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.
npx agentmods add instructions/usathyan/epistract/claude-mdgit clone --depth 1 https://github.com/usathyan/epistractWrote 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/instructions/usathyan/epistract/claude-md)<a href="https://agentmods.dev/instructions/usathyan/epistract/claude-md"><img src="https://agentmods.dev/badge/instructions/usathyan/epistract/claude-md.svg" alt="Measured on agentmods" 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 | $0.04426 | $0.04426 |
| Opus 5 | $0.02213 | $0.02213 |
| Sonnet 5 | $0.00885 | $0.00885 |
| Haiku 4.5 | $0.00443 | $0.00443 |
Grade A, and why
epistract CLAUDE.md 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 273 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project
Epistract — Domain-Agnostic Knowledge Graph Framework
Epistract is a domain-agnostic knowledge graph framework. Plug in a domain schema (YAML + extraction prompts + epistemic rules), point at a document corpus, and get a structured knowledge graph with an epistemic analysis layer. It runs as a Claude Code plugin.
Core Value: Extract knowledge, not information. Any corpus, any domain — plug in a schema, get a knowledge graph with epistemic layer that reveals what documents say, what they contradict, and what they are missing.
Two pre-built domains demonstrate the framework:
- drug-discovery — 17 entity types, 30 relation types for biomedical literature analysis
- contracts — 11 entity types, 11 relation types for event/vendor contract analysis
Constraints
- Tech stack: Python 3.11+, uv for package management
- Document formats: PDF, DOCX, HTML, TXT, XLS, EML — 75+ formats via Kreuzberg with OCR fallback
- Large files: Some documents are 12-31 MB — extraction must handle large documents
- Domain pluggability: New domains added via configuration package (domain.yaml + SKILL.md + epistemic.py), no pipeline code changes
- Existing codebase: Must preserve backward compatibility with all existing domains
Technology Stack
Languages
- Python 3.11+ - Core runtime for knowledge graph building, molecular validation, plugin integration
- Bash - Setup and utility scripts
- YAML - Domain schema and configuration
Runtime
- Python 3.11 or later (enforced in
scripts/setup.sh) - Claude Code plugin runtime (runs as Claude Code marketplace plugin)
uv(preferred) - For installing Python dependenciespip(fallback) - Alternative package management
Frameworks
- sift-kg ≥0.9.0 - Knowledge graph construction, document ingestion, entity resolution, visualization, export
- Kreuzberg ≥4.0 - Text extraction from 75+ document formats (PDF, DOCX, HTML, TXT, etc.) with OCR support for scans
- pdfplumber ≥0.10 - Legacy PDF extraction backend
- Pydantic ≥2.5 - Validation and serialization for DocumentExtraction models (entities, relations, attributes)
- NetworkX ≥3.2 - Graph data structure (MultiDiGraph) for knowledge graph nodes and edges
- pytest - Unit test framework (run:
python -m pytest tests/test_unit.py -v) - ruff - Linting and code formatting (
ruff check,ruff format)
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.
- 5d ago First seen · 273 lines · 4,426 tokens per session scan A 436ffa5a698d
epistract CLAUDE.md is an instructions file published in the GitHub repository usathyan/epistract (8 stars, last pushed 20d ago), licensed MIT. It adds 4,426 tokens to every session, about $0.0221 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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