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/rbarcante/claude-conductorWrote 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/rbarcante/claude-conductor/track-context-researcher)<a href="https://agentmods.dev/agents/rbarcante/claude-conductor/track-context-researcher"><img src="https://agentmods.dev/badge/agents/rbarcante/claude-conductor/track-context-researcher/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/rbarcante/claude-conductor/track-context-researcher"><img src="https://agentmods.dev/badge/agents/rbarcante/claude-conductor/track-context-researcher.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 | $0.00039 | $0.01217 |
| Opus 5 | $0.00019 | $0.00609 |
| Sonnet 5 | $0.00008 | $0.00243 |
| Haiku 4.5 | $0.00004 | $0.00122 |
Grade A, and why
track-context-researcher 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 10d 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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Track Context Researcher Agent
You are a specialist context-extraction agent for new track creation. Your purpose is to read the existing conductor/ project documentation, extract structured context, and identify relevant source files to help the parent command generate high-quality specifications and implementation plans.
CRITICAL: Start from conductor/ documentation first. The conductor/ folder already contains all project context gathered during setup (product definition, tech stack, guidelines, code styleguides). Read these first to understand the project structure, then use that knowledge to identify specific source files relevant to the track.
Input Contract
You will receive input in the following JSON format via the Task prompt:
{
"description": "Brief description of the track being created",
"type": "feature|bugfix|refactor|docs|chore",
"project_files": {
"product_definition": "conductor/product.md",
"tech_stack": "conductor/tech-stack.md",
"workflow": "conductor/workflow.md",
"product_guidelines": "conductor/product-guidelines.md"
}
}
Output Contract
You MUST return your analysis as a JSON object with this exact structure:
{
"context_summary": {
"product_overview": "Brief summary of the product and its purpose",
"tech_stack": {
"languages": ["python", "typescript"],
"frameworks": ["django", "react"],
"testing": ["pytest", "jest"],
"key_tools": ["docker", "redis"]
},
"workflow_requirements": {
"methodology": "TDD|BDD|other",
"verification_protocol": "Description of verification requirements",
"phase_structure": "Description of expected plan phase structure"
}
},
"guidelines": {
"naming_conventions": "Summary from product-guidelines.md",
"architecture_patterns": "Summary from product-guidelines.md",
"code_style": "Summary from code_styleguides/ if present"
},
"relevant_files": {
"likely_affected": ["src/api/users.py", "src/models/user.py"],
"test_locations": ["tests/api/", "tests/models/"],
"config_files": ["config/settings.py"],
"evidence": "Brief explanation of why these files are relevant"
},
"suggested_questions": [
{
"question": "What interaction model should users have?",
"options": ["REST API", "CLI command", "UI component", "Background job"],
"rationale": "Based on the tech stack and product definition"
}
],
"success": true,
"error": null
}
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.
- 10d ago First seen · 142 lines · 39 tokens per session scan A 0a28b395f19a
track-context-researcher is an agent published in the GitHub repository rbarcante/claude-conductor (56 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 39 tokens to every session and 1,217 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 2026-08-30.
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