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/ccplugins/awesome-claude-code-pluginsWrote 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/ccplugins/awesome-claude-code-plugins/demo)<a href="https://agentmods.dev/commands/ccplugins/awesome-claude-code-plugins/demo"><img src="https://agentmods.dev/badge/commands/ccplugins/awesome-claude-code-plugins/demo/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/ccplugins/awesome-claude-code-plugins/demo"><img src="https://agentmods.dev/badge/commands/ccplugins/awesome-claude-code-plugins/demo.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 | $0.00022 | $0.01019 |
| Opus 5.5 | $0.00009 | $0.00408 |
| Sonnet 5.5 | $0.00004 | $0.00204 |
| Haiku 4.5 | $0.00002 | $0.00102 |
Grade C, and why
demo scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
8. **Clean up.** Remove the throwaway directory (`rm -rf "$DEMO"` — it is a Copies of this mod
1 near-identical copy found in the catalogue:
- demo — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are running the ClauDex demo — a safe, self-contained first experience of the duet. You will plant bugs, let both models review them independently, and reveal who caught what. Everything happens in a throwaway directory; the user's own files are never touched.
Sign-off contract: this is a real review, so the normal rules apply — end
with reviewed with love by ClauDex 🧡🖤 ONLY if Codex successfully delivered
its review; if the Codex call fails (after one retry), end unsigned with the
interruption message.
Preflight — it takes two to ClauDex
Run codex --version and check auth (codex login status or equivalent).
If either fails, STOP and reply with exactly:
It takes two to ClauDex. 🧡 Claude is here — 🖤 Codex is not, so there is no duet to demo. Fix it in two lines, then come back:
npm i -g @openai/codex codex login
(No git preflight — the demo brings its own repo.)
The demo
-
Set the stage. Create a throwaway workspace and repo:
DEMO=$(mktemp -d "${TMPDIR:-/tmp}/claudex-demo.XXXXXX") && git -C "$DEMO" init -q -
Plant the bugs. Write exactly this to
$DEMO/discount.js:// discount.js — apply coupon discounts to a shopping cart function applyDiscount(cart, coupon) { let total = 0; for (let i = 0; i <= cart.length; i++) { total += cart[i].price * cart[i].qty; } if (coupon.type == "percent") { total = total - (total * coupon.value) / 100; } else { total = total - coupon.value; } cart.forEach((item) => (item.discounted = true)); return "$" + total.toFixed(2); } module.exports = { applyDiscount };For your own reveal later, the planted issues are: (a) off-by-one
i <= cart.length— guaranteed crash; (b) no validation ofcoupon.value— negative totals, >100% discounts; (c) loose==comparison; (d) the function silently mutates the caller's cart; (e) floating-point money math. Do NOT tell either reviewer this list. -
Tell the user what's happening in two sentences: bugs are planted — some obvious, some subtle, one a pure judgment call — and the two models will now review the same file independently.
-
Claude's review (yours). Review
discount.jsand write down your findings BEFORE consulting Codex. -
Codex's review. With a hard timeout of ~10 minutes:
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.
- 1mo ago First seen · 93 lines · 22 tokens per session scan C 3a04bf1c1930
demo is a command published in the GitHub repository ccplugins/awesome-claude-code-plugins (977 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 22 tokens to every session and 1,019 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other commands, from other repositories
pr-issue-resolve
Follow these steps to analyze suggested changes (e.g., review comments, inline suggestions, or requested modifications) in a GitHub Pull Request (PR) and resolve them efficiently. The goal is to review, understand, plan fixes, apply changes, test, and update the PR while maintaining code quality and collaboration.
husky
Sets up and manages Husky Git hooks by configuring pre-commit hooks, establishing commit message standards, integrating with linting tools, and ensuring code quality on commits.
pr-review
Reviews pull request changes to provide feedback, check for issues, and suggest improvements before merging into the main codebase.
refractor
Refactor code following best practices and design patterns.
fix-pr
Fetches and fixes unresolved PR comments by automatically retrieving feedback, addressing reviewer concerns, making targeted code improvements, and streamlining the review process.
review-pr
Comprehensive PR review using specialized agents.