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 Snowflake-Labs/cocoplus --skill cocoreviewgit clone --depth 1 https://github.com/Snowflake-Labs/cocoplusWrote 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/snowflake-labs/cocoplus/cocoreview)<a href="https://agentmods.dev/skills/snowflake-labs/cocoplus/cocoreview"><img src="https://agentmods.dev/badge/skills/snowflake-labs/cocoplus/cocoreview.svg" alt="Measured on agentmods" 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 | $0.00057 | $0.04924 |
| Opus 5 | $0.00028 | $0.02462 |
| Sonnet 5 | $0.00011 | $0.00985 |
| Haiku 4.5 | $0.00006 | $0.00492 |
Grade A, and why
cocoreview 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 4d 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 — 366 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Objective
You are executing CocoReview — a structured, evidence-grounded code review. Your task is to produce an actionable prioritized finding report using the six-severity vocabulary and the four-phase review process.
Before proceeding, verify that .cocoplus/ exists. If not, output: "CocoPlus is not initialized. Run $pod init first." Then stop.
Routing Table
| Invocation | Loads |
|---|---|
$review <file> |
universal-quality.md + language guide inferred from file extension |
$review --security |
universal-quality.md + language guide + security-review.md |
$review --architecture |
universal-quality.md + architecture-review.md |
$review --complexity |
Run cocoreview/pr-complexity only — no LLM review |
$review --language <lang> |
universal-quality.md + explicit language guide |
| `$review export markdown | html |
Step 1 — Parse Invocation and Run Complexity Analyzer
Parse the $review command for file path and flags. If no file path provided for non-complexity commands, ask: "Which file or directory should I review?"
Always run cocoreview/pr-complexity first (before any LLM work):
invoke cocoreview/pr-complexity --file <path>
Read the output JSON. If size_bucket is XL (≥800 lines of change), surface a split recommendation:
⚠ CocoReview: This artifact is in the XL complexity bucket (<N> lines changed, complexity score <score>).
XL changes are significantly harder to review effectively. Consider splitting into:
- Schema/model changes (separate PR)
- Logic/transformation changes (separate PR)
- Test additions (can merge with logic changes)
Proceed with full review anyway? [YES/SPLIT]
If --complexity flag: display complexity output and stop (no LLM review).
Step 2 — Load Reference Guides
Based on routing table above, load the appropriate guides from .cortex/skills/cocoreview/. Always load universal-quality.md. Load others based on flags and risk_flags from complexity analyzer output (e.g., if security-sensitive in risk_flags, load security-review.md).
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.
- 4d ago First seen · 366 lines · 57 tokens per session scan A b48e15950443
cocoreview is a skill published in the GitHub repository Snowflake-Labs/cocoplus (720 stars, last pushed 5d ago), licensed MIT. It adds 57 tokens to every session and 4,924 once invoked, about $0.0003 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.
Other skills, from other repositories
code-review
Review code for quality, bugs, and best practices. Use when asked to review or audit code.
audit
(forwward) Aggressively audits and cleans a codebase — removes slop, dead code, and AI-generated noise; fixes DRY/SOLID violations; restructures toward the simplest correct implementation. One commit, no behavior changes. Use when the user says "audit the code", "clean up tech debt", "remove dead code", "deslop"…
review-loop
Run the adversarial verification loop — implement, then hand the change to a fresh checker that did not write it, fix what it finds, and re-dispatch until APPROVE. Use before claiming any behavioural change is done, and on requests like "review loop", "adversarial review", "independent review", "get this verified"…
understand-pr
Guided interactive PR review — understand the history and context before forming opinions.
performance-review
Performance-focused code review for identifying bottlenecks and optimization opportunities.
code-review
Performs structured code review on a file or directory.