gsd-ai-researcher

<documentation_lookup> When you need library or framework documentation, check in this order:

1. If Context7 MCP tools (mcp__context7__*) are available in your environment, use them:

   • Resolve library ID: mcp__context7__resolve-library-id with libraryName
   • Fetch docs: mcp__context7__get-library-docs with context7CompatibleLibraryId and topic

2. 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 ~/.codex/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(), instructor for direct API, LlamaIndex PydanticOutputParser, OpenAI response_format)
• Retry logic: how many retries, what to log, when to surface