session-learn
SolidUse when a completed work session should yield durable concepts, corrections, decisions, reusable patterns, and a traceable next action.
AI & Automation 137 stars
20 forks Updated 3 weeks ago MIT
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Skill Content
# Session Learn
<skill_contract>
<input>Completed session objective, actions, artifacts, verification receipts, errors, decisions, and destination paths.</input>
<output>Deduplicated durable deltas for concepts, entities, corrections, patterns, ideas, decisions, and gaps.</output>
<done>Each retained delta is formatted, linked, logged, provenance-preserving, and paired with a traceable next action when unresolved.</done>
<non_goals>Automatic-capture claims without a hook, raw transcript storage, conversational filler, or immutable-source edits.</non_goals>
Close a session by extracting only reusable deltas. Invocation must be explicit or performed by a verified external hook; this skill never claims it ran automatically.
## Usage Template
Provide: session objective, actions, outputs, verification receipts, errors, decisions, and destination paths. Optional: existing notes for deduplication.
## Workflow
<intake>
Establish the session boundary and compare intended versus observed result. Ignore conversational filler and separate execution evidence from retrospective interpretation.
</intake>
<unknowns_gate>
If the session outcome or evidence is unavailable, return `INSUFFICIENT_EVIDENCE`. Ask for a missing artifact only when it determines whether a lesson is valid; otherwise preserve it as an unresolved gap.
</unknowns_gate>
<execute>
Scan for seven signal types:
1. **Concept** — a stable mechanism worth linking.
2. **Entity** — a person, system, project, ...
Details
- Author
- Mark393295827
- Repository
- Mark393295827/third-brain-v7-skills
- Created
- 4 months ago
- Last Updated
- 3 weeks ago
- Language
- Python
- License
- MIT
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