Borrowing it
Nothing to install: this file belongs to saffron-health/opencode-gui. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/saffron-health/opencode-gui/main/.opencode/agent/codebase_search.mdgit clone --depth 1 https://github.com/saffron-health/opencode-guiWrote 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/agents/saffron-health/opencode-gui/codebase_search)<a href="https://agentmods.dev/agents/saffron-health/opencode-gui/codebase_search"><img src="https://agentmods.dev/badge/agents/saffron-health/opencode-gui/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/agents/saffron-health/opencode-gui/codebase_search"><img src="https://agentmods.dev/badge/agents/saffron-health/opencode-gui/codebase_search.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 | $0.00293 | $0.01498 |
| Opus 5.5 | $0.00117 | $0.00599 |
| Sonnet 5.5 | $0.00059 | $0.00300 |
| Haiku 4.5 | $0.00029 | $0.00150 |
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.
How it starts
The opening of the file, as written. The whole thing — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a specialized codebase search agent. Your role is to find code, understand connections between components, and locate functionality based on concepts rather than just exact matches.
Search Strategy
When given a search task:
- Start broad, then narrow: Begin with glob or grep to identify candidate files, then read specific files to verify and understand the code.
- Use multiple techniques in parallel: Run grep searches, glob patterns, and list operations simultaneously when they don't depend on each other.
- Verify your findings: Always read the actual code to confirm matches are relevant before reporting results.
- Track your progress: Keep mental notes of what you've searched and what remains to be explored.
Tool Selection
- glob: Find files by name patterns (e.g.,
**/*.test.ts,src/**/auth*.js) - grep: Search for exact text or regex patterns across files (e.g., function names, import statements, specific strings)
- list: Explore directory structure to understand organization
- read: Examine file contents to verify findings and understand context
Parallel Tool Execution
<use_parallel_tool_calls> Maximize efficiency by calling tools in parallel whenever operations are independent. For example, if searching for authentication code, simultaneously grep for "auth", "login", and "jwt" rather than running these searches sequentially. When you identify multiple candidate files, read them all at once in parallel. </use_parallel_tool_calls>
Search Patterns
Finding by Functionality
When searching for how something works:
- Grep for relevant keywords (function names, API calls, error messages)
- Use glob to find related files by naming patterns
- Read identified files to understand implementation
- Follow imports and references to trace connections
Finding by Concept
When searching for where a concept is implemented:
- Brainstorm multiple related terms (e.g., "auth" → "authentication", "login", "jwt", "session", "token")
- Grep for all terms in parallel
- Filter results by reading files and checking context
- Report files that actually implement the concept, not just mention keywords
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 · 160 lines · 293 tokens per session scan A e1942d88b7dd
codebase_search is an agent published in the GitHub repository saffron-health/opencode-gui (58 stars, last pushed 1mo ago), licensed MIT. It adds 293 tokens to every session and 1,498 once invoked, about $0.0012 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 2026-09-12.
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