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Gotcha Harvest

ASecurity

Harvest discovery-driven lessons from autonomous loops. Scans a session (or --days N of history) for 'CI/check failed → fix → passed' arcs and recurring tool-errors, then proposes entries for .claude/rules/gotchas.md (repo-specific) or your frontmatter-per-fact memory (cross-repo). Use after /implement-queue runs, or invoke /gotcha-harvest. Complements hand-written corrections, which are correction-driven and miss these.

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Added 9/22/2026
ai-agentsgobashnodegitdatabase

Works with

claude codecli

Security Analysis

A100/100

Scanned 9/22/2026

Install to Claude Code

$npx -y skills add mattbutlerengineering/mattbutlerengineering --skill gotcha-harvest --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: gotcha-harvest
description: "Harvest discovery-driven lessons from autonomous loops. Scans a session (or --days N of history) for 'CI/check failed → fix → passed' arcs and recurring tool-errors, then proposes entries for .claude/rules/gotchas.md (repo-specific) or your frontmatter-per-fact memory (cross-repo). Use after /implement-queue runs, or invoke /gotcha-harvest. Complements hand-written corrections, which are correction-driven and miss these."
user-invocable: true
allowed-tools: Read, Edit, Write, Glob, Grep, Bash, AskUserQuestion, TodoWrite
---

# Gotcha Harvest

Hand-written corrections in `.claude/memory/corrections/` capture places where a human told the agent "no, do X." Autonomous loops (`/implement-queue`) rarely produce those; their lessons are **discovery-driven**: a CI check fails, the agent diagnoses and fixes it, the check passes. That arc is the richest source of reusable gotchas and a human-correction capture structurally never sees it. This skill harvests it.

**Output is a proposal, never a silent write.** Always show findings and get a human decision before editing any file.

## Arguments

- (none) — scan the **current session** transcript only.
- `--days N` — scan the last N days (default 7 when the flag is bare).
- `--source transcript|github|auto` — where to mine from (default `auto`).
- `--dry-run` — show proposals, write nothing.

## Source modes

The failure→fix→pass arc lives in two places; pick by where you're running:

- **`transcript`** — local session `.jsonl` files. Richest signal (the agent's own reasoning + the exact commands), but only exists on the machine that ran the loop, and Claude Code prunes sessions after 30 days. Use locally.
- **`github`** — the repo's merged-PR + CI-run history via `gh`. Durable and available **in a cloud/CI checkout with no local files** — this is the mode a scheduled cloud routine must use. Lower fidelity (you see the failed check and the fixing commit, not the deliberation), but the arc is still recoverable.
- **`auto`** (default) — `transcript` if local session files for this project exist, else `github`.

## Process

### Step 0: Track the run

Use TodoWrite with: locate transcripts → detect arcs → synthesize gotchas → dedupe → route → review → apply.

### Step 1: Locate the source

**Resolve the mode** (`--source`, default `auto`):

```bash
# transcript candidates for this project (paths have / replaced by -)
ls ~/.claude/projects/ | grep -i "$(basename "$(pwd)" | tr '_' '-')"
```

- If candidates exist (or `--source transcript`) → **transcript mode**: no flag = most recent non-`agent-*` `.jsonl`; `--days N` = every `*.jsonl` (incl. `agent-*.jsonl` — workers hit the recurring drift/typecheck failures) modified within N days.
- If none exist (cloud/CI) or `--source github` → **github mode**: gather the window's history (the `date` math below; BSD/macOS `date -v`, GNU `date -d`):

  ```bash
  SINCE=$(date -u -v-7d +%F 2>/dev/null || date -u -d '7 days ago' +%F)
  gh pr list --state merged --search "merged:>=$SINCE" --json number,title,mergedAt --limit 50
  gh run list --created ">=$SINCE" --status failure --json databaseId,headBranch,workflowName --limit 50
  ```

### Step 2: Detect failure→fix→pass arcs

**Transcript mode** — scan for this shape, in order:

1. **A signal of a check failing** — a tool result or assistant line containing CI/build feedback. Anchor patterns (case-insensitive):
   - `❌`, `FAIL`, `exit code 1`, `ELIFECYCLE`, `Process completed with exit code`
   - named checks: `CI Gate`, `Integrity`, `Build`, `typecheck`, `lint`, `instruction rot`, `dependency-graph.md is stale`, `llms.txt … out of sync`, `frozen-lockfile`, `check-adr`, `check-deps`
2. **An action taken in response** — an Edit/Write/Bash between the failure and the recovery (regenerate, rebase, add a step, change a value).
3. **A recovery signal** — a later "all pass" / green / merged / "✓" for the same check.

