* add repo learnings feature with edit history
introduces a new "Learnings" section in the repo console where agents can
persist operational knowledge (setup steps, test commands, conventions) at
the end of runs via an MCP tool. users can also edit learnings manually.
- add `learnings` field to Repo model and `LearningsRevision` audit table
- add `update_learnings` MCP tool for agents to persist repo knowledge
- integrate learnings into prompt assembly as REPO LEARNINGS section
- add learnings step to mode guidance (Build, AddressReviews, Plan, Fix, Task)
- add PATCH /api/repo/[owner]/[repo]/learnings endpoint (JWT auth)
- add GET /api/repo/[owner]/[repo]/learnings/history endpoint (Clerk auth)
- add LearningsSection component with textarea, save-on-blur, and history modal
- record revision history with actor tracking (agent vs user) and pruning (50 max)
- gate UI behind owner === "pullfrog" for internal dogfooding
Made-with: Cursor
* fix prisma enum import path for LearningsActor
Made-with: Cursor
* simplify learnings schema: remove LearningsActor enum, store model name directly
the actor/actorName split was unnecessary — learnings are only written by
agents so the revision table just needs a model column. removes all user
editing concepts from schema, API, and frontend.
Made-with: Cursor
* fix migration: add separate migration instead of rewriting existing one
restores original learnings_revisions migration and adds a new migration
that drops actor/actorName columns, backfills model from actorName, and
drops the LearningsActor enum.
Made-with: Cursor
* polish learnings feature: rename to Repo Intelligence, fix atomicity, fix review skip
- rename user-facing "learnings" to "Repo Intelligence" (UI, prompt section, wiki, sidebar)
- simplify description to "Automatically discovered by the agent across runs."
- wrap repo.update + revision create in $transaction for atomicity
- refactor recordLearningsRevision to pruneLearningsRevisions (prune-only)
- fix empty review skip: don't block APPROVE reviews with no body
- fix broken docs anchor: #free-options → #free-models
- update agent guidance to require flat bullet list format with pruning
- add accessibility: aria-expanded, sr-only loading, output element
- add chevron rotation, stale data clear on modal close, max-h scroll
- trim + length-limit model field, remove type cast, restore pre-existing comment
- update wiki prompt examples with actual bullet-formatted content
- update model test snapshot
Made-with: Cursor
* fix stale free model name in docs, rename utility file to match export
- docs/keys.mdx: MiMo V2 Flash → MiMo V2 Pro (matches model code change)
- rename recordLearningsRevision.ts → pruneLearningsRevisions.ts
Made-with: Cursor
* Add skill, .neon
* polish learnings UI and remove verbose log
- learnings code block: read-only appearance with muted text, copy button, rounded corners
- history modal: full-width rows with cursor-pointer, chevron moved to right, no preview text
- drop noisy update_learnings log line
Made-with: Cursor
* inject learningsStep into all modes, drop seed script, soften revision styling
Made-with: Cursor
* Drop seed
---------
Co-authored-by: Colin McDonnell <colinmcd94@gmail.com>
Pullfrog is a GitHub bot that brings the full power of your favorite coding agents into GitHub. It's open source and powered by GitHub Actions.
Tag @pullfrog — Tag @pullfrog in a comment anywhere in your repo. It will pull in any relevant context using the action's internal MCP server and perform the appropriate task.
Prompt from the web — Trigger arbitrary tasks from the Pullfrog dashboard
Automated triggers — Configure Pullfrog to trigger agent runs in response to specific events. Each of these triggers can be associated with custom prompt instructions.
issue created
issue labeled
PR created
PR review created
PR review requested
and more...
Pullfrog is the bridge between your preferred coding agents and GitHub. Use it for:
🤖 Coding tasks — Tell @pullfrog to implement something and it'll spin up a PR. If CI fails, it'll read the logs and attempt a fix automatically. It'll automatically address any PR reviews too.
🔍 PR review — Coding agents are great at reviewing PRs. Using the "PR created" trigger, you can configure Pullfrog to auto-review new PRs.
🤙 Issue management — Via the "issue created" trigger, Pullfrog can automatically respond to common questions, create implementation plans, and link to related issues/PRs. Or (if you're feeling lucky) you can prompt it to immediately attempt a PR addressing new issues.
Literally whatever — Want to have the agent automatically add docs to all new PRs? Cut a new release with agent-written notes on every commit to main? Pullfrog lets you do it.
Standalone Usage
You can also use pullfrog/pullfrog as a step in your own workflows. The action exposes a result output that can be consumed by subsequent steps.
Example: Auto-generate release notes on new tags
name:Releaseon:push:tags:['v*']permissions:contents:writejobs:release:runs-on:ubuntu-lateststeps:- name:Checkoutuses:actions/checkout@v4with:fetch-depth:0- name:Generate release notesid:notesuses:pullfrog/pullfrog@v0with:prompt:| Generate release notes for ${{ github.ref_name }}.
Compare commits between this tag and the previous tag.
Format as markdown: summary paragraph, then ### Features, ### Fixes, ### Breaking Changes sections.
Omit empty sections. Be concise.env:ANTHROPIC_API_KEY:${{ secrets.ANTHROPIC_API_KEY }}# write to file to avoid shell escaping issues with special characters- name:Create GitHub releaserun:| notesfile="$RUNNER_TEMP/release-notes-$GITHUB_RUN_ID.md"
printf '%s' "$NOTES" > "$notesfile"
gh release create ${{ github.ref_name }} --title "${{ github.ref_name }}" --notes-file "$notesfile"env:GH_TOKEN:${{ github.token }}NOTES:${{ steps.notes.outputs.result }}
Example: Structured Output with Zod Schema
You can force the agent to return structured JSON output by providing a JSON schema. This allows you to reliably parse and use the agent's response in subsequent workflow steps.
You can define your JSON schema directly or uou can use any validation library that converts to JSON Schema. Here's an example using Zod:
name:Release Checkon:pull_request:types:[closed]jobs:check-release:if:github.event.pull_request.merged == trueruns-on:ubuntu-lateststeps:- uses:actions/checkout@v4- name:Install dependenciesrun:npm install --no-save --no-package-lock zod @actions/core- name:Generate Schemaid:schemarun:| node -e '
import { z } from "zod";
import { setOutput } from "@actions/core";
const schema = z.object({
version: z.string().describe("Semantic version number (e.g. 1.0.0)"),
isBreaking: z.boolean().describe("Whether this release contains breaking changes"),
changelog: z.array(z.string()).describe("List of changes in this release"),
});
setOutput("schema", JSON.stringify(z.toJSONSchema(schema)));
'- name:Analyze PRid:analysisuses:pullfrog/pullfrog@v0with:prompt:| Analyze this PR and determine semantic versioning impact.
Return a JSON object matching the provided schema.output_schema:${{ steps.schema.outputs.schema }}env:ANTHROPIC_API_KEY:${{ secrets.ANTHROPIC_API_KEY }}- name:Process Resultrun:| # Parse the JSON result using fromJSON()
echo "Version: ${{ fromJSON(steps.analysis.outputs.result).version }}"
echo "Breaking: ${{ fromJSON(steps.analysis.outputs.result).isBreaking }}"