Weekly Meta Audit

STARTER_CHARACTER = 🔍

Weekly Meta-Audit

A structured weekly self-audit that examines your agent's operational health, identifies gaps, and generates concrete improvement actions. Inspired by Outcome Engineering principles — measure outcomes, not outputs.

Purpose

Most AI agent setups accumulate invisible debt: silent cron failures, wrong assumptions in memory, manual work that should be automated, cross-project synergies nobody pursues. This skill surfaces all of it systematically.

When to Run

• Scheduled: Sunday evening / Monday morning (end-of-week retrospective)
• On demand: After a week with notable failures or when things feel "off"
• Recommended cadence: Weekly (diminishing returns if more frequent)

Prerequisites

The audit reads from your existing workspace structure. It works best with:

• Memory files: Daily logs (memory/YYYY-MM-DD.md) from the past 7 days
• Feedback file: Shared operational rules (memory/feedback/feedback.md or similar)
• Long-term memory: MEMORY.md with project state and decisions
• Cron system: OpenClaw crons (or any cron manager with list and runs commands)

If any of these don't exist, the audit adapts — it just has less data to work with.

Audit Process

Phase 1: Gather Context

Read these files (skip any that don't exist):

1. Operating principles — AGENTS.md or equivalent
2. Current state — MEMORY.md
3. Shared rules — memory/feedback/feedback.md
4. Last 7 daily logs — ls memory/2*.md | tail -7, read each
5. Cron list — Run openclaw cron list (or equivalent)
6. Recent cron runs — Run openclaw cron runs --limit 50

Phase 2: Analyze (All 11 Sections Mandatory)

Work through each section. Be specific, not generic — name cron IDs, script paths, project names, dates, and incidents. Every finding must have a concrete next action.

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1. MISSING TOOLS/AUTOMATIONS

What broke or required manual intervention this week that should be automated?

Format per finding:

• Incident: What happened (date, project, impact)
• Root cause: Why it wasn't caught automatically
• Proposed fix: Script/cron/workflow to prevent recurrence
• Build cost: Estimate (trivial / 30min / 2h / half-day)

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2. WRONG ASSUMPTIONS

What assumptions in feedback.md, MEMORY.md, cron prompts, or operational rules turned out wrong?

Check for:

• Feedback entries that no longer apply
• Memory entries that are stale or incorrect
• Cron prompts with outdated paths, models, or logic
• Standing rules that were violated without consequence

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3. NEXT WEEK LIKELY NEEDS

Based on active projects, blockers, and the human's recent attention — what will matter next week?

Rank by likely priority (what the human will ask about, not what you think is important).

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4. SKILLS TO DEVELOP

What capability gaps appeared this week? Name the specific task that exposed each gap.

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5. CONTEXT LOSSES

What information was lost between sessions or between agents? What should have been written down but wasn't?

Common patterns:

• Sub-agent decisions not logged (WHY choices were made)
• Verbal corrections not appended to feedback
• Cron failures missing task context
• Architecture decisions only in chat, not in docs

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6. CONNECTIONS UNMADE

Cross-project synergies, shared components, or bundling opportunities nobody is pursuing.

Think about:

• Shared audiences across projects
• Reusable code/infrastructure
• Cross-promotion opportunities
• Data that could enrich another project

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7. FRICTION → WORKFLOWS

Recurring friction points that should become automated workflows.

Format per finding:

• Friction: What keeps happening manually
• Frequency: How often (daily / weekly / per-deploy)
• Proposed workflow: Tool chain to automate it
• Compound value: Why this gets better over time

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8. NEW FEEDBACK ENTRIES

Write new entries for the feedback file based on this week's lessons.

Format:

### Entry N — YYYY-MM-DD
- **Pattern:** [What went wrong or what was learned]
- **Rule:** [Concrete rule to prevent recurrence]
- **Source:** [Incident or observation that triggered this]

Actually append them to the feedback file — don't just list them.

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9. LAST WEEK AUDIT

Two lists:

✅ Forward momentum — What shipped, what progressed, what unblocked ❌ Wasted effort — What was abandoned, repeated, took too long, or produced nothing

Be honest. "We spent 2 hours debugging X when Y would have been faster" is useful. "Everything went great" is not.

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10. GENERIC → SPECIFIC

Which cron outputs, reports, or agent responses are too generic? How should they be made more specific and actionable?

Test each report against: "Could someone act on this without asking follow-up questions?"

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11. COMPOUND SYSTEM

Propose ONE compound system (tool/script/cron combo) that would have the highest leverage over the next month.

Template:

• What it does: [Concrete description]
• What it replaces: [Current manual process]
• Build cost: [Hours estimate]
• Compound value: [Why it gets more valuable over time]
• First user: [Which project/workflow benefits first]

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Output Format

Send the full audit as a single message with all 11 sections. Use headers, tables, and bullet points for scanability.

Tone: Brutally honest. This is an internal operations review, not a status report for a stakeholder. Name problems clearly. Don't soften findings.

Cron Setup Example

openclaw cron add \
  --name "weekly-meta-audit" \
  --cron "0 20 * * 0" \
  --message "Perform the weekly meta-audit. Read the weekly-meta-audit skill instructions and follow them completely." \
  --model claude-sonnet-4-5 \
  --channel telegram \
  --to YOUR_CHAT_ID \
  --announce \
  --timeout-seconds 300 \
  --session isolated

Adjust the model based on your budget:

• Opus: Most thorough, catches subtle patterns
• Sonnet: Good balance of depth and cost (recommended)
• Haiku: Too shallow for meaningful audit — not recommended

Anti-Patterns

• ❌ "Everything looks good this week" — If nothing needs fixing, the audit isn't looking hard enough
• ❌ Vague recommendations ("improve monitoring") — Every finding needs a concrete next action
• ❌ Listing only successes — The ❌ section matters more than the ✅ section
• ❌ Repeating last week's findings without checking if they were fixed
• ❌ Proposing new systems without estimating build cost

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: suryast
• Source: suryast/free-ai-agent-skills
• License: MIT
• Homepage: https://skillpacks.dev

Install and usage instructions live in the source repository linked above.