Also collect **recurring tool-errors**: the same error class (e.g. `@mbe/agent-core … not built`, `vitest: command not found`, lockfile desync) appearing **2+ times** across the scanned scope — these are gotchas even without a clean arc.

Discard one-off transient failures with no fix and no recurrence.

**GitHub mode** — reconstruct the arc from history:

1. For each failed run from Step 1, read its failing job log for the anchor patterns above:
   ```bash
   gh run view <databaseId> --log-failed | grep -iE 'error|fail|drift|stale|out of sync|rot|exit code'
   ```
2. Find the **fix**: the next commit/PR on that branch that turned the same check green — inspect its diff and message:
   ```bash
   gh pr view <N> --json commits,files
   gh pr diff <N> --name-only
   ```
   Commits like `chore: regenerate …`, `fix: … drift`, follow-up pushes after a red check are the fix signal.
3. A check that failed on a PR and passed after a specific commit **is** an arc — the failing log gives the cause, the fixing diff gives the remedy. Cluster identical failures across PRs (e.g. the same llms.txt drift on 3 PRs) into one recurring-gotcha.

Lower fidelity than transcripts (no agent reasoning), so when the cause is ambiguous from the log alone, mark the proposal `needs-confirmation` rather than asserting it.

### Step 3: Synthesize a one-line gotcha per arc

Imperative, cause→fix, ≤2 lines. Mirror the existing `gotchas.md` voice (terse, concrete, command-bearing). Example shapes:

- "Deleting a workspace package drifts the **root** llms.txt — `pnpm pack-changed` misses it; regenerate with `node tools/cli/dist/index.js pack .` and run `detect-instruction-rot.mjs`."
- "Worktree agents must `pnpm build --filter @mbe/agent-core...` before `tools/cli` typecheck — fresh checkouts have no dist."

### Step 4: Dedupe against existing knowledge

```bash
grep -niE "<keyword>" .claude/rules/gotchas.md
```

If a near-match exists, propose **merge/refine** rather than a new bullet. Also skip lessons **already encoded this session** into a skill/agent/PR (check `git log --oneline origin/main..HEAD` and the session for edits that already fixed it) — re-proposing what you just shipped is noise.

### Step 5: Route each gotcha

| Kind of lesson                                                           | Destination                 | How                                                                                                                                                           |
| ------------------------------------------------------------------------ | --------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Repo CI / build / pre-commit / drift / release / deploy / Prisma         | `.claude/rules/gotchas.md`  | append a bullet under the matching `## ` section (Pre-commit / Pre-push / Build / CI / Dependencies / Releases / Tooling / Auth0 · E2E / Prisma · DO migrate) |
| Cross-repo Claude Code / harness / tooling fact (true outside this repo) | frontmatter-per-fact memory | see **Memory schema** below                                                                                                                                   |
| Workflow/process correction tied to a specific skill                     | that skill's `SKILL.md`     | only when it changes how the skill should behave                                                                                                              |

If no `## ` section fits a repo gotcha, propose a new section header.

### Step 6: Review, then apply

Always present a compact table first (`#`, gotcha, destination, new/merge, confidence).

- **Interactive (local)** → `AskUserQuestion`: Apply all / Select / Skip. Apply with `Edit` (stage specific files only — never `git add -A`). Report what landed where.
- **Unattended (cloud routine, no human to prompt)** → do **not** write to `main` and do **not** silently apply. Create a branch, apply the proposals, and open a PR titled `chore(gotchas): harvested from CI history (last N days)` with the proposal table in the body for human review. This is the conservative scheduled-run contract: propose via PR, never auto-commit to `main`. If there are zero proposals, exit quietly without a PR.

On `--dry-run`, stop after the table regardless of mode.

## Memory schema (cross-repo facts)

Cross-repo facts go to `~/.claude/projects/<project>/memory/` as **one file per fact** with this frontmatter — the same schema as `MEMORY.md`, so the manual memory protocol, this skill, and any future auto-memory path all converge on one format (resolves the two-schema split in that directory):

```markdown
---
name: <short-kebab-case-slug>
description: <one-line summary used for recall>
metadata:
  type: feedback | reference
---

<the fact. **Why:** … **How to apply:** … Link related facts with [[their-name]].>
```

After writing the file, add one index line to `MEMORY.md`: `- [Title](file.md) — hook`. Never put fact bodies in `MEMORY.md`.

## Relationship to hand-written corrections

- **Hand-written correction** → human corrections, routed to CLAUDE.md / rules / skills. Written directly to `.claude/memory/corrections/` during interactive sessions; there is no skill that does this for you.
- `/gotcha-harvest` → agent-discovered CI/build lessons, routed to `gotchas.md` / memory. Run it after autonomous loops.

They are complementary; doing both loses nothing because each dedupes against the shared targets.

Attribution

mattbutlerengineeringmattbutlerengineering
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