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 tmcfarlane/oh-my-cursor --skill codebase-searchgit clone --depth 1 https://github.com/tmcfarlane/oh-my-cursorWrote 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/tmcfarlane/oh-my-cursor/codebase-search)<a href="https://agentmods.dev/skills/tmcfarlane/oh-my-cursor/codebase-search"><img src="https://agentmods.dev/badge/skills/tmcfarlane/oh-my-cursor/codebase-search/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/tmcfarlane/oh-my-cursor/codebase-search"><img src="https://agentmods.dev/badge/skills/tmcfarlane/oh-my-cursor/codebase-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00041 | $0.02945 |
| Opus 5.5 | $0.00016 | $0.01178 |
| Sonnet 5.5 | $0.00008 | $0.00589 |
| Haiku 4.5 | $0.00004 | $0.00295 |
Grade A, and why
codebase-search 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- codebase-search — 95% identical, 8 lines differ
How it starts
The opening of the file, as written. The whole thing — 533 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codebase Search
When to use this skill
- Finding specific functions or classes
- Tracing function calls and dependencies
- Understanding code structure and architecture
- Finding usage examples
- Identifying code patterns
- Locating bugs or issues
- Code archaeology (understanding legacy code)
- Impact analysis before changes
Instructions
Step 1: Understand what you're looking for
Feature implementation:
- Where is feature X implemented?
- How does feature Y work?
- What files are involved in feature Z?
Bug location:
- Where is this error coming from?
- What code handles this case?
- Where is this data being modified?
API usage:
- How is this API used?
- Where is this function called?
- What are examples of using this?
Configuration:
- Where are settings defined?
- How is this configured?
- What are the config options?
Step 2: Choose search strategy
Semantic search (for conceptual questions):
Use when: You understand what you're looking for conceptually
Examples:
- "How do we handle user authentication?"
- "Where is email validation implemented?"
- "How do we connect to the database?"
Benefits:
- Finds relevant code by meaning
- Works with unfamiliar codebases
- Good for exploratory searches
Grep (for exact text/patterns):
Use when: You know exact text or patterns
Examples:
- Function names: "def authenticate"
- Class names: "class UserManager"
- Error messages: "Invalid credentials"
- Specific strings: "API_KEY"
Benefits:
- Fast and precise
- Works with regex patterns
- Good for known terms
Glob (for file discovery):
Use when: You need to find files by pattern
Examples:
- "**/*.test.js" (all test files)
- "**/config*.yaml" (config files)
- "src/**/*Controller.py" (controllers)
Benefits:
- Quickly find files by type
- Discover file structure
- Locate related files
Step 3: Search workflow
1. Start broad, then narrow:
Step 1: Semantic search "How does authentication work?"
Result: Points to auth/ directory
Step 2: Grep in auth/ for specific function
Pattern: "def verify_token"
Result: Found in auth/jwt.py
Step 3: Read the file
File: auth/jwt.py
Result: Understand implementation
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 · 533 lines · 41 tokens per session scan A 53413c9581a7
codebase-search is a skill published in the GitHub repository tmcfarlane/oh-my-cursor (109 stars, last pushed 3mo ago), licensed MIT. It adds 41 tokens to every session and 2,945 once invoked, about $0.0002 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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