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 commands/usathyan/epistract/enhancegit 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/commands/usathyan/epistract/enhance)<a href="https://agentmods.dev/commands/usathyan/epistract/enhance"><img src="https://agentmods.dev/badge/commands/usathyan/epistract/enhance.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 | $0.00033 | $0.00661 |
| Opus 5 | $0.00016 | $0.00331 |
| Sonnet 5 | $0.00007 | $0.00132 |
| Haiku 4.5 | $0.00003 | $0.00066 |
Grade A, and why
epistract-enhance 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 4d 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.
What it actually says
Improve the quality of a project's built knowledge graph with three research-backed
passes. Operates on <project>/graph_data.json in place and writes an
enhancement_report.json. Runs offline with lexical fallbacks; pass --llm to use a
configured LLM for calibrated judgments.
Requires a built graph — run /epistract:build first.
Passes (if none is named, all three run):
--judge— LLM-as-judge triple gate (GraphJudge arXiv 2411.17388 / GraphEval arXiv 2407.10793): scores each relation against its evidence span, flags triples whose evidence does not support them.--resolve— two-stage entity resolution (ComEM arXiv 2405.16884): blocks by type, clusters by character/token/embedding similarity, merges duplicates (e.g. "GLP-1 Receptor" and "GLP1 receptor").--epistemic— bi-temporal contradiction layer (Graphiti/Zep arXiv 2501.13956) with graded hedge scoring (arXiv 2405.13319): when a newer relation contradicts an older one, the older edge is markedsuperseded(not deleted) with provenance; every edge gets a gradedhedge_scoreand epistemic status (asserted / hypothesized / speculative).
Usage Guard
If invoked with no arguments or with --help: Display the following usage block verbatim and stop.
Usage: /epistract:enhance [--project <name>] [--judge] [--resolve] [--epistemic] [--llm]
Options:
--project <name> Target project (default: detected from cwd or $EPISTRACT_PROJECT)
--judge Only run the triple-judge gate
--resolve Only run entity resolution
--epistemic Only run the bi-temporal epistemic layer
--llm Use the configured LLM instead of the lexical fallback
(no pass flag) Run all three passes
Examples:
/epistract:enhance --project glp1-research
/epistract:enhance --project glp1-research --judge --llm
/epistract:enhance --project acme-contracts --epistemic
PYTHONPATH="${CLAUDE_PLUGIN_ROOT}" python3 -m core.cli enhance [--project NAME] [--judge] [--resolve] [--epistemic] [--llm]
Report the merge count, triple-verdict breakdown, and epistemic status counts (including
any superseded/contradicted edges). This complements /epistract:epistemic, which builds
the domain-specific Super Domain claims narrative.
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.
- 4d ago First seen · 53 lines · 33 tokens per session scan A 082536593b62
epistract-enhance is a command published in the GitHub repository usathyan/epistract (8 stars, last pushed 20d ago), licensed MIT. It adds 33 tokens to every session and 661 once invoked, about $0.0002 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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