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 pedrol-cmd/brain-drin --skill drin-code-base-recongit clone --depth 1 https://github.com/pedrol-cmd/brain-drinWrote 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/pedrol-cmd/brain-drin/drin-code-base-recon)<a href="https://agentmods.dev/skills/pedrol-cmd/brain-drin/drin-code-base-recon"><img src="https://agentmods.dev/badge/skills/pedrol-cmd/brain-drin/drin-code-base-recon/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/pedrol-cmd/brain-drin/drin-code-base-recon"><img src="https://agentmods.dev/badge/skills/pedrol-cmd/brain-drin/drin-code-base-recon.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 | $0.00185 |
| Opus 5.5 | $0.00009 | $0.00074 |
| Sonnet 5.5 | $0.00004 | $0.00037 |
| Haiku 4.5 | $0.00002 | $0.00018 |
Grade A, and why
drin-code-base-recon 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
Codebase Reconnaissance
Purpose
To rapidly build a mental model of an unknown system, identifying key structures and risks.
Phase 1: Landscape
ls -R: File distribution.package.json/requirements.txt: Tech stack and dependencies.README.md / CLAUDE.md: Intent and rules.
Phase 2: Core Paths
- Entry points (Main, Index, Server).
- Data models (Schema, Types).
- Primary business logic flows.
Phase 3: Infrastructure
- CI/CD pipelines.
- Deployment configs (Docker, Terraform).
- Monitoring and logging patterns.
Output
A RECON-REPORT.md summarizing the architecture, hot spots, and "WTF" areas.
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 · 29 lines · 22 tokens per session scan A 6d04cd069d88
drin-code-base-recon is a skill published in the GitHub repository pedrol-cmd/brain-drin (12 stars, last pushed 6mo ago), licensed MIT. It adds 22 tokens to every session and 185 once invoked, about $0.0001 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 2026-09-03.
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