Borrowing it
Nothing to install: this file belongs to Felipe-SO/coarse-ink-claude-code. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Felipe-SO/coarse-ink-claude-code/main/.claude/skills/coarse-review/SKILL.mdgit clone --depth 1 https://github.com/Felipe-SO/coarse-ink-claude-codeWrote 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/felipe-so/coarse-ink-claude-code/coarse-review)<a href="https://agentmods.dev/skills/felipe-so/coarse-ink-claude-code/coarse-review"><img src="https://agentmods.dev/badge/skills/felipe-so/coarse-ink-claude-code/coarse-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/skills/felipe-so/coarse-ink-claude-code/coarse-review"><img src="https://agentmods.dev/badge/skills/felipe-so/coarse-ink-claude-code/coarse-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 | $0.00034 | $0.00604 |
| Opus 5.5 | $0.00014 | $0.00242 |
| Sonnet 5.5 | $0.00007 | $0.00121 |
| Haiku 4.5 | $0.00003 | $0.00060 |
Grade A, and why
coarse-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/coarse-review — Full Review Pipeline
Usage: /coarse-review papers/paper.pdf
Runs the complete Coarse review pipeline by invoking each sub-skill in sequence.
All paths are relative to the workspace root d:/Dropbox/Research/Coarse Reviewer/.
The argument ($ARGUMENTS) is the path to the paper PDF.
Derive the slug from the filename: lowercase, spaces→hyphens, no extension.
e.g. papers/my-paper.pdf → slug = my-paper
Pass the PDF path only to coarse-extract. Pass the slug to all subsequent
sub-skills — they work entirely from cache files and never need the PDF again.
Pipeline
Run each sub-skill in order. Wait for each to complete before starting the next. If a sub-skill fails, stop and report the error — do not skip ahead.
| Step | Sub-skill | What it does | Output |
|---|---|---|---|
| 1–2 | /coarse-extract $ARGUMENTS |
PDF → markdown, parse sections | _extracted.md, _sections.json |
| 3–6 | /coarse-classify <slug> |
Classify, calibrate, contributions, literature | _classification.json, _calibration.json, _contribution.json, _literature.txt |
| 7–8 | /coarse-overview <slug> |
Macro overview + assumption check + completeness | _overview.json |
| 9–11 | /coarse-section-review <slug> |
Per-section review + adversarial proof verify + cross-section + compile | _comments_draft.json |
| 12–13 | /coarse-editorial <slug> |
Editorial filter + quote verify (Python) | _comments_verified.json |
| 14 | /coarse-write <slug> |
Write final review markdown | reviews/<slug>-review.md |
Cache location
All intermediate files are written to .coarse_cache/<slug>_*.json and
.coarse_cache/<slug>_extracted.md. If a run is interrupted, you can resume
from any sub-skill without re-running earlier steps — the cache files persist.
Notes
- Each sub-skill re-reads its dependencies from cache at startup, so context compression between steps is safe.
- To re-run only part of the pipeline (e.g. redo the editorial filter after adjusting a comment), invoke the relevant sub-skill directly.
- See
reference_review.mdfor the gold-standard output format.
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.
- 2mo ago First seen · 56 lines · 34 tokens per session scan A 6e83df7a5de5
coarse-review is a skill published in the GitHub repository Felipe-SO/coarse-ink-claude-code (2 stars, last pushed 6mo ago), licensed MIT. It adds 34 tokens to every session and 604 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.
coarse-review compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| coarse-reviewFelipe-SO/coarse-ink-claude-code | Skill | 2 | 6mo ago | MIT | A | 34 | Claude Code |
| apify-youtube-transcript-scrapersickn33/agentic-awesome-skills | Skill | 49k | yesterday | MIT | A | 48 | Claude Code |
| foundry-hosted-agent-validationmicrosoft/agent-framework | Skill | 15k | yesterday | MIT | A | 82 | Claude Code, Codex |
| skill-doc-deliverynyldn/claude-octopus | Skill | 4.4k | yesterday | MIT | A | 29 | Claude Code |
| meta-web-to-pdf-briefingopensquilla/opensquilla | Skill | 7.1k | 6d ago | Apache-2.0 | A | 45 | Claude Code, Codex |
| paper-readerhuangkiki/dailypaper-skills | Skill | 1.3k | 4d ago | Apache-2.0 | A | 135 | Claude Code, Codex |
| chat-complex-documentsvellum-ai/vellum-assistant | Skill | 1.5k | 2d ago | MIT | A | 90 | Claude Code, Codex |