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 agentmods add skills/drvoss/everything-copilot-cli/reviewnpx skills add drvoss/everything-copilot-cli --skill reviewgit clone --depth 1 https://github.com/drvoss/everything-copilot-cliWhat 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 | $0.00041 | $0.01291 |
| Opus 5 | $0.00020 | $0.00646 |
| Sonnet 5 | $0.00008 | $0.00258 |
| Haiku 4.5 | $0.00004 | $0.00129 |
Grade A, and why
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 2d 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 — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review
Review compares the diff between HEAD and a pinned git reference along two deliberately separate
axes:
- Standards - does the change follow this repository's documented conventions?
- Spec - does the change match the originating issue, PRD, or spec?
Run the two axes in separate agent sessions in parallel, then report them side by side. Keeping them independent prevents coding-standard findings from hiding scope or requirement mismatches, and vice versa.
When to Use
- The user asks to "review since X", review a branch, or compare work against a commit, branch, tag,
or
HEAD~N - You need to verify both repository conventions and requirement alignment, not just general code quality
- A branch looks plausible, but you need to separate "implemented correctly" from "implemented as requested"
- You want a review artifact that distinguishes standards violations from spec drift
When NOT to Use
| Instead of review | Use |
|---|---|
| You only need a general quality or correctness pass | code-review |
| You want a broad 6-lens PR review across PM, QA, Security, DevOps, and UX | pr-multi-perspective-review |
| The task is to verify a delegated implementation against a handoff or task file item-by-item after it landed | implementation-review |
Workflow
1. Pin the reference first
Do not review against a fuzzy baseline. Use exactly what the user supplied: a commit SHA, branch,
tag, main, HEAD~5, or another explicit git reference.
If the user did not specify one, stop and ask what to compare against.
Use one stable comparison for both axes:
git --no-pager diff <reference>...HEAD
git --no-pager log <reference>..HEAD --oneline
Use the same diff and commit list for both review axes so the findings stay comparable.
2. Find the spec source
Look for the originating spec in this order:
- Issue or ticket references in commit messages
- A path the user provided directly
- A matching doc under
docs/,specs/, or.scratch/
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.
- 2d ago First seen · 155 lines · 41 tokens per session scan A 196f0b261ab5
review is a skill published in the GitHub repository drvoss/everything-copilot-cli (45 stars, last pushed 5d ago), licensed MIT. It adds 41 tokens to every session and 1,291 once invoked, about $0.0002 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 2026-08-30.
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