Borrowing it
Nothing to install: this file belongs to cmdaltctr/claude-gemini-mcp-slim. 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/cmdaltctr/claude-gemini-mcp-slim/main/.claude/commands/a.mdgit clone --depth 1 https://github.com/cmdaltctr/claude-gemini-mcp-slimWrote 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/cmdaltctr/claude-gemini-mcp-slim/a)<a href="https://agentmods.dev/commands/cmdaltctr/claude-gemini-mcp-slim/a"><img src="https://agentmods.dev/badge/commands/cmdaltctr/claude-gemini-mcp-slim/a/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/cmdaltctr/claude-gemini-mcp-slim/a"><img src="https://agentmods.dev/badge/commands/cmdaltctr/claude-gemini-mcp-slim/a.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 | $0.00006 | $0.00111 |
| Opus 5.5 | $0.00002 | $0.00044 |
| Sonnet 5.5 | $0.00001 | $0.00022 |
| Haiku 4.5 | $0.00001 | $0.00011 |
Grade A, and why
a 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 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.
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.
What it actually says
Quick Code Analysis
Fast code analysis with Gemini's insights.
Usage: /a [file_path] [analysis_type:optional]
Examples:
/a auth.py/a UserForm.vue security
Analyzing: $ARGUMENTS
!mcp__gemini-mcp__gemini_analyze_code code_content="@$1" analysis_type="$2"
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 · 19 lines · 6 tokens per session scan A 3a808807ec1a
a is a command published in the GitHub repository cmdaltctr/claude-gemini-mcp-slim (231 stars, last pushed 11mo ago), licensed MIT. It adds 6 tokens to every session and 111 once invoked, about $0.0000 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 2026-08-30.
Other commands, from other repositories
ai-hygiene-audit
Audit codebase for AI-generated code quality issues (vibe coding, Tab bloat, slop).
deep-audit.skeleton
Description: This section is populated by Bootstrap with manifest data. Required manifest fields: project.description, stack.primary, project.structure, project.subprojects, stack.orm, stack.authmethod Example output.
harness:audit
Cross-dimensional codebase audit orchestrator — classify repo shape, fan out parallel read-only audit agents, dedup and severity-rank findings against existing issues, publish grouped tracking issues.
modify
Command "modify" from MartyBonacci/specswarm, covering user input, flag parsing, parse flags from arguments, mode routing and goal.
prism-graph
Export Prism's graph of this repository and summarise it.
review
Review code across five axes with categorized findings.