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 skills add Kevin-Liu-01/Agent-Machines --skill issuegit clone --depth 1 https://github.com/Kevin-Liu-01/Agent-MachinesWrote 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/kevin-liu-01/agent-machines/issue)<a href="https://agentmods.dev/skills/kevin-liu-01/agent-machines/issue"><img src="https://agentmods.dev/badge/skills/kevin-liu-01/agent-machines/issue/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/skills/kevin-liu-01/agent-machines/issue"><img src="https://agentmods.dev/badge/skills/kevin-liu-01/agent-machines/issue.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00070 | $0.00819 |
| Opus 5.5 | $0.00028 | $0.00328 |
| Sonnet 5.5 | $0.00014 | $0.00164 |
| Haiku 4.5 | $0.00007 | $0.00082 |
Grade A, and why
issue 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 1mo 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context (auto-detected from HEAD)
- Current branch: !
git branch --show-current - Last commit: !
git log -1 --oneline - Remote: !
git remote get-url upstream 2>/dev/null || git remote get-url origin
Linear First
Dedalus tracks issues in Linear. The issue templates (.github/ISSUE_TEMPLATE/) all
require a Linear link at the top. Unless the user explicitly says "no Linear" or supplies
--linear N/A, ask once for the Linear URL before creating the GitHub issue. If the user
is filing a public-facing issue and has no Linear, accept N/A and proceed.
Template Selection
Parse the first positional arg from $ARGUMENTS as the issue type:
| Type | Template file | Labels |
|---|---|---|
| bug | .github/ISSUE_TEMPLATE/bug-report.yml |
bug,needs triage |
| feature | .github/ISSUE_TEMPLATE/feature_request.md |
enhancement |
| question | .github/ISSUE_TEMPLATE/question.md |
question |
The bug-report.yml file is a GitHub issue form. gh issue create --body submits plain
markdown, so translate the yaml form fields into a markdown body with the same section
headings (Linear Issue, Description, Steps to Reproduce, Expected Behavior, Component,
Environment, Additional Context).
For feature_request.md and question.md, read the file and replace the
[Delete and type here]. placeholders with real content. Drop the > [!IMPORTANT] and
> [!NOTE] callouts; they are instructions to the filer, not issue content.
Rules
- Issue title: short, imperative, no period, under 80 chars. No conventional-commit prefix (that's for PRs, not issues).
- The remaining positional args from
$ARGUMENTS(after the type) form the title. - If
--linear <url>is in$ARGUMENTS, use it verbatim. Otherwise ask the user once. - Use
gh issue create --title "..." --body "$(cat <<'EOF' ... EOF)" --label "...". - Labels come from the table above. Do not invent new labels.
- If the user mentions a specific component in the title or body, set the Component field accordingly (bug template only).
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.
- 1mo ago First seen · 65 lines · 70 tokens per session scan A 8b06b35f0893
issue is a skill published in the GitHub repository Kevin-Liu-01/Agent-Machines (30 stars, last pushed 3d ago), licensed MIT. It adds 70 tokens to every session and 819 once invoked, about $0.0003 per session on Opus 5.5. 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 skills, from other repositories
report-issue
File a bug or feature request against this repository (cyanheads/git-mcp-server) using the gh CLI. Use for tool logic bugs, git provider misbehavior, transport issues, auth/config problems, or new feature proposals.
gh-issues
Triage GitHub issues, select safe candidates, implement focused fixes, open pull requests, and address actionable review feedback.
github
Use GitHub CLI for repositories, issues, pull requests, reviews, CI runs, releases, and structured GitHub API queries.
oss-workflow
Open-source project success workflow for viznoir. Codifies contributor onboarding, release management (Release Please + PyPI), issue triage, and showcase curation. Triggers: release, contributor, onboarding, PyPI publish, issue triage, showcase, CHANGELOG, good first issue.
papi-build
Invoke when executing a build via buildexecute. Covers branching, gestalt pre-build check, and post-build audit.
papi-auto
Continue an approved PAPI cycle through implementation, verification and review using bounded autonomy. Resume durable work without rebuilding it; propose new scope before persisting it.