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/petar-djukic/writing-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/petar-djukic/writing-skills/cold-review)<a href="https://agentmods.dev/commands/petar-djukic/writing-skills/cold-review"><img src="https://agentmods.dev/badge/commands/petar-djukic/writing-skills/cold-review/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/petar-djukic/writing-skills/cold-review"><img src="https://agentmods.dev/badge/commands/petar-djukic/writing-skills/cold-review.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 | $0.00001 | $0.00062 |
| Opus 5.5 | $0.00000 | $0.00025 |
| Sonnet 5.5 | $0.00000 | $0.00012 |
| Haiku 4.5 | $0.00000 | $0.00006 |
Grade A, and why
cold-review 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 11d 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
Apply the cold-review skill. Read .github/skills/cold-review/SKILL.md and follow
its workflow, using the reference and asset files under
.github/skills/cold-review/. Treat any text after the prompt invocation as
the skill's input.
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.
- 11d ago First seen · 9 lines · 1 tokens per session scan A 25e6d38bb3b9
cold-review is a command published in the GitHub repository petar-djukic/writing-skills (5 stars, last pushed 7d ago), licensed MIT. It adds 1 tokens to every session and 62 once invoked, about $0.0000 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 2026-10-05.
Other commands, from other repositories
story-long-scan
A command for scanning long-form online fiction rankings on platforms such as Qidian, Fanqie, and Jinjiang, then analyzing the ranking data.
story-short-scan
A tool for scanning and analysing popular short web-fiction rankings on platforms such as Zhihu Yanyan and Fanqie Short Stories.
genshijin-review
A compact Japanese-language code-review command that reports one finding per line with a severity label and suggested fix.
review-open-prs
Command "review-open-prs" from The-Artificer-of-Ciphers-LLC/skills-from-the-artificer, covering batch pr review directive — all open prs i did not author, phase a — enumerate target prs & build the queue, phase b — per-pr directive (runs once per queued $pr), 0. context anchoring and 1. preconditions.
review
Recent git commits: !git log --oneline -10.
resolve-review
Resolve reviewer feedback - from GitHub PRs, chat, or any reviewer.