispatching subagent: ${dispatchedLabel}` +
(taskInput.subagent_type ? ` (subagent_type=${taskInput.subagent_type})` : "")
);
}
return;
}
if (status !== "completed" && status !== "error") return;
await handlers.tool_use({
type: "tool_use",
sessionID,
part,
} as OpenCodeToolUseEvent);
return;
}
// intentionally NOT routing subagent step_start / step_finish through
// the orchestrator's handlers:
// - step_finish carries `tokens` and `cost` and the handler folds
// them into the run-wide accumulators. surfacing subagent steps
// here would inflate the orchestrator's usage telemetry — and
// either double-count (if opencode also bills child tokens back
// up to the parent session) or just over-report. the existing
// init/message/text handlers all gate on ORCHESTRATOR_LABEL for
// the same reason.
// - step_start mutates `currentStepId` / `currentStepType` /
// `stepHistory`, which are orchestrator-scoped — using them to
// attribute subagent activity in the orchestrator's tool-use
// timing log would be wrong.
// the subagent's tool calls and text still surface (handled below)
// — that's the user-visible activity.
if (partType === "step-start" || partType === "step-finish") return;
if (partType === "text" && part.time?.end !== undefined) {
await handlers.text({
type: "text",
sessionID,
part,
} as OpenCodeTextEvent);
return;
}
},
};
const recentStderr: string[] = [];
let lastProviderError: string | null = null;
let agentErrorEvent: OpenCodeErrorEvent | null = null;
// shared with main.ts via toolState. updated in place as events stream and
// stderr accumulates so the outer activity-timeout catch sees the same
// context the harness's own catch path uses to format `result.error`.
// recentStderr is shared by reference; the scalar fields are mirrored on
// each update below.
const diagnostic: AgentDiagnostic = {
label: params.label,
recentStderr,
lastProviderError: undefined,
eventCount: 0,
};
params.toolState.agentDiagnostic = diagnostic;
// capped accumulator for the agent's narration. used as a post-run fallback
// when `finalOutput` (the orchestrator's final assistant message) is empty.
// unbounded `output += text` previously grew to ~1 GiB on multi-lens Reviews
// and contributed to the wrapper-level RangeError. retain:"none" on spawn
// skips the duplicate buffer there; this TailBuffer caps the agent layer.
const output = new TailBuffer(DEFAULT_MAX_RETAINED_BYTES);
let stdoutBuffer = "";
try {
const result = await spawn({
cmd: params.cliPath,
args: params.args,
cwd: params.cwd,
env: params.env,
activityTimeout: 300_000,
onActivityTimeout: params.onActivityTimeout,
stdio: ["ignore", "pipe", "pipe"],
// node_modules/opencode-ai/bin/opencode is a Node shim that spawnSyncs
// the native opencode-<plat>-<arch> binary with stdio:"inherit". without
// a process-group kill, SIGKILL hits only the shim, the native binary
// is reparented to PID 1, holds our stdout pipe open, and `child.close`
// never fires — producing zombie runs. detached + killGroup nukes the
// whole tree.
killGroup: true,
// we already drain every chunk via onStdout/onStderr (NDJSON parsing
// + recentStderr ring buffer). retaining a second copy in the spawn
// wrapper would grow unbounded for multi-lens Reviews and previously
// crashed the wrapper with RangeError at ~1 GiB. see issue #680.
retain: "none",
// NB: we used to pass `isPausedExternally: isSubagentInFlight` to suspend
// the activity timer during subagent dispatches. unnecessary now that
// our injected plugin (action/agents/opencodePlugin.ts) re-emits
// subagent `message.part.updated` events on opencode's stdout — those
// arrive at child.stdout here, fire updateActivity(), and reset
// lastActivityTime naturally. verified empirically in PR #634
// (~3.3 plugin events/sec during a typical subagent run).
