Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.
Security Analysis
high confidenceThis instruction-only skill is internally consistent: it documents how the agent should capture learnings/errors into local .learnings Markdown files and how to promote items into project memory; it asks for no installs, credentials, or external access.
Name/description match the behavior in SKILL.md: creating and appending learning/error/feature-request entries to .learnings/* and promoting broad learnings to project files (CLAUDE.md, AGENTS.md). No unexpected binaries, env vars, or network endpoints are requested.
Instructions stay within the stated purpose (logging and promoting learnings). They explicitly instruct the agent to create/write .learnings/, append formatted Markdown, search the .learnings/ directory, and update project files. This is expected for a logging skill, but the guidance is broad (e.g., 'Environment details if relevant' and 'Promote to project memory') and grants the agent permission to modify repository files — consider whether you want autonomous edits vs. user-approved changes.
No install spec and no code files — lowest risk. The skill is instruction-only and will not download or write executables to disk beyond the Markdown files it instructs the agent to create.
The skill declares no required environment variables or credentials, which is appropriate. However, the logging templates encourage capturing 'Environment details' and 'Context' for errors; without explicit redaction guidance the agent could inadvertently log sensitive config, secrets, or credentials from the environment. This is a privacy/safety concern to mitigate operationally.
always:false and default invocation settings are appropriate. The skill will persist data by writing project files (.learnings/*, CLAUDE.md, AGENTS.md) — this is expected for its purpose but does mean the agent will modify repository contents, so consider commit/review controls.
Guidance
This skill is coherent and appears to do what it says: log learnings/errors to .learnings/*. Before installing, consider these operational safeguards: (1) Decide whether the agent should write directly to the repo or only prepare entries for human review — require manual approval before committing/promoting entries. (2) Add .learnings/* to .gitignore or otherwise ensure sensitive logs aren't accidentally committed to VCS. (3) Add an explicit redaction step to the skill (or your agent workflow) so environment details, stack traces, or pasted inputs are scrubbed for secrets (API keys, passwords, tokens, PII) before being saved. (4) Limit who or what can invoke this skill if you don't want autonomous edits. (5) If you prefer centralized, auditable storage for learnings, adapt the workflow to send sanitized entries to a secure logging store rather than raw files. These mitigations will preserve the skill's usefulness while reducing accidental leakage or unwanted repo modification.
Latest Release
v1.0.0
Initial release of the self-improvement skill for structured learnings and error logging. - Enables agents to capture learnings, corrections, errors, and feature requests in dedicated markdown files under `.learnings/`. - Provides clear logging templates and category/tag structure for learnings, errors, and feature requests. - Outlines criteria for promoting broadly relevant learnings to persistent project memory files (`CLAUDE.md`, `AGENTS.md`). - Includes guidelines for recurring pattern detection, priority assignments, and periodic review practices. - Offers quick reference tables, command examples, and review scripts to streamline adoption. - Designed to support continuous improvement and reduce repeat mistakes.
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Published by @dc-acronym on ClawHub