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 brazil-bench/pourpoise --skill codebase-summarygit clone --depth 1 https://github.com/brazil-bench/pourpoiseWrote 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/brazil-bench/pourpoise/codebase-summary)<a href="https://agentmods.dev/skills/brazil-bench/pourpoise/codebase-summary"><img src="https://agentmods.dev/badge/skills/brazil-bench/pourpoise/codebase-summary/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/skills/brazil-bench/pourpoise/codebase-summary"><img src="https://agentmods.dev/badge/skills/brazil-bench/pourpoise/codebase-summary.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 | $0.00082 | $0.02926 |
| Opus 5.5 | $0.00033 | $0.01170 |
| Sonnet 5.5 | $0.00016 | $0.00585 |
| Haiku 4.5 | $0.00008 | $0.00293 |
Grade A, and why
codebase-summary 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 2mo 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 — 314 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codebase Summary
Overview
This sop analyzes a codebase and generates comprehensive documentation including structured metadata files that describe the system architecture, components, interfaces, and workflows. It can create targeted documentation files like AGENTS.md (README for AI agents), README.md, CONTRIBUTING.md, or generate a complete documentation ecosystem. The documentation is organized to make it easy for AI assistants to understand the system and help with development tasks.
Parameters
- output_dir (optional, default: ".sop/summary"): Directory where documentation will be stored
- consolidate (optional, default: false): Whether to create a consolidated documentation file
- consolidate_target (optional, default: "AGENTS.md"): Target file for consolidation (e.g., "README.md", "CONTRIBUTING.md", or custom filename). Only used if consolidate is true
- consolidate_prompt (optional): Description of how to structure the consolidated content for the target file type (e.g., Reference the AGENTS.md example below for the default "consolidate_prompt"). Only used if consolidate is true
- check_consistency (optional, default: true): Whether to check for inconsistencies across documents
- check_completeness (optional, default: true): Whether to identify areas lacking sufficient detail
- update_mode (optional, default: false): Whether to update existing documentation based on recent changes
- codebase_path (optional, default: current directory): Path to the codebase to analyze
Constraints for parameter acquisition:
- You MUST ask for all parameters upfront in a single prompt rather than one at a time
- You MUST support multiple input methods including:
- Direct input: Text provided directly in the conversation
- File path: Path to a local file containing codebase information
- Directory path: Path to the codebase to analyze
- Other methods: You SHOULD be open to other ways the user might want to specify the codebase
- You MUST use appropriate tools to access content based on the input method
- You MUST confirm successful acquisition of all parameters before proceeding
- You MUST validate that the codebase_path exists and is accessible
- If consolidate is false, you MUST inform the user that consolidate_target and consolidate_prompt will be ignored
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.
- 2mo ago First seen · 314 lines · 82 tokens per session scan A a928f2d2a964
codebase-summary is a skill published in the GitHub repository brazil-bench/pourpoise (11 stars, last pushed 9mo ago), licensed Apache-2.0. It adds 82 tokens to every session and 2,926 once invoked, about $0.0003 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.
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