aeonfun/self-improve

> ${var} — Mode selector, optionally with a focus area, as mode or mode:focus. > - empty or improve → improve mode: find and fix the highest-impact issue from recent logs, then propose + apply the fix via PR (default). > - improve:<area> (or a bare area like notifications) → improve mode focused on that specific area (e.g. heartbeat, notifications, memory). > - audit → audit mode: review what the agent did, what failed, and what to improve; save a full review and apply safe, obvious fixes directly. > - audit:<area> → audit mode focused on that specific area (e.g. reliability, memory).

Setup (both modes)

Parse ${var} into a mode and an optional focus area:

• Split on the first : — the part before is the mode, the part after is the focus.
• If the mode is audit → run the Mode: audit branch below (focus = optional area to concentrate the review on).
• If the mode is improve or empty → run the Mode: improve branch below (focus = optional area to fix).
• If the token is neither keyword but non-empty (e.g. notifications) → treat it as improve mode with the whole ${var} as the focus area (backward compatibility).

Then:

• Read memory/MEMORY.md for high-level context and goals.
• Read recent memory/logs/ (improve mode: last 2 days; audit mode: last 7 days) for errors, failures, and quality issues.

If a focus area is set, concentrate the run on that area.

Mode: improve (default)

Improve the agent itself based on recent performance. ONE change per run.

Steps

1. Check for open improvement PRs — don't pile up unreviewed work:

bash OPEN_PRS=$(gh pr list --state open --json title,number --jq '[.[] | select(.title | test("^(fix|feat|chore)\\("; "i"))] | length') If there are already 3+ open improvement PRs, log "self-improve: 3+ open PRs, waiting for review" and exit. Don't create more debt.

1. Identify what to improve. If the focus area is empty, scan for issues:

• Read memory/logs/ from last 2 days — look for:
• Skills that failed or produced low-quality output
• Errors, timeouts, "zero output", rate limiting
• Notifications that didn't send or were truncated
• Memory consolidation problems
• Read memory/cron-state.json for skills with low success rates
• Read output/articles/repo-actions-*.md from last 7 days for self-improvement ideas
• Pick the highest-impact, smallest-effort fix. One change per run.

1. Understand the area you're fixing. Read the relevant files:

• Skills: skills/{name}/SKILL.md
• Config: aeon.yml
• Workflows: .github/workflows/*.yml
• Agent instructions: CLAUDE.md
• Dashboard: apps/dashboard/ (if UI-related)

Understand the current behavior before changing anything.

1. Implement the fix. Make minimal, targeted changes:

• If a skill prompt is unclear → rewrite the ambiguous section
• If a skill is hitting rate limits → add backoff logic or reduce frequency
• If output quality is low → tighten the prompt, add examples, clarify format
• If a notification is broken → fix the formatting or truncation
• If a config is wrong → fix aeon.yml

Do NOT:

• Rewrite entire skills from scratch
• Add new features (that's create-skill's job)
• Change the core architecture
• Modify secrets or environment variables

1. Create a branch and PR:

bash git checkout -b fix/self-improve-${today} git add -A git commit -m "fix: description of what was improved]

Problem: what was failing/degraded] Fix: what was changed] Evidence: log entries, error messages, success rates]" Open a PR: bash gh pr create --title "fix: short description]" \ --body "## Problem What was failing or degraded — cite specific log entries or error messages]

## Fix What was changed and why]

## Evidence

• Relevant log entries]
• Success rate before: X%]
• Error pattern: ...]"

1. Notify. Send via ./notify:

self-improve: [what was fixed] — PR: [url]

1. Log (see the shared ## Log section below).

Guidelines

• ONE fix per run. Don't bundle unrelated changes.
• Smallest viable fix. A one-line prompt tweak > a full rewrite.
• If you can't find anything to improve, that's fine. Log "self-improve: everything looks healthy" and exit.
• Never modify workflow files (.github/workflows/) — only skill files, CLAUDE.md, and aeon.yml.
• Don't create circular improvements (e.g. don't improve self-improve).

Mode: audit

Audit what the agent did, what failed, and what to improve. Produce a full review, apply safe fixes, and surface recommendations.

Steps

Read memory/MEMORY.md for context and goals. Read ALL memory/logs/ entries from the last 7 days.

1. Audit quality of outputs:

• Read recent articles in output/articles/ — are they substantive or formulaic?
• Check recent notifications in logs — were they useful or noisy?
• Review any PR comments posted — were they actionable?

1. Audit reliability:

• How many skills ran vs expected?
• Any repeated errors or patterns of failure?
• Are monitors catching real issues or always returning OK?

1. Audit memory hygiene:

• Is MEMORY.md current and under 50 lines?
• Are logs structured consistently?
• Any stale data that should be cleaned?

1. Generate improvement recommendations:

• Skills to add, modify, or disable
• Schedule adjustments
• Config changes (feeds, repos, addresses to add/remove)
• Quality improvements (better prompts, new data sources)

1. Save the full review to output/articles/self-review-${today}.md.
2. Apply any safe, obvious improvements directly:

• Prune stale MEMORY.md entries
• Update feeds.yml if feeds are dead

1. Send a summary via ./notify:

*Self Review — ${today}* Quality: assessment Reliability: X/Y skills ran Actions taken: what was fixed Recommendations: top 2-3 suggestions

1. Log (see the shared ## Log section below).

Log

After completing the run, append a log entry to memory/logs/${today}.md under a single ### self-improve heading, with a discriminator line naming the mode that ran:

### self-improve
- **Mode:** improve  (or: audit)

Then, for improve mode:

- **Target:** [what was improved]
- **Problem:** [what was failing]
- **Fix:** [what was changed]
- **PR:** [url]

For audit mode:

- **Review:** output/articles/self-review-${today}.md
- **Quality:** [assessment]
- **Reliability:** [X/Y skills ran]
- **Actions taken:** [what was fixed directly]
- **Recommendations:** [top 2-3]

Network note

Write mode. Both branches touch the repo (improve opens a PR via git/gh; audit writes output/articles/self-review-${today}.md and may prune MEMORY.md/feeds.yml). For the GitHub API, use the gh CLI (gh pr list, gh pr create) — it handles auth internally, so no $SECRET ever touches the command line (a bare secret on the line is what the Bash permission layer refuses; there is no network sandbox). No pre-fetch or post-process side-channel is needed.