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.
git clone --depth 1 https://github.com/vinnie357/claude-skillsWrote 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/commands/vinnie357/claude-skills/audit-epics)<a href="https://agentmods.dev/commands/vinnie357/claude-skills/audit-epics"><img src="https://agentmods.dev/badge/commands/vinnie357/claude-skills/audit-epics/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/vinnie357/claude-skills/audit-epics"><img src="https://agentmods.dev/badge/commands/vinnie357/claude-skills/audit-epics.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00014 | $0.00692 |
| Opus 5 | $0.00007 | $0.00346 |
| Sonnet 5 | $0.00003 | $0.00138 |
| Haiku 4.5 | $0.00001 | $0.00069 |
Grade A, and why
audit-epics 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audit existing Linear epics for VantageEx compatibility.
Steps
- Load the
/linearskill - Read the audit checklist at
references/audit-checklist.md - Read the audit report template at
templates/0.1.0/audit-report.md
Fetch Issues
Determine scope from arguments:
--issue=<key>: Audit a single issue by key (e.g., MT-123)--project=<slug>: Audit all issues in a project--state=<state>: Filter by Linear state type (e.g., "started", "unstarted", "completed")- No arguments: Ask the user which project or issues to audit
Use Linear MCP tools (preferred) or GraphQL to fetch issues with their full descriptions, states, labels, and attachments.
Run Checks
For each issue, run every check from the audit checklist:
Structure Checks
- Parse description for
## Objective,## Skills,## Repossections - Validate objective quality (2-3 sentences)
- Validate skills exist in marketplace (read marketplace.json)
- Check for core skills that should not be listed
Team Checks
- Check for
## Teamsection - Check for escalation policy
Naming Checks
- Evaluate title quality (imperative statement)
- Check slug derivability
- Check branch naming convention if branch exists
State Consistency Checks
- For completed/review issues: check for
## PRsection or GitHub PR attachment - For needs_help issues: check for blocker documentation
- Use
gh pr listandgh pr viewto cross-reference PR URLs
Epic-Sizing Checks
See references/epic-sizing.md for thresholds.
- Flag epics with > 8 issues — signal to split the epic
- Flag issues with > ~10 target files — exceeds one worker session
- Flag multi-deliverable issue titles (joined by "and", "also", "then", "plus") — split them
- Flag acceptance criteria that cannot be verified in a single worker session
- Flag issues with cross-subsystem or cross-repo scope — split candidates
Dependency-Ordering Checks
See references/epic-sizing.md for conventions.
- Flag issues with implicit or missing dependency declarations (no blocking relations / bees deps)
- Flag dependency cycles — halt: re-decompose required before queueing
- Flag dependency chains deeper than 5 levels — serializes workers unnecessarily
- Flag independent issues that are serialized without cause — reduces worker fan-out
- Flag a DAG source issue that is itself marked
blockedByanother issue — inconsistent foundational ordering
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.
- 6d ago First seen · 81 lines · 14 tokens per session scan A 370d641b9ae4
audit-epics is a command published in the GitHub repository vinnie357/claude-skills (25 stars, last pushed 3d ago), licensed MIT. It adds 14 tokens to every session and 692 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other commands, from other repositories
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sync-linear
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add-note
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dispatcher
Pick the next-best repo to work on across the portfolio — rank free repos, recommend one, claim its lease atomically, and route to the entry command.
workpm
A project-management workflow for coordinating multiple AI workers through five stages. It includes task assignment, shared activity logs, worker replacement, and final checks.