A network of agentic research specialists coordinated by a principal investigator agent. V1: web-search researcher MCP server + CLI shim.
ae9c11a79b
New field on ResearchResult: open_questions — follow-up questions that emerged from the research itself. Distinct from gaps (backward: what failed) and discovery_events (sideways: what's lateral). Open questions look forward: 'based on what I found, this needs deeper investigation.' - OpenQuestion model: question, context, priority (high/medium/low), source_locator - Updated agent synthesis prompt to produce open_questions - Updated agent result builder to parse open_questions from JSON - 3 new tests for OpenQuestion model - Updated existing tests for new field 77 tests passing. Refs: archeious/marchwarden#1 Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com> |
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| cli | ||
| orchestrator | ||
| researchers | ||
| tests | ||
| .gitignore | ||
| CONTRIBUTING.md | ||
| pyproject.toml | ||
| README.md | ||
Marchwarden
A network of agentic research specialists coordinated by a principal investigator agent.
Marchwarden researchers are stationed at the frontier of knowledge — they watch, search, synthesize, and report back what they find. Each specialist is self-contained, fault-tolerant, and exposed via MCP. The PI agent orchestrates them to answer complex, multi-domain questions.
V1: Single web-search researcher + CLI shim for development.
V2+: Multiple specialists (arxiv, database, internal docs, etc.) + PI orchestrator.
Quick start
# Clone
git clone https://forgejo.labbity.unbiasedgeek.com/archeious/marchwarden.git
cd marchwarden
# Install
pip install -e .
# Ask a question
marchwarden ask "What are ideal crops for a garden in Utah?"
# Replay a research session
marchwarden replay <trace_id>
Documentation
- Architecture — system design, researcher contract, MCP flow
- Development Guide — setup, running tests, debugging
- Research Contract — the
research()tool specification - Contributing — branching, commits, PR workflow
Status
- V1 scope: Issue #1
- Branch:
main(development) - Tests:
pytest tests/
Stack
- Language: Python 3.10+
- Agent framework: Anthropic Claude Agent SDK
- MCP server: Model Context Protocol
- Web search: Tavily API
License
(TBD)