onStdout: async (chunk) => {
const text = chunk.toString();
output.append(text);
markActivity();
stdoutBuffer += text;
const lines = stdoutBuffer.split("\n");
stdoutBuffer = lines.pop() || "";
for (const line of lines) {
const trimmed = line.trim();
if (!trimmed) continue;
let event: OpenCodeEvent;
try {
event = JSON.parse(trimmed) as OpenCodeEvent;
} catch {
log.debug(`» non-JSON stdout line: ${trimmed.substring(0, 200)}`);
continue;
}
eventCount++;
diagnostic.eventCount = eventCount;
log.debug(JSON.stringify(event, null, 2));
const timeSinceLastActivity = getIdleMs();
if (timeSinceLastActivity > 10000) {
const activeToolCalls = toolCallTimings.size;
const toolCallInfo =
activeToolCalls > 0
? ` (waiting for ${activeToolCalls} tool call${activeToolCalls > 1 ? "s" : ""})`
: ` (${params.label} may be processing internally - LLM calls, planning, etc.)`;
log.info(
`» no activity for ${(timeSinceLastActivity / 1000).toFixed(1)}s${toolCallInfo} (${eventCount} events processed so far)`
);
}
markActivity();
const handler = handlers[event.type as keyof typeof handlers];
if (!handler) {
log.info(
`» ${params.label} event (unhandled): type=${event.type}, data=${JSON.stringify(event).substring(0, 500)}`
);
continue;
}
try {
await handler(event as never);
} catch (err) {
log.info(
`» ${params.label} handler for type=${event.type} threw: ${err instanceof Error ? err.message : String(err)}`
);
}
}
},
onStderr: (chunk) => {
const trimmed = chunk.trim();
if (!trimmed) return;
recentStderr.push(trimmed);
if (recentStderr.length > MAX_STDERR_LINES) recentStderr.shift();
const match = findProviderErrorMatch(trimmed);
if (match) {
lastProviderError = match.label;
diagnostic.lastProviderError = match.label;
log.info(`» provider error detected (${match.label}): ${match.excerpt}`);
} else {
log.debug(trimmed);
}
},
});
if (result.exitCode === 0) {
await params.todoTracker?.flush();
} else {
params.todoTracker?.cancel();
}
// any pending task dispatches that never got a matching tool_result are
// surfaced here so the gap is visible rather than silently swallowed.
// this happens when opencode delivers the subagent's reply through a
// path other than tool_result (e.g. inlined into the next assistant
// message). flushing here is best-effort attribution — the durations
// reported are upper bounds (the subagent could have finished any time
// between dispatch and run-end), but the labels and ordering are exact.
//
// NB: the `result` event handler is dead in opencode (opencode never
// emits a `result`-typed event), which is why this flush lives here in
// the post-subprocess block instead.
if (pendingTaskDispatches.length > 0) {
for (const dispatch of [...pendingTaskDispatches]) {
const elapsed = performance.now() - dispatch.startedAt;
log.info(
`» subagent finished (inferred at run-end): ${dispatch.label} (≤${(elapsed / 1000).toFixed(1)}s) — no matching tool_result observed; subagent reply likely arrived via assistant message`
);
}
pendingTaskDispatches.length = 0;
taskDispatchByCallID.clear();
}
const duration = performance.now() - startTime;
log.info(
`» ${params.label} completed in ${Math.round(duration)}ms with exit code ${result.exitCode}`
);
if (eventCount === 0) {
const stderrContext = recentStderr.join("\n");
const diagnosis = lastProviderError
? `provider error: ${lastProviderError}`
: "unknown cause (no stdout events received)";
log.info(`» ${params.label} produced 0 events (${diagnosis})`);
if (stderrContext) log.info(`» last stderr output:\n${stderrContext}`);
}
if (
!tokensLogged &&
(accumulatedTokens.input > 0 ||
accumulatedTokens.output > 0 ||
accumulatedTokens.cacheRead > 0 ||
accumulatedTokens.cacheWrite > 0)
) {
logTokenTable({ ...accumulatedTokens, costUsd: accumulatedCostUsd });
tokensLogged = true;
}
const usage = buildUsage();
if (result.exitCode !== 0) {
const errorContext = lastProviderError ? ` (${lastProviderError})` : "";
// result.stdout / result.stderr are empty because we pass retain:"none"
// to spawn (see issue #680); use the agent's bounded mirrors instead.
