parallel tool execution: enable opencode batch + nudge agents to parallelize (#719)
opencode: opt into `experimental.batch_tool` (anomalyco/opencode#2983) so the `batch` tool registers and the model can bundle 1-25 independent calls into one round trip. edit calls are excluded upstream. instructions.ts: add a "Parallel tool execution" section to the SYSTEM Workflow block, agent-specialized via ctx.agentId. uses Anthropic's canonical wording ("invoke all relevant tools simultaneously...") so Claude reliably emits multiple tool_use blocks per message; tells OpenCode about the new `batch` affordance. verified end-to-end against haiku-class models (sonnet for claude, default for opencode) with a "read 3 files and report first lines" fixture. results: - opencode used `batch` with 3 nested reads AND emitted 3 native parallel read calls in the same assistant turn - claude went from 3 serial turns (1 read each) to 1 message with 3 parallel Read tool_use blocks
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pullfrog[bot]
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@@ -65,6 +65,7 @@ type OpenCodeConfig = {
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permission?: Record<string, unknown>;
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provider?: Record<string, unknown>;
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agent?: Record<string, unknown>;
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experimental?: Record<string, unknown>;
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model?: string;
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enabled_providers?: string[];
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[key: string]: unknown;
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@@ -120,6 +121,15 @@ function buildSecurityConfig(ctx: AgentRunContext, model: string | undefined): s
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[pullfrogMcpName]: { type: "remote", url: ctx.mcpServerUrl },
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},
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agent: buildReviewerAgentConfig(),
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// opt into opencode's experimental `batch` tool (added in
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// anomalyco/opencode PR #2983, opt-in via `experimental.batch_tool`). it
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// exposes a single `batch` tool that runs 1-25 independent tool calls
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// (read/grep/glob/bash/etc.) concurrently in one assistant turn, which
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// collapses the dominant grep→20×read pattern into a single round trip.
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// edits are explicitly disallowed inside the batch upstream. paired with
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// the "Parallel tool execution" guidance in utils/instructions.ts so the
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// model actually reaches for it. see wiki/prompt.md.
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experimental: { batch_tool: true },
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provider: {
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google: {
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models: Object.fromEntries(
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@@ -283,6 +283,21 @@ ${getStandaloneModeInstructions(ctx.payload.event.trigger, t, ctx.outputSchema)}
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Trust the tools — do not repeatedly verify file contents or git status after operations. If a tool reports success, proceed to the next step. Only verify if you encounter an actual error. Exception: right before \`${t("push_branch")}\`, ensure the working tree is clean — that tool rejects dirty trees, and tests you ran earlier often leave untracked output.
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### Parallel tool execution
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For maximum efficiency, whenever you need to perform multiple independent operations, invoke all relevant tools simultaneously in a single assistant turn rather than sequentially. The dominant failure mode is grep → read → read → read → read across separate turns when one round trip would do. Always parallelize when calls are independent:
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- reading multiple files (especially after a grep returns candidates)
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- multiple greps with different patterns
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- glob + grep + read combos
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- listing multiple directories
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- inspecting multiple MCP tools or resources
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Do NOT parallelize operations that depend on prior output (e.g. create a file then read it), or ordered stateful mutations. Edits are not parallelizable — sequence those normally.${
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ctx.agentId === "opencode"
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? `\n\nOn OpenCode you also have a \`batch\` tool that bundles 1-25 independent calls into one wrapper call. Reach for it whenever you have >=2 independent calls. Native parallel tool_use and \`batch\` both achieve one round trip instead of N — use whichever your provider supports best.`
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: `\n\nEmit multiple \`tool_use\` blocks in the same assistant message for independent calls — the runtime executes them concurrently. Do not wait for one tool result before issuing the next independent call.`
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}
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### Command execution
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Never use \`sleep\` to wait for commands to complete. Commands run synchronously — when the shell tool returns, the command has finished.
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