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/pleaseai/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/pleaseai/claude-code-plugins/review)<a href="https://agentmods.dev/commands/pleaseai/claude-code-plugins/review"><img src="https://agentmods.dev/badge/commands/pleaseai/claude-code-plugins/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/pleaseai/claude-code-plugins/review"><img src="https://agentmods.dev/badge/commands/pleaseai/claude-code-plugins/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 | $0.00047 | $0.00733 |
| Opus 5.5 | $0.00019 | $0.00293 |
| Sonnet 5.5 | $0.00009 | $0.00147 |
| Haiku 4.5 | $0.00005 | $0.00073 |
Grade B, and why
review scanned grade B with 2 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 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.
Downloads and executes remote codemediumSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -fsSL https://cubic.dev/install | bash Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -fsSL https://cubic.dev/install | bash How it starts
The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cubic AI Code Review
Run an AI-powered code review using Cubic CLI and apply fixes.
Workflow
Step 1: Determine review scope
Analyze $ARGUMENTS to determine the review mode:
| User Intent | Command |
|---|---|
| Review uncommitted changes (default) | cubic review --json |
| Review branch diff against base | cubic review --base <branch> --json |
| Review specific commit | cubic review --commit <ref> --json |
| Review with custom focus | cubic review --prompt "<instructions>" --json |
If $ARGUMENTS is empty, default to reviewing uncommitted changes.
Step 1.5: Sanitize arguments
Before constructing any Bash command, validate that user-provided values (branch names, commit refs, prompt text) do not contain shell metacharacters (;, &&, ||, |, `, $(), ', newlines). Always use single quotes around user-provided values when interpolating into shell commands. Reject any input containing command separators, substitution patterns, or single quotes (which break single-quote escaping).
Step 2: Run Cubic review
Execute the appropriate command via Bash. Always include --json for structured output. Ensure all user-provided arguments are properly shell-quoted.
cubic review --json
If cubic is not installed, inform the user:
cubic CLI is not installed. Install it with:
curl -fsSL https://cubic.dev/install | bash
# or: npm install -g @cubic-dev-ai/cli
Step 3: Parse and analyze results
Parse the JSON output. Each issue contains:
priority: Severity level (P0 = critical, P1 = high, P2 = medium, P3 = low)file: File path where the issue was foundline: Line number of the issuetitle: Brief description of the issuedescription: Detailed explanation
Step 4: Present findings
Summarize the review results grouped by priority:
=== Cubic Review Results ===
Found N issues (X critical, Y high, Z medium, W low)
[P0] file:line - title
description
[P1] file:line - title
description
...
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 · 99 lines · 47 tokens per session scan B 82aa6ad8ab12
review is a command published in the GitHub repository pleaseai/claude-code-plugins (16 stars, last pushed 5d ago), licensed MIT. It adds 47 tokens to every session and 733 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it B with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
refactor
Systematic code refactoring with smart scope detection.
review-branch
Review the current branch's diff against base by dispatching atomic-reviewer. No orchestration loop, no spec required — pre-flight before /commit pr or /commit merge.
init
Install the formatters this repository needs, with every command visible before it runs.
merge-conflict-analysis
You are analyzing merge conflicts for PR #${{ pr-number }}.
boot
Start a new PromptKit prompt assembly session (alias for /bootstrap).
repo-audit
Audit a codebase (local or remote GitHub/GitLab) against architecture principles and requirements, surfacing drift, risk, and missing decisions.