clinicaltrials-extraction

clinicaltrials-extraction is a skill for Claude Code from usathyan/epistract. It costs 83 tokens per session (4,249 once invoked), scanned A, original, MIT.

A document-extraction skill for clinical-trial materials such as protocols, ethics submissions, study reports, and publications. It identifies trials, treatments, conditions, sponsors, outcomes, and relationships, using ClinicalTrials.gov identifiers when available.

In plain words
What is it for?
Extracting entities and relationships from clinical-trial documents and returning them in the required DocumentExtraction JSON format.
Why use it?
It turns unstructured medical-study documents into consistently structured trial information that can be processed or enriched.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the epistract plugin — 5 skills, 22 commands shipped together

Good fit Extracting entities and relationships from clinical-trial documents and returning them in the required DocumentExtraction JSON format.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/usathyan/epistract/clinicaltrials
Install

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.

Any agent
npx skills add usathyan/epistract --skill clinicaltrials
Clone the repo
git clone --depth 1 https://github.com/usathyan/epistract

Made for: Claude Code.

Or install epistract, the plugