Automation Audit Ops

SkillDev tools

This skill lets your AI inventory every automation you have in place and produce an evidence-based report on what is live, broken, redundant, or missing. You get a clear picture of your setup across jobs, hooks, connectors, and wrappers, so you know exactly what needs attention before making any fixes.

Available today. Use it from your connected AI after setup.

After adding the skill, ask your AI to audit your automations whenever you want a trustworthy picture of your setup before changing anything.

Then ask your AI: use the Automation Audit Ops skill

What your AI can do with it

  • Inventory all your automations, including jobs, hooks, connectors, and wrappers
  • Report which automations are live and working
  • Flag automations that are broken
  • Identify redundant setups that overlap
  • Point out automations that are missing
  • Back every finding with evidence so you fix the right things first

What this skill tells your AI

The instructions your AI receives, as published by affaan-m/ecc in skills/automation-audit-ops/SKILL.md and read by ahel’s review.

Use this when the user asks what automations are live, which jobs are broken, where overlap exists, or what tooling and connectors are actually doing useful work right now.

This is an audit-first operator skill. The job is to produce an evidence-backed inventory and a keep / merge / cut / fix-next recommendation set before rewriting anything.

Skill Stack

Pull these ECC-native skills into the workflow when relevant:

  • workspace-surface-audit for connector, MCP, hook, and app inventory
  • knowledge-ops when the audit needs to reconcile live repo truth with durable context
  • github-ops when the answer depends on CI, scheduled workflows, issues, or PR automation
  • ecc-tools-cost-audit when the real problem is webhook fanout, queued jobs, or billing burn in the sibling app repo
  • research-ops when local inventory must be compared against current platform support or public docs
  • verification-loop for proving post-fix state instead of relying on assumed recovery

When to Use

  • user asks "what automations do I have", "what is live", "what is broken", or "what overlaps"
  • the task spans cron jobs, GitHub Actions, local hooks, MCP servers, connectors, wrappers, or app integrations
  • the user wants to know what was ported from another agent system and what still needs to be rebuilt inside ECC
  • the workspace has accumulated multiple ways to do the same thing and the user wants one canonical lane

Guardrails

  • start read-only unless the user explicitly asked for fixes
  • separate:
    • configured
    • authenticated
    • recently verified
    • stale or broken
    • missing entirely
  • do not claim a tool is live just because a skill or config references it
  • do not merge or delete overlapping surfaces until the evidence table exists

Workflow

1. Inventory the real surface

Read the current live surface before theorizing:

  • repo hooks and local hook scripts
  • GitHub Actions and scheduled workflows
  • MCP configs and enabled servers
  • connector- or app-backed integrations
  • wrapper scripts and repo-specific automation entrypoints

Group them by surface:

  • local runtime
  • repo CI / automation
  • connected external systems
  • messaging / notifications
  • billing / customer operations
  • research / monitoring

2. Classify each item by live state

For every surfaced automation, mark:

  • configured
  • authenticated
  • recently verified
  • stale or broken
  • missing

Then classify the problem type:

  • active breakage
  • auth outage
  • stale status
  • overlap or redundancy
  • missing capability

3. Trace the proof path

Back every important claim with a concrete source:

  • file path
  • workflow run
  • hook log
  • config entry
  • recent command output
  • exact failure signature

If the current state is ambiguous, say so directly instead of pretending the audit is complete.

4. End with keep / merge / cut / fix-next

For each overlapping or suspect surface, return one call:

  • keep
  • merge
  • cut
  • fix next

The value is in collapsing noisy automation into one canonical ECC lane, not in preserving every historical path.

Output Format

CURRENT SURFACE
- automation
- source
- live state
- proof

FINDINGS
- active breakage
- overlap
- stale status
- missing capability

RECOMMENDATION
- keep
- merge
- cut
- fix next

NEXT ECC MOVE
- exact skill / hook / workflow / app lane to strengthen

Pitfalls

  • do not answer from memory when the live inventory can be read
  • do not treat "present in config" as "working"
  • do not fix lower-value redundancy before naming the broken high-signal path
  • do not widen the task into a repo rewrite if the user asked for inventory first

Verification

  • important claims cite a live proof path
  • each surfaced automation is labeled with a clear live-state category
  • the final recommendation distinguishes keep / merge / cut / fix-next

Signals

GitHub stars
256k
Forks
38k
Last commit
Sep 2026

Others that do the same job

Advanced
Catalog kind
skill
Gateway key
automation-audit-ops
Source
github.com/affaan-m/ecc