forge-deeplearn
Skill2 starsChanged 5 days agoMITView on GitHub
Use in an unknown repo or before a PRD or big refactor: read-only scan.
- Reads credentials
1 other project uses a version of this, 1 of them edited.
Adopted by
Most recently taken up by
- ForgeyClap/claude-forgeedited, first seen Oct 11, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 1
- ForgeyClap/claude-forge★ 295% same
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository99 other files it gives its agents.
- docs/AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- brainstormingSkill
- claude-md-improverSkill
- dispatching-parallel-agentsSkill
- executing-plansSkill
- finishing-a-development-branchSkill
- forge-a11ySkill
- forge-agent-reportSkill
- forge-agentSkill
- forge-apiSkill
- forge-authSkill
- forge-autoresearchSkill
- forge-botsSkill
- forge-brainstormSkill
- forge-cliSkill
- forge-cmsSkill
- forge-code-reviewSkill
- forge-contextSkill
- forge-councilSkill
- forge-craftSkill
- forge-databaseSkill
- forge-dataSkill
- forge-debugSkill
- forge-devopsSkill
- forge-docdriftSkill
- forge-doctorSkill
- forge-ecc-adapterSkill
- forge-ecommerceSkill
- forge-electronSkill
- forge-extensionSkill
- forge-figmaSkill
- forge-fullstackSkill
- forge-gameSkill
- forge-graded-verifySkill
- forge-guardianSkill
- forge-heartbeatSkill
- forge-i18n-docsSkill
- forge-intakeSkill
- forge-integrationSkill
- forge-long-form-writingSkill
- forge-mcp-clientsSkill
- forge-memorySkill
- forge-migrationSkill
- forge-mindmapSkill
- forge-mlopsSkill
- forge-mobileSkill
- forge-n8nSkill
- forge-nightshiftSkill
- forge-observabilitySkill
- forge-paymentsSkill
- forge-plan-largeSkill
- forge-prdSkill
- forge-predictionSkill
- forge-projectbrainSkill
- forge-prompt-coachSkill
- forge-qualitySkill
- forge-ragSkill
- forge-registrySkill
- forge-releaseSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 13
Before generating a PRD or acceptance criteria for a non-trivial feature.
- Distinctive: line 14
Before a large refactor, migration, or architecture change.
- Very specific: line 15
Not needed for a 1-2 line fix, or a project already scanned this session — check .claude/forge-artifacts/index.jsonl first.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Deep Learn Mode (WP2 — full-codebase priming scan)
Deep Learn Mode is an on-demand, read-only scan of the current project (.claude/forge-bin/forge-deeplearn.cjs) that produces an honest project-summary and risk-list BEFORE the Lead commits to a PRD or a big architectural change. It never writes into the scanned tree — its only output is its own artifact under .claude/ (with --store) and optional dashboard events.
When the Lead runs it
- A new or unfamiliar project (first
/forgerun, or "gebruik forge voor dit project" on a folder with no memory yet). - Before generating a PRD or acceptance criteria for a non-trivial feature.
- Before a large refactor, migration, or architecture change.
- Not needed for a 1-2 line fix, or a project already scanned this session — check
.claude/forge-artifacts/index.jsonlfirst.
How
node .claude/forge-bin/forge-deeplearn.cjs --path . --run <run_id> --store--path <dir>— defaults to the current directory.--run <run_id>— logsdeep_learn_started/deep_learn_completedto that run's dashboard events (omit to run standalone).--store— persists the full result viaforge-store.cjs(.claude/forge-artifacts/deeplearn-<epoch>.json).
What it outputs
Stack (node/python/go/rust/dotnet/php/static + framework hints from package.json deps), file counts by category, likely entry points, tests presence, the 5 largest code files, and a risk-list (high/med/low) covering missing tests, oversized files (>800 lines), a missing README, TODO/FIXME density, secret-looking strings, and an unignored .env. Feed the summary + risks straight into the PRD's acceptance criteria, and hand any high risk to the Security Boss / security-reviewer; a secret-looking hit under a test/fixture/docs location (test/, tests/, __tests__/, test-evidence/, fixtures/, docs/, *.test.*, *.spec.*, *.md) is instead reported as a med secret-pattern-fixture-looking risk with a note pointing at forge-doctor.cjs's leak scan (forge-secret-scrub.cjs) as the real authority.
Honesty rule (non-negotiable)
- Read-only. It only ever reads files under
--path; it never edits, deletes, or writes into the scanned project. Its only write is the explicit--storeartifact under.claude/forge-artifacts/. - Real findings only — every risk is backed by an actual file/pattern match; nothing is invented.
- Never prints or stores a raw secret. A secret-looking match is reported as
{file, pattern_name}only, never the matched text —forge-store.cjs's own redaction is a second safety net when--storeis used.
Deeper priming (optional, not required)
For genuinely deep semantic understanding beyond this structural scan, the Lead MAY additionally invoke the graphify skill (knowledge graph of the codebase) or the ECC learn-codebase skill (full-file read-through). A full-file read-through is costly: use it only for a large, unfamiliar codebase before a big change; otherwise the structural scan is enough. When reading big files, use chunks rather than loading entire files at once. Deep Learn Mode is fast and structural; those are slower and semantic — use them together on large/unfamiliar codebases, not as a replacement for each other.
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