A network of agentic research specialists coordinated by a principal investigator agent. V1: web-search researcher MCP server + CLI shim.
7956bf4873
The synthesis step was passing max_tokens=4096 to Claude, which was not enough for a full ResearchResult JSON over a real evidence set (28 sources). The model's output got cut mid-string, json.loads failed, and the agent fell back to a stub answer with zero citations. The trace logger then truncated the raw_response to 1000 chars before recording it, hiding the actual reason for the parse failure (the truncated JSON suffix) and making the bug invisible from traces. Fixes: - Bump synthesis max_tokens to 16384 - Capture and log Claude's stop_reason on synthesis_error so future truncation cases are diagnosable from the trace alone - Log the parser exception text alongside the raw_response - Stop slicing raw_response — record the full string Verified end-to-end against the Utah crops question: - Before: 0 citations, confidence 0.10, fallback stub - After: 9 citations, confidence 0.88, real synthesized answer Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
||
|---|---|---|
| cli | ||
| orchestrator | ||
| researchers | ||
| scripts | ||
| tests | ||
| .dockerignore | ||
| .gitignore | ||
| CLAUDE.md | ||
| CONTRIBUTING.md | ||
| Dockerfile | ||
| 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>
Docker test environment
A reproducible container is available for running the test suite and the CLI without depending on the host's Python install:
scripts/docker-test.sh build # build the image
scripts/docker-test.sh test # run pytest
scripts/docker-test.sh ask "question" # run `marchwarden ask` end-to-end
# (mounts ~/secrets ro and ~/.marchwarden rw)
scripts/docker-test.sh replay <id> # replay a trace from ~/.marchwarden/traces
scripts/docker-test.sh shell # interactive bash in the container
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)