Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/junmystery/agent-guidance-python/automation-audit-opsnpx skills add JunMystery/Agent-Guidance-Python --skill automation-audit-opsgit clone --depth 1 https://github.com/JunMystery/Agent-Guidance-PythonWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/junmystery/agent-guidance-python/automation-audit-ops)<a href="https://agentmods.dev/skills/junmystery/agent-guidance-python/automation-audit-ops"><img src="https://agentmods.dev/badge/skills/junmystery/agent-guidance-python/automation-audit-ops.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00049 | $0.00916 |
| Opus 5 | $0.00024 | $0.00458 |
| Sonnet 5 | $0.00010 | $0.00183 |
| Haiku 4.5 | $0.00005 | $0.00092 |
Grade A, and why
automation-audit-ops scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
88% identical to automation-audit-ops — 27 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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-auditfor connector, MCP, hook, and app inventoryknowledge-opswhen the audit needs to reconcile live repo truth with durable contextgithub-opswhen the answer depends on CI, scheduled workflows, issues, or PR automationecc-tools-cost-auditwhen the real problem is webhook fanout, queued jobs, or billing burn in the sibling app reporesearch-opswhen local inventory must be compared against current platform support or public docsverification-loopfor 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
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 143 lines · 49 tokens per session scan A cb4f49604a9d
automation-audit-ops is a skill published in the GitHub repository JunMystery/Agent-Guidance-Python (2 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 916 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to automation-audit-ops, differing in 27 lines, and is treated as a copy.
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