automation-audit-ops
Evidence-first automation inventory and overlap audit workflow for ECC.
Skill by JunMystery
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/junmystery-automation-audit-ops
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About
Use cases: security, productivity, agent-building
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What's inside
- Skill name
automation-audit-ops- Description
- Evidence-first automation inventory and overlap audit workflow for ECC. Use when the user wants to know which jobs, hooks, connectors, MCP servers, or wrappers are live, broken, redundant, or missing before fixing anything.
- License
- MIT
- Instructions
- 138 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Automation Audit Ops 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 ```text CURRENT SURFACE - automation - source - live state - proof FINDINGS - active breakage - overlap - stale status - missing capability RECOMMENDATION - keep - merge - cut - fix next
From JunMystery/Agent-Guidance-Python, MIT.
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Signals
- Stars
- 2
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Jun 11, 2026 (4 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
automation-audit-ops skill. Agent Mart. https://agentmart.dev/skills/junmystery-automation-audit-ops (last updated 2026-10-24)