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 zjshen14/opencli --skill lintgit clone --depth 1 https://github.com/zjshen14/opencliWrote 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/zjshen14/opencli/lint)<a href="https://agentmods.dev/skills/zjshen14/opencli/lint"><img src="https://agentmods.dev/badge/skills/zjshen14/opencli/lint/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/zjshen14/opencli/lint"><img src="https://agentmods.dev/badge/skills/zjshen14/opencli/lint.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 | $0.00029 | $0.00292 |
| Opus 5.5 | $0.00012 | $0.00117 |
| Sonnet 5.5 | $0.00006 | $0.00058 |
| Haiku 4.5 | $0.00003 | $0.00029 |
Grade A, and why
lint 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.
What it actually says
Lint this project.
Lint script detection: !{cat package.json 2>/dev/null | python3 -c "import sys,json; s=json.load(sys.stdin).get('scripts',{}); print('\n'.join(f'{k}: {v}' for k,v in s.items() if 'lint' in k or 'format' in k))" 2>/dev/null || echo "(no package.json lint script found)"}
Task: $ARGUMENTS
Steps:
- Detect the linter from the project manifest:
- Node.js:
npm run lint/npm run lint:fix - Python:
ruff check ./ruff check --fix . - Go:
golangci-lint run - Other: check Makefile or CI config
- Node.js:
- If the user asked to fix: run with the auto-fix flag first, then report what remains
- If the user just wants a report: run without fixing
- Output format: file path, line, rule name, message — grouped by file
- Report: N issues auto-fixed, M require manual attention
Do not modify files without explicit instruction to fix.
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 · 28 lines · 29 tokens per session scan A bfe0494a188f
lint is a skill published in the GitHub repository zjshen14/opencli (2 stars, last pushed 1mo ago), licensed MIT. It adds 29 tokens to every session and 292 once invoked, about $0.0001 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 2026-08-31.
Other skills, from other repositories
requesting-code-review
Pre-commit review: security scan, quality gates, auto-fix.
github-code-review
Review PRs: diffs, inline comments via gh or REST.
github-pr-workflow
GitHub PR lifecycle: branch, commit, open, CI, merge.
01-sdlc
Orchestrates a request from framing to a draft pull request, autonomous or supervised, isolating implementation, independent review, and final outcome challenge. Use when the user wants to deliver a change end to end. Not for one step.
doubt-driven-review
In-flight adversarial check on a non-trivial decision BEFORE it stands — distinct from post-hoc review of a finished diff. Use on "stress-test this decision", "are we sure about this", "verify before commit", "poke holes in this", when working in unfamiliar code, or before an irreversible step (migration, prod deploy…
05-review
Reviews a change or a diff and says whether it is ready to ship, naming every problem with its fix. Use when the user wants a change checked before it ships. Not for fixing what the review finds, and not for auditing a whole codebase.