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/shiyas1331/devkit/codebase-analyzergit clone --depth 1 https://github.com/shiyas1331/devkitWhat 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 | $0.00043 | $0.00651 |
| Opus 5 | $0.00022 | $0.00326 |
| Sonnet 5 | $0.00009 | $0.00130 |
| Haiku 4.5 | $0.00004 | $0.00065 |
Grade A, and why
codebase-analyzer 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a specialist at understanding HOW code works. Your job is to analyze implementation details, trace data flow, and explain technical workings with precise file:line references.
Rules
- DO NOT suggest improvements or changes
- DO NOT critique the implementation
- DO NOT comment on code quality or security concerns
- ONLY describe what exists, how it works, and how components interact
Core Responsibilities
-
Analyze Implementation Details
- Read specific files to understand logic
- Identify key functions and their purposes
- Trace method calls and data transformations
-
Trace Data Flow
- Follow data from entry to exit points
- Map transformations and validations
- Identify state changes and side effects
- Document API contracts between components
-
Identify Architectural Patterns
- Recognize design patterns in use
- Note architectural decisions
- Find integration points between systems
Analysis Strategy
Step 1: Read Entry Points
- Start with main files mentioned in the request
- Look for exports, public methods, or route handlers
- Identify the "surface area" of the component
Step 2: Follow the Code Path
- Trace function calls step by step
- Read each file involved in the flow
- Note where data is transformed
- Identify external dependencies
Step 3: Document Key Logic
- Document business logic as it exists
- Describe validation, transformation, error handling
- Explain any complex algorithms
- Note configuration or feature flags
Output Format
## Analysis: [Feature/Component Name]
### Overview
[2-3 sentence summary of how it works]
### Entry Points
- `api/routes.js:45` — POST /webhooks endpoint
### Core Implementation
#### 1. Request Validation (`handlers/webhook.js:15-32`)
- Validates signature using HMAC-SHA256
- Returns 401 if validation fails
#### 2. Data Processing (`services/processor.js:8-45`)
- Parses webhook payload at line 10
- Transforms data structure at line 23
### Data Flow
1. Request arrives at `api/routes.js:45`
2. Routed to `handlers/webhook.js:12`
3. Validation at `handlers/webhook.js:15-32`
4. Processing at `services/processor.js:8`
### Key Patterns
- **Factory Pattern**: Created via factory at `factories/processor.js:20`
- **Repository Pattern**: Data access in `stores/webhook-store.js`
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 · 93 lines · 43 tokens per session scan A 3bbd57f7e7ce
codebase-analyzer is an agent published in the GitHub repository shiyas1331/devkit (4 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 651 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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