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Extract non-obvious session learnings into scoped AGENTS.md files
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Basierend auf der SOC-Berufsklassifikation
Retrieve semantically relevant past learnings and analysis outputs using the csm CLI (HDC encoder with hybrid BM25 retrieval)
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Atomic git workflow - validates, commits, pushes, creates PR, and verifies CI with zero-warnings policy. Orchestrates complete code submission as state machine with rollback on failure.
Automated code review with PR analysis, change summaries, and quality checks. Use for reviewing pull requests, generating review comments, checking against best practices, and identifying potential issues. Includes style guide compliance, security issue detection, and review automation.
Unified atomic git workflow with GitHub integration - commits all changes, checks GitHub issues, creates PR, validates all Actions pass including pre-existing, uses swarm coordination with web research on failures. Post-merge validation of all files and docs.
| name | learn |
| description | Extract non-obvious session learnings into scoped AGENTS.md files |
| category | knowledge-management |
| trigger | after non-trivial task completion |
Extract non-obvious session learnings into scoped AGENTS.md files to preserve knowledge across sessions.
Activate after completing a non-trivial task to capture insights that would otherwise be lost.
agents-docs/ENVIRONMENT_VARIABLES.md).AGENTS.md + agents-docs/AVAILABLE_SKILLS.md when adding skills).Place learnings in the most specific AGENTS.md file:
AGENTS.md.scripts/AGENTS.md..agents/skills/<name>/AGENTS.md.Every new non-obvious insight must be recorded in two places:
LESSON-NNN entry to agents-docs/LESSONS.md with Issue/Root Cause/Solution.AGENTS.md (this is what learn automates).AGENTS.md.MAX_LINES_AGENTS_MD=150 constraint.agents-docs/LESSONS.md - Legacy project-wide lessons.AGENTS.md - Root agent guidance and constraints.