# Intelligence Learn From Session

> Capture session lessons and workflows in project context

- Skill: `ainova-systems/intelligence-learn-from-session` (Agent Skill)
- Install (CLI): `npx skillmds@latest add ainova-systems/intelligence-learn-from-session`
- Raw SKILL.md: https://api.skillmd.com/api/skills/ainova-systems/intelligence-learn-from-session/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: ainova-systems (https://skillmd.com/u/ainova-systems)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/ainova-systems/intelligence-learn-from-session

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# Learn from a session

Capture a durable preference, working pattern, recurring friction, or successful
workflow from a session in an established Intelligence project. This skill owns
identifying and generalizing the lesson; `intelligence-update-context` owns writing it.

## Verify readiness

1. Locate `<manifest>`, `<content-dir>`, and `<module>`, then run
   `intelligence status --check`. Missing or inconsistent setup, an onboarding
   pending header, or unresolved preserved instructions routes to
   `/intelligence-learn-from-repository` for repair and migration. Stop session
   capture until onboarding is complete. A retained backup manifest or converted
   legacy config alone does not mean onboarding is incomplete.

## Analyze and propose

2. Identify the lesson from the conversation or explicit user input. For a
   workflow, list the actual steps performed, user decisions, branches, failure
   recovery, and verification. Retain the sequence that worked.
3. Generalize the evidence by removing instance-specific filenames, dates, and
   phrasing. Keep the reason needed to apply the lesson to the next task. Prefer
   a positive instruction such as "Default to one recommendation" for "Stop
   generating three options". Preserve safety prohibitions; confirm a translation
   if changing the negation changes meaning. Keep a negative example only when
   paired with its replacement and useful for recognizing the pattern.
4. Inspect configured sources for an existing owner. A preference or constraint
   belongs in a rule, path-specific context in a scoped rule, an observed
   repeatable procedure in a skill, and a persona or expertise boundary in an
   agent. Prefer extending an existing artifact over adding a sibling.
5. Present each proposal with its action (`CREATE`, `UPDATE`, or `ARCHIVE`),
   source path, concrete draft, and one-line reason. This phase is read-only;
   only user-accepted lessons become persistent instructions. Reuse approval
   already given for the exact proposal.

## Apply and verify

6. Pass accepted proposals and their session evidence to
   `/intelligence-update-context`. It handles artifact-specific authoring,
   references, a single batch sync, and the final status check.
7. Compare the resulting source changes with the accepted lesson. For a workflow,
   verify that its decisions, working steps, recovery, and proof of completion
   remain executable without this conversation. Report the saved lesson, its
   owner, and verification; a session-specific transcript is not completion.