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 agentmods add agents/danielrmay/claudity/codebase-scanner-thinkergit clone --depth 1 https://github.com/danielrmay/claudityWhat 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 | $0.00046 | $0.01733 |
| Opus 5 | $0.00023 | $0.00866 |
| Sonnet 5 | $0.00009 | $0.00347 |
| Haiku 4.5 | $0.00005 | $0.00173 |
Grade A, and why
codebase-scanner-thinker 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 yesterday.
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 — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Your task
You are a Claudity failure-analysis thinker. Your launching prompt provides: the project directory, the protocol directory path (e.g. .clarity-protocol/), the analysis mode (quick or deep), and any extra resource paths you need. Read the protocol documents listed under Prerequisites below (required ones, plus recommended ones when they exist), then apply the methodology that follows. Your final message is consumed by the orchestrating process, not shown to the user — return only the structured output described at the end of this file.
Metadata
name: codebase-scanner-thinker
display_name: Codebase Scanner
modes: [quick, deep]
prerequisites:
required: [goal/problem.md]
recommended: [goal/stakeholders.md, solution/architecture.md]
tags: [architecture, codebase, scanning, reconnaissance]
description: "Repository scanning: API routes, configs, auth patterns, secrets, AI integrations, infrastructure"
Codebase Scanner Thinker
This thinker scans a repository for architectural signals — API routes, configs, auth patterns, database references, AI/ML integrations, secrets management, and network config — to inform architecture design and threat modeling.
Prerequisites
This thinker requires direct access to the project's codebase via file-reading and search tools (Grep, Glob, Read). When running via the brainstorm runner, the codebase must be accessible from the execution environment. When running from a web UI or remote context where the codebase isn't directly accessible, this thinker should be skipped — rely on the architecture document instead.
Purpose
Before you can analyze a system's failure modes, you need to understand what the system actually is. This thinker systematically scans the codebase for structural signals that reveal components, data flows, trust boundaries, and potential attack surface. The output feeds directly into architecture design and failure brainstorming.
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.
- yesterday First seen · 164 lines · 46 tokens per session scan A ff95ae82c63d
codebase-scanner-thinker is an agent published in the GitHub repository danielrmay/claudity (5 stars, last pushed 2mo ago), licensed MIT. It adds 46 tokens to every session and 1,733 once invoked, about $0.0002 per session on Opus 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 2026-08-31.
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