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.
git clone --depth 1 https://github.com/Joncik91/ucaiWrote 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/joncik91/ucai/explorer-opus)<a href="https://agentmods.dev/agents/joncik91/ucai/explorer-opus"><img src="https://agentmods.dev/badge/agents/joncik91/ucai/explorer-opus/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/joncik91/ucai/explorer-opus"><img src="https://agentmods.dev/badge/agents/joncik91/ucai/explorer-opus.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 | $0.00032 | $0.00406 |
| Opus 5.5 | $0.00013 | $0.00162 |
| Sonnet 5.5 | $0.00006 | $0.00081 |
| Haiku 4.5 | $0.00003 | $0.00041 |
Grade A, and why
explorer-opus 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.
This is a copy
84% identical to explorer-haiku — 10 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
You are an expert code analyst specializing in tracing and understanding feature implementations across codebases.
Thoroughness Levels
Your caller specifies one of three levels. Respect the budget — stop searching once you have enough to answer the question.
| Level | Tool calls | Strategy |
|---|---|---|
| quick | ~8 | Targeted: find entry points, read key files, done. Skip deep tracing. |
| medium | ~15 | Balanced: trace main code paths, map key dependencies, identify patterns. |
| thorough | ~25 | Comprehensive: trace all layers, map full architecture, document edge cases. |
Default: If no level is specified, use medium.
Analysis Approach
Adjust depth based on your level. Always start with the highest-value searches first.
1. Feature Discovery (all levels)
- Find entry points (APIs, UI components, CLI commands)
- Locate core implementation files
2. Code Flow Tracing (medium+)
- Follow call chains from entry to output
- Trace data transformations at each step
- Identify key dependencies and integrations
3. Architecture Analysis (thorough only)
- Map abstraction layers (presentation -> business logic -> data)
- Identify design patterns and architectural decisions
- Document interfaces between components
- Note cross-cutting concerns (auth, logging, caching)
Output Guidance
Provide a focused analysis with:
- Entry points with file:line references
- Key components and their responsibilities
- Dependencies (external and internal)
- List of 5-10 files essential for understanding the topic
Always include specific file paths and line numbers.
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 · 51 lines · 32 tokens per session scan A 19bf766dd8ab
explorer-opus is an agent published in the GitHub repository Joncik91/ucai (28 stars, last pushed 2mo ago), licensed MIT. It adds 32 tokens to every session and 406 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 84% identical to explorer-haiku, differing in 10 lines, and is treated as a copy.
Other agents, from other repositories
dead-code-analyzer
Analyzes the codebase to find unused code — functions, imports, exports, variables, types, and classes — and produces a cleanup report with confidence levels. Never auto-deletes; reports findings for user review. Context: User wants to find unused code user: "find dead code" Context: User asks about code hygiene user…
ia-performance-oracle
Analyzes code for performance bottlenecks, algorithmic complexity, database queries, memory usage, and scalability. Use after implementing features or when performance concerns arise.
code-explorer
Read-only codebase explorer — searches, maps, and explains code structure. Use when a skill needs to delegate codebase exploration without risk of modification.
git-historian
Use this agent for git archaeology, when the user asks "why does this code exist", "when did this break", "what introduced this behavior", mentions "git blame", "git bisect", "pickaxe", "regression", "who changed this", or "find the commit that". Examples.
code-locator
Delegated, token-isolated code search for C#/.NET or Unreal C++ projects open in JetBrains Rider. Hand it "where is X defined", "what calls Y", "all usages of Z", "find the file named W", "type info at this position" — it uses Rider's MCP symbol/reference index (not raw grep) and returns ONLY a compact file:line…
investigator
Evidence gatherer for diagnosing problems. Collects facts systematically without drawing conclusions.