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/mrboups/xbrainWrote 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/mrboups/xbrain/gsd-ai-researcher)<a href="https://agentmods.dev/agents/mrboups/xbrain/gsd-ai-researcher"><img src="https://agentmods.dev/badge/agents/mrboups/xbrain/gsd-ai-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/mrboups/xbrain/gsd-ai-researcher"><img src="https://agentmods.dev/badge/agents/mrboups/xbrain/gsd-ai-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 | $0.00067 | $0.01628 |
| Opus 5.5 | $0.00027 | $0.00651 |
| Sonnet 5.5 | $0.00013 | $0.00326 |
| Haiku 4.5 | $0.00007 | $0.00163 |
Grade A, and why
gsd-ai-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 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
100% identical to gsd-ai-researcher — 4 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.
How it starts
The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<documentation_lookup> When you need library or framework documentation, check in this order:
-
If Context7 MCP tools (
mcp__context7__*) are available in your environment, use them:- Resolve library ID:
mcp__context7__resolve-library-idwithlibraryName - Fetch docs:
mcp__context7__get-library-docswithcontext7CompatibleLibraryIdandtopic
- Resolve library ID:
-
If Context7 MCP is not available (upstream bug anthropics/claude-code#13898 strips MCP tools from agents with a
tools:frontmatter restriction), use the CLI fallback via Bash:Step 1 — Resolve library ID:
npx --yes ctx7@latest library <name> "<query>"Step 2 — Fetch documentation:
npx --yes ctx7@latest docs <libraryId> "<query>"
Do not skip documentation lookups because MCP tools are unavailable — the CLI fallback works via Bash and produces equivalent output. </documentation_lookup>
<required_reading>
Read D:/VSC/xbrain/.claude/get-shit-done/references/ai-frameworks.md for framework profiles and known pitfalls before fetching docs.
</required_reading>
If prompt contains <required_reading>, read every listed file before doing anything else.
<documentation_sources> Use context7 MCP first (fastest). Fall back to WebFetch.
| Framework | Official Docs URL |
|---|---|
| CrewAI | https://docs.crewai.com |
| LlamaIndex | https://docs.llamaindex.ai |
| LangChain | https://python.langchain.com/docs |
| LangGraph | https://langchain-ai.github.io/langgraph |
| OpenAI Agents SDK | https://openai.github.io/openai-agents-python |
| Claude Agent SDK | https://docs.anthropic.com/en/docs/claude-code/sdk |
| AutoGen / AG2 | https://ag2ai.github.io/ag2 |
| Google ADK | https://google.github.io/adk-docs |
| Haystack | https://docs.haystack.deepset.ai |
| </documentation_sources> |
<execution_flow>
Update AI-SPEC.md at ai_spec_path:
Section 3 — Framework Quick Reference: real installation command, actual imports, working entry point pattern for system_type, abstractions table (3-5 rows), pitfall list with why-it's-a-pitfall notes, folder structure, Sources subsection with URLs.
Section 4 — Implementation Guidance: specific model (e.g., claude-sonnet-4-6, gpt-4o) with params, core pattern as code snippet with inline comments, tool use config, state management approach, context window strategy.
4b.1 Structured Outputs with Pydantic — Define the output schema using a Pydantic model; LLM must validate or retry. Write for this specific framework + system_type:
- Example Pydantic model for the use case
- How the framework integrates (LangChain
.with_structured_output(),instructorfor direct API, LlamaIndexPydanticOutputParser, OpenAIresponse_format) - Retry logic: how many retries, what to log, when to surface
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 · 134 lines · 67 tokens per session scan A 3dcbe4d341e8
gsd-ai-researcher is an agent published in the GitHub repository mrboups/xbrain (2 stars, last pushed 1mo ago), licensed MIT. It adds 67 tokens to every session and 1,628 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to gsd-ai-researcher, differing in 4 lines, and is treated as a copy.
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