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 pproenca/dot-skills --skill cli-review-runnergit clone --depth 1 https://github.com/pproenca/dot-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/skills/pproenca/dot-skills/cli-review-runner)<a href="https://agentmods.dev/skills/pproenca/dot-skills/cli-review-runner"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/cli-review-runner/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/pproenca/dot-skills/cli-review-runner"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/cli-review-runner.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 | $0.00121 | $0.01944 |
| Opus 5 | $0.00060 | $0.00972 |
| Sonnet 5 | $0.00024 | $0.00389 |
| Haiku 4.5 | $0.00012 | $0.00194 |
Grade A, and why
cli-review-runner 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.
How it starts
The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
cli-review-runner
Automates the 10-item agent-friendliness audit from cli-for-agents. Runs black-box probes against a target CLI and emits a structured report mapping each finding to a rule ID (e.g., help-examples-in-help, err-non-zero-exit-codes, safe-dry-run-flag). Default mode is read-only - probes never run destructive verbs with real arguments.
When to Apply
- User asks to review or audit a CLI for agent-friendliness, automation readiness, or CI use
- User has just finished building a CLI and wants a pre-ship sanity check
- User is grading their own or a third-party CLI against the cli-for-agents catalog
- User is asking why a CLI is hanging an agent, blowing up context, or failing to compose in a pipeline
- PR review for a CLI change - quickly regress-test the
--help, errors, and dry-run flags
How to Use
The skill is orchestrated by scripts/review.sh. Point it at the target CLI (absolute path or PATH-resolvable name) and pick an output format.
# Default: text table on stdout, exit 0 if all passed, 1 if any failed
bash scripts/review.sh --target /usr/local/bin/mycli
# Machine-readable output
bash scripts/review.sh --target gh --format json
bash scripts/review.sh --target kubectl --format ndjson
# Supply subcommand list when auto-discovery misses them
bash scripts/review.sh --target gh --subcommands pr,issue,repo
# Preview what would run without touching the target CLI
bash scripts/review.sh --target mycli --dry-run
# Include risky probes on destructive verbs (off by default)
bash scripts/review.sh --target mycli --include-destructive
See bash scripts/review.sh --help for the full flag list.
Workflow Overview
--target <cli>
│
▼
[1] Validate target fail fast if path missing or not executable
│
▼
[2] Load rule catalog references/rule-catalog.tsv (45 rules)
│
▼
[3] Discover subcommands parse top-level --help (gh/kubectl/commander shapes)
│
▼
[4] Run probes P1..P10 each probe emits NDJSON findings to a temp file
│
▼
[5] Render report scripts/render.sh -> text | json | ndjson
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- config.json 1.0 KB
- gotchas.md 2.7 KB
- metadata.json 1.3 KB
- references/rule-catalog.tsv 4.5 KB
- references/workflow.md 9.2 KB
- scripts/lib/common.sh 8.8 KB runs code
- scripts/lib/probes.sh 29 KB runs code
- scripts/render.sh 8.9 KB runs code
- scripts/review.sh 11 KB runs code
- scripts/selftest.sh 4.7 KB runs code
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 · 131 lines · 121 tokens per session scan A 0718633f5ee7
cli-review-runner is a skill published in the GitHub repository pproenca/dot-skills (205 stars, last pushed 24d ago), licensed MIT. It adds 121 tokens to every session and 1,944 once invoked, about $0.0006 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.
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