const stdoutSnapshot = output.toString();
const stderrSnapshot = recentStderr.join("\n");
const errorMessage =
stderrSnapshot ||
stdoutSnapshot ||
`unknown error - no output from OpenCode CLI${errorContext}`;
log.error(
`${params.label} exited with code ${result.exitCode}${errorContext}: ${errorMessage}`
);
log.debug(`stdout: ${stdoutSnapshot.substring(0, 500)}`);
log.debug(`stderr: ${stderrSnapshot.substring(0, 500)}`);
return {
success: false,
output: finalOutput || stdoutSnapshot,
error: errorMessage,
usage,
};
}
if (eventCount === 0 && lastProviderError) {
return {
success: false,
output: finalOutput || output.toString(),
error: `provider error: ${lastProviderError}`,
usage,
};
}
if (agentErrorEvent) {
const errorEvent: OpenCodeErrorEvent = agentErrorEvent;
const errorName = errorEvent.error?.name || "agent error";
const errorMessage =
errorEvent.error?.data?.message || errorEvent.error?.name || JSON.stringify(errorEvent);
return {
success: false,
output: finalOutput || output.toString(),
error: `${errorName}: ${errorMessage}`,
usage,
};
}
return { success: true, output: finalOutput || output.toString(), usage };
} catch (error) {
params.todoTracker?.cancel();
const duration = performance.now() - startTime;
const errorMessage = error instanceof Error ? error.message : String(error);
const isActivityTimeout =
error instanceof SpawnTimeoutError && error.code === SPAWN_ACTIVITY_TIMEOUT_CODE;
const stderrContext = recentStderr.slice(-10).join("\n");
const diagnosis = lastProviderError
? `likely cause: ${lastProviderError}`
: eventCount === 0
? "OpenCode produced 0 stdout events - check if the model provider is reachable"
: `${eventCount} events were processed before the hang`;
log.info(
`» ${params.label} ${isActivityTimeout ? "hung" : "failed"} after ${(duration / 1000).toFixed(1)}s: ${errorMessage}`
);
log.info(`» diagnosis: ${diagnosis}`);
if (stderrContext)
log.info(
`» recent stderr (last ${Math.min(recentStderr.length, 10)} lines):\n${stderrContext}`
);
const body = formatAgentHangBody({ diagnostic, isHang: isActivityTimeout, errorMessage });
return {
success: false,
output: finalOutput || output.toString(),
error: body ?? `${errorMessage} [${diagnosis}]`,
usage: buildUsage(),
};
}
}
// ── agent ───────────────────────────────────────────────────────────────────────
export const opencode = agent({
name: "opencode",
install: installOpencodeCli,
run: async (ctx) => {
const cliPath = await installOpencodeCli();
const rawModel = ctx.payload.proxyModel ?? ctx.resolvedModel ?? autoSelectModel(cliPath);
// bedrock route: opencode's `amazon-bedrock` provider expects the model
// string in `amazon-bedrock/<bedrock-id>` form. the bare AWS model ID
// (what the user puts in `BEDROCK_MODEL_ID`) needs the prefix added.
// detect via env-var sentinel — same pattern as claude.ts.
