docmancer 0.3.0

Compress local documentation context for coding agents.

docmancer

Compress documentation context so coding agents spend tokens on code.

Docmancer fetches documentation, normalizes it into inspectable sections, indexes those sections with SQLite FTS5, and returns compact context packs with source attribution. The goal is agentic runway: your agent should burn tokens on implementation, tests, and debugging, not on rereading entire documentation sites.

In a typical agentic coding session, raw docs pages can consume 30 to 40 percent of the context window. Docmancer compresses that overhead by 60 to 90 percent, so the agent stays sharp longer, runs more iterations before context degradation, and produces more output per session.

Quickstart

pipx install docmancer --python python3.13

docmancer setup
docmancer add https://docs.example.com
docmancer query "How do I authenticate?"

setup creates ~/.docmancer/docmancer.yaml, initializes ~/.docmancer/docmancer.db, and installs detected agent skills. Use setup --all for non-interactive installation across all supported agents.

What It Does

• Uses SQLite FTS5 by default. No Qdrant server, no embedding model download, no vector database startup.
• Stores normalized sections in SQLite and writes extracted markdown/json files under .docmancer/extracted/ for inspection.
• Supports documentation URLs, GitHub README and docs markdown, local directories, and markdown/text files.
• Returns compact context packs with estimated docs-token savings and agentic runway.

Commands

Command	What it does
docmancer setup	Create config/database and install detected agent skills
docmancer setup --all	Non-interactively install all supported agent integrations
docmancer add <url-or-path>	Fetch or read documentation and index normalized sections
docmancer update	Re-fetch and re-index all existing docs sources
docmancer update <source>	Re-fetch and re-index a specific source
docmancer query <text>	Return a compact markdown context pack
docmancer query <text> --format json	Return the same context pack as JSON
docmancer query <text> --expand	Include adjacent sections around matches
docmancer query <text> --expand page	Include the full matching page, subject to the token budget
docmancer list	List indexed docsets or sources
docmancer inspect	Show SQLite index stats and extract locations
docmancer remove <source>	Remove a source or docset root
docmancer doctor	Check config, SQLite FTS5, index stats, and agent skill installs
docmancer init	Create a project-local docmancer.yaml
docmancer install <agent>	Advanced/manual skill installation for a single agent

Retrieval Shape

By default, query uses a 2400 token budget and returns markdown. It includes a summary like:

Context pack: ~900 tokens vs ~4800 raw docs tokens (81.2% less docs overhead, 5.33x agentic runway)

The savings are estimates, but the direction is explicit: compress docs overhead so the remaining token budget goes into useful agent work.

Keeping Docs Up To Date

Run docmancer update to refresh all indexed sources. Docmancer re-fetches each URL or re-reads each local path and updates the index in place. Only the content that changed gets reprocessed.

To update a single source:

docmancer update https://docs.example.com

Project-Local Config

Global config is stored under ~/.docmancer/ by default. To use a project-local index:

docmancer init
docmancer add ./docs

The generated docmancer.yaml points to .docmancer/docmancer.db and .docmancer/extracted inside the project. If no project config exists, docmancer falls back to the global config.

Supported Agents

setup detects common agent installations. Manual installation remains available:

docmancer install claude-code
docmancer install claude-desktop
docmancer install codex
docmancer install cursor
docmancer install cline
docmancer install gemini
docmancer install opencode

Claude Desktop receives a zip package that can be uploaded through Claude Desktop's Skills UI.

Evals

docmancer eval is available as an optional quality layer for benchmarking compression quality. It compares raw docs context against docmancer context packs and measures whether token reduction degrades answer quality.