agentleFS
kopp0510kopp0510/claude-dd/skills/self-improving-agent/CLAUDE.md

claude-dd / self-improving-agent

CLAUDE.md12 starsChanged 13 days agoMITView on GitHub

This plugin helps you curate Claude Code's auto-memory into durable project knowledge. Use the /self-improving-agent: namespace for all commands: Claude Code maintains ~/.claude/projects/<project-path>/memory/MEMORY.md automatically. The first 200 lines load into every session. When it grows too large, Claude moves details into topic files like debugging.md or patterns.md. This plugin reads that directory — it never creates its own storage. Check if anything Claude learned should become a permanent rule. Moves it from MEMORY.md (background note) to CLAUDE.md (enforced rule). Creates…

The file

We split this CLAUDE.md into the rules it gives an agent

3 rules. About 0 are common, 1 is distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Use the /self-improving-agent: namespace for all commands:

    line 7
  2. Distinctive:

    Check if anything Claude learned should become a permanent rule.

    line 27
  3. Very specific:

    Use those exact strings as subagent_type.

    line 60

≈ “Common” is an estimate: at least 1 in 5 of the 26,980 CLAUDE.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
CLAUDE.md

Self-Improving Agent — Claude Code Instructions

This plugin helps you curate Claude Code's auto-memory into durable project knowledge.

Commands

Use the /self-improving-agent: namespace for all commands:

  • /self-improving-agent:review — Analyze auto-memory health and find promotion candidates
  • /self-improving-agent:promote <pattern> — Graduate a learning to CLAUDE.md or .claude/rules/
  • /self-improving-agent:extract <pattern> — Create a reusable skill from a proven pattern
  • /self-improving-agent:status — Quick memory health dashboard
  • /self-improving-agent:remember <knowledge> — Explicitly save something to auto-memory

How auto-memory works

Claude Code maintains ~/.claude/projects/<project-path>/memory/MEMORY.md automatically. The first 200 lines load into every session. When it grows too large, Claude moves details into topic files like debugging.md or patterns.md.

This plugin reads that directory — it never creates its own storage.

When to use each command

After completing a feature or debugging session

/self-improving-agent:review

Check if anything Claude learned should become a permanent rule.

When a pattern keeps coming up

/self-improving-agent:promote "Always run migrations before tests in this project"

Moves it from MEMORY.md (background note) to CLAUDE.md (enforced rule).

When you solved something non-obvious that could help other projects

/self-improving-agent:extract "Docker build fix for ARM64 platform mismatch"

Creates a standalone skill with SKILL.md, ready to install elsewhere.

To check memory capacity

/self-improving-agent:status

Shows line counts, topic files, stale entries, and recommendations.

Key principle

Don't fight auto-memory — orchestrate it.

  • Auto-memory is great at capturing patterns. Let it do its job.
  • This plugin adds judgment: what's worth keeping, what should be promoted, what's stale.
  • Promoted rules in CLAUDE.md have higher priority than MEMORY.md entries.
  • Removing promoted entries from MEMORY.md frees space for new learnings.

Agents

Both register under the plugin namespace: self-improving-agent:memory-analyst and self-improving-agent:skill-extractor (plugin name + agent name — not the agent name twice). Use those exact strings as subagent_type.

  • skill-extractor: spawned by /self-improving-agent:extract Step 4 to generate complete skill packages
  • memory-analyst: available for cross-file pattern analysis. /self-improving-agent:review does not spawn it — that flow runs inline, start to finish. Spawn it yourself when you want an independent second pass over the memory files.

Hooks

The error-capture.sh hook fires on PostToolUse (Bash only). It scans the command's output text for error patterns and surfaces a short reminder (via hookSpecificOutput.additionalContext) suggesting /self-improving-agent:remember to save the solution — it does not write to auto-memory itself. Zero overhead unless an error pattern matches.

It matches the output text, not the exit status. The tool_response Claude Code hands the hook carries no numeric exit code at all — stdout / stderr / interrupted / isImage / noOutputExpected on every record, plus occasional extras, none of them an exit status (see hooks/CLAUDE.md for the measured field list; do not restate it as a closed set here). So a command that succeeded while printing failed or error: will also fire. Matching is per line, so one incidental console.error no longer silences a real failure beside it.

It is registered automatically by hooks/hooks.json — do not add it to settings.json by hand (see hooks/CLAUDE.md).

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.