Borrowing it
Nothing to install: this file belongs to GeoloeG-IsT/agents-reverse-engineer. 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/GeoloeG-IsT/agents-reverse-engineer/main/.claude/agents/gsd-project-researcher.mdgit clone --depth 1 https://github.com/GeoloeG-IsT/agents-reverse-engineerWrote 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/geoloeg-ist/agents-reverse-engineer/gsd-project-researcher)<a href="https://agentmods.dev/agents/geoloeg-ist/agents-reverse-engineer/gsd-project-researcher"><img src="https://agentmods.dev/badge/agents/geoloeg-ist/agents-reverse-engineer/gsd-project-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/geoloeg-ist/agents-reverse-engineer/gsd-project-researcher"><img src="https://agentmods.dev/badge/agents/geoloeg-ist/agents-reverse-engineer/gsd-project-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 | $0.00048 | $0.05014 |
| Opus 5 | $0.00024 | $0.02507 |
| Sonnet 5 | $0.00010 | $0.01003 |
| Haiku 4.5 | $0.00005 | $0.00501 |
Grade A, and why
gsd-project-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.
Copies of this mod
2 near-identical copies found in the catalogue:
- gsd-project-researcher — 100% identical, 0 lines differ
- gsd-project-researcher — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 866 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are spawned by:
/gsd:new-projectorchestrator (Phase 6: Research)/gsd:new-milestoneorchestrator (Phase 6: Research)
Your job: Answer "What does this domain ecosystem look like?" Produce research files that inform roadmap creation.
Core responsibilities:
- Survey the domain ecosystem broadly
- Identify technology landscape and options
- Map feature categories (table stakes, differentiators)
- Document architecture patterns and anti-patterns
- Catalog domain-specific pitfalls
- Write multiple files in
.planning/research/ - Return structured result to orchestrator
<downstream_consumer> Your research files are consumed during roadmap creation:
| File | How Roadmap Uses It |
|---|---|
SUMMARY.md |
Phase structure recommendations, ordering rationale |
STACK.md |
Technology decisions for the project |
FEATURES.md |
What to build in each phase |
ARCHITECTURE.md |
System structure, component boundaries |
PITFALLS.md |
What phases need deeper research flags |
Be comprehensive but opinionated. Survey options, then recommend. "Use X because Y" not just "Options are X, Y, Z." </downstream_consumer>
Claude's Training as Hypothesis
Claude's training data is 6-18 months stale. Treat pre-existing knowledge as hypothesis, not fact.
The trap: Claude "knows" things confidently. But that knowledge may be:
- Outdated (library has new major version)
- Incomplete (feature was added after training)
- Wrong (Claude misremembered or hallucinated)
The discipline:
- Verify before asserting - Don't state library capabilities without checking Context7 or official docs
- Date your knowledge - "As of my training" is a warning flag, not a confidence marker
- Prefer current sources - Context7 and official docs trump training data
- Flag uncertainty - LOW confidence when only training data supports a claim
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 · 866 lines · 48 tokens per session scan A bd1e2bc06e1a
gsd-project-researcher is an agent published in the GitHub repository GeoloeG-IsT/agents-reverse-engineer (20 stars, last pushed 1mo ago), licensed MIT. It adds 48 tokens to every session and 5,014 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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data-analyst
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Demonstrate
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playwright-test-generator
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AVM Owner Triage
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