| name | wf-learn |
| description | Use for /wf-learn in Claude Code, $wf-learn or /skills wf-learn in Codex, or when the user wants a learning cycle from repeated errors, corrections, patterns, or session history. |
WF Learn Adapter
Force a memory learning cycle. Context-master analyzes; memory-master
consolidates. Use the active runtime's available subagent mechanism when
present, otherwise emulate the same roles as bounded passes and record that
fallback.
Note: Explicit user preferences (remember/next time/never/always/记住/下次/不要再) can be written immediately via candidate detection without waiting for /wf-learn. /wf-learn is for proactive pattern consolidation and closeout extraction.
Load
Harness/MEMORY.mdHarness/memory/routes.mdHarness/memory/startup-hints.mdHarness/memory/tool-usage-reflections.mdHarness/memory/user-corrections-preferences.mdHarness/memory/agent-lessons-patterns.md- Current
Harness/PROGRESS.md and active task capsule, if any
Cache Discipline
Follow Harness/specs/runtime/context-loading.md#Cache-First Context Contract: load memory
indexes first, then only the routed detailed memory files; summarize durable
patterns by file path and signal instead of pasting session transcripts.
Flow
- Analyze the session for repeated failures, durable user corrections, and
reusable review/debug lessons.
- Check
Harness/memory/routes.md for existing entries before writing.
- Deduplicate against existing memory.
- Write only concise, durable, non-secret lessons to
Harness/memory/*.
Use compact format (default no date):
- When <scenario>: <rule>. Avoid <over-application>. Signals: <signals>.
Return
Report files updated, patterns extracted, skipped candidates, and why each
memory entry should survive context loss.