//
// we deliberately do NOT gate on `!isBedrockAnthropicId(rawModel)` here:
// Anthropic-on-Bedrock normally routes to claude-code (per `resolveAgent`),
// but `PULLFROG_AGENT=opencode` is the documented escape hatch for forcing
// opencode regardless. when that override fires, opencode still needs the
// `amazon-bedrock/` prefix or the provider lookup fails with
// "Model not found: <modelId>/.". the Anthropic-vs-other discriminant
// only belongs in `resolveAgent`.
const bedrockModelId = process.env[BEDROCK_MODEL_ID_ENV]?.trim();
const isBedrockRoute =
rawModel !== undefined && bedrockModelId !== undefined && bedrockModelId === rawModel;
const model = isBedrockRoute ? `amazon-bedrock/${rawModel}` : rawModel;
const homeEnv = {
HOME: ctx.tmpdir,
XDG_CONFIG_HOME: join(ctx.tmpdir, ".config"),
};
mkdirSync(join(homeEnv.XDG_CONFIG_HOME, "opencode"), { recursive: true });
// drop our bus-event surfacing plugin into opencode's global config dir
// (which we've redirected to the per-run tmpdir via XDG_CONFIG_HOME).
// opencode auto-discovers plugins from `<Global.Path.config>/{plugin,plugins}/*.{ts,js}`
// (see `packages/opencode/src/config/config.ts:633` calling
// `ConfigPlugin.load(dir)`), so this lands in the loader without any
// config wiring. critically: this MUST be inside the tmpdir, never the
// user's repo working tree — see AGENTS.md.
const opencodePluginDir = join(homeEnv.XDG_CONFIG_HOME, "opencode", "plugin");
mkdirSync(opencodePluginDir, { recursive: true });
writeFileSync(
join(opencodePluginDir, PULLFROG_OPENCODE_PLUGIN_FILENAME),
PULLFROG_OPENCODE_PLUGIN_SOURCE
);
const agentBrowserVersion = getDevDependencyVersion("agent-browser");
addSkill({
ref: `vercel-labs/agent-browser@v${agentBrowserVersion}`,
skill: "agent-browser",
env: homeEnv,
agent: "opencode",
});
installBundledSkills({ home: homeEnv.HOME });
// base args shared between initial run and continue runs
const baseArgs = ["run", "--format", "json", "--print-logs"];
// OPENCODE_PERMISSION has absolute highest precedence (merged after managed/MDM configs).
// external_directory gates ALL native filesystem tools (Read, Write, Edit, Glob, Grep, etc.)
// for paths outside the project root. last-match-wins: deny everything, then allow /tmp.
const permissionOverride = JSON.stringify({
external_directory: { "*": "deny", "/tmp/*": "allow" },
});
const env: Record<string, string | undefined> = {
...process.env,
...homeEnv,
OPENCODE_CONFIG_CONTENT: buildSecurityConfig(ctx, model),
OPENCODE_PERMISSION: permissionOverride,
GOOGLE_GENERATIVE_AI_API_KEY:
process.env.GOOGLE_GENERATIVE_AI_API_KEY || process.env.GEMINI_API_KEY,
};
const repoDir = process.cwd();
log.debug(`» starting Pullfrog (OpenCode): ${cliPath} ${baseArgs.join(" ")}`);
log.debug(`» working directory: ${repoDir}`);
const runParams = {
label: "Pullfrog",
cliPath,
cwd: repoDir,
env,
toolState: ctx.toolState,
todoTracker: ctx.todoTracker,
onActivityTimeout: ctx.onActivityTimeout,
onToolUse: ctx.onToolUse,
};
const result = await runOpenCode({
...runParams,
args: [...baseArgs, ctx.instructions.full],
});
// post-run retry loop aggregates usage across the initial run + every
// resume, so the caller sees the whole session — not just the final
// slice. opencode always accepts `--continue`, so no canResume guard.
// the reflection prompt fires once after gates go clean, as a dedicated
// turn that nudges the agent to persist learnings.
return runPostRunRetryLoop({
ctx,
initialResult: result,
initialUsage: result.usage,
reflectionPrompt:
ctx.toolState.learningsFilePath && shouldRunReflection(ctx.toolState.selectedMode)
? buildLearningsReflectionPrompt(ctx.toolState.learningsFilePath)
: undefined,
resume: async (c) =>
runOpenCode({
...runParams,
args: [...baseArgs, "--continue", c.prompt],
}),
});
},
});