drain

name	drain
description	Triage accumulated learnings from the local harny inbox into GitHub Issues, AGENTS.md edits, or discards. Walks one entry at a time, verifies claims against current code, opens issues with provenance. Sister of /learn.
allowed-tools	Bash, Read, Edit, Write

drain — analytical triage of the harny learnings inbox

The drainable companion to /learn. Walks the user through the inbox at <cwd>/.harny/LEARNINGS.local.md (and optionally .harny/*/review.md files), classifying each entry into a destination — GitHub Issue, AGENTS.md edit, or DISCARD — with evidence cited.

This skill is analytical and slow. Unlike /learn (which captures verbatim), drain verifies claims, decomposes multi-part actions, and writes back changes only with the user's approval per entry.

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Inputs

• <cwd>/.harny/LEARNINGS.local.md — raw captures from /learn.
• <cwd>/.harny/*/review.md — per-run reviews produced by /review. Treat the "Architect proposals" section as drainable; inline review narrative is context only.

If neither source has content, tell the user there's nothing to drain and stop.

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UX — walk one at a time

Batch summary tables tempt bulk classification without thinking. Walk one entry at a time, human-in-the-loop.

For N > 10 entries, offer the user a pause marker mid-drain:

5 done, 7 remaining — continue, or pause here?

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Per-item process

For each entry, in order:

1. Read the entry verbatim back to the user

So you both look at the same words.

2. Verify claims against current state

Before classifying, check the code/repo:

• References to a file/commit/function — does it exist? Does the referenced behavior match? Use Read, git log -- <path>, git show <sha>.
• Look for absorption markers. "Permanent fix landed", "Already infra-shipped", "Convention enshrined in AGENTS.md" — strong DISCARD signals. Verify each.
• Correlate with run history. An entry about "task trailer duplication" + a run named dedup-task-trailer → fix likely landed. Check git log --all --oneline --grep <keyword>.
• AGENTS.md cross-check. If the entry's principle is now documented, it's been absorbed.

3. Decompose multi-part actions

If the entry has sub-actions (a), (b), (c), triage each separately. Common pattern: (a) and (b) landed, (c) is still open → opens an Issue scoped to (c) only, discards (a)+(b).

4. Apply the counterfactual test

Would a fresh dev, reading only AGENTS.md + code, hit the same friction?

If yes → there's still teaching to do (AGENTS.md edit or Issue). If no → the lesson has been absorbed elsewhere → DISCARD.

5. Propose a destination

Load the classification patterns once, early in the drain:

Read ${CLAUDE_SKILL_DIR}/patterns.md

Match the entry to one of the 6 patterns. Propose the destination with evidence.

6. Wait for user approval

Show:

• The classification verdict
• The evidence supporting it
• The proposed action (DISCARD, OPEN ISSUE, AGENTS.md edit, DEFER)

Do not execute until the user says go.

7. Execute

Per verdict:

• DISCARD — Edit .harny/LEARNINGS.local.md to remove the entry. No other artifact created.
• PROMOTED to AGENTS.md — Apply the edit (Edit tool). Remove inbox entry.
• OPEN ISSUE — Use gh issue list --search ... to dedup first; then gh issue create with proper title prefix and learning label. Remove inbox entry.
• OPEN DISCUSSION — gh discussion create with rfc: or decide: prefix. Remove inbox entry.
• DEFERRED — Edit the entry in place to add [deferred YYYY-MM-DD: <reason>]. Keep entry.

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Side-effect: stale doc drift

While verifying entries, you'll often spot unrelated documentation drift — an AGENTS.md paragraph describing a value that changed months ago, a §N reference pointing at a deleted doc, etc.

Rule:

• 1-2 line factual fix verifiable from code → propose inline alongside the current entry's verdict.
• Larger drift (paragraph, multiple refs, architectural staleness) → open a separate Issue with label documentation rather than expanding the entry's verdict.

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Cluster detection

Track classification cohorts during the walk. At the end, emit concise cluster alerts:

• "Migration debt": N entries absorbed by file X scheduled to migrate. List what must be preserved.
• "Issue family": N entries opened as Issues under a common theme. Propose a tracking milestone or umbrella Issue.
• "Doc drift found": Inline fixes applied during the walk. Summarize for the user's review.

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GitHub discipline

Issues

• Dedup first. gh issue list --search "<key terms>" --state all --json number,title,state. Surface matches before opening.
• Title prefix: feat:, bug:, learning:, docs:, chore:.
• Labels: always learning if origin was a drained entry, plus one of enhancement / bug / documentation.
• Body must include an "Origin" section citing the source (file path + original entry text). Preserves provenance.

Discussions

• Use Discussions (not Issues) when the entry poses an open question ("is this worth doing?", "which of 3 approaches?") rather than a ready-to-implement change.
• Title prefix: rfc: for debate, decide: for decision-shaped prompt.
• Labels: rfc or decision. Add resolved after the discussion concludes (enables ADR-style search via label:decision label:resolved).

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Inbox mutation

• DISCARD / PROMOTED / ISSUE-OPENED / DISCUSSION-OPENED → delete the entry from .harny/LEARNINGS.local.md.
• DEFERRED → keep and annotate with [deferred YYYY-MM-DD: <reason>].
• No separate history of drained items is kept. The resulting Issue / commit / Discussion IS the history.

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What this skill does NOT do

• Does not auto-classify in batches without human approval.
• Does not edit files outside .harny/LEARNINGS.local.md, the proposed AGENTS.md edits, and inline doc-drift fixes (each approved per-entry).
• Does not bulk-open issues — every Issue creation is a single, deduped, evidence-backed action.

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Edge cases

• Inbox does not exist → tell user, suggest /learn to capture first.
• Entry references a slug whose .harny/ dir was cleaned → state is gone, but the entry text is still drainable. Verify against current code instead.
• gh not authenticated → ask user to gh auth login. Do not proceed with Issue/Discussion actions.
• User rejects a proposed classification → take the feedback. Their context overrides yours. Re-classify or defer.
• Entry mid-drain triggers a follow-up thought from the user → suggest they /learn it; resume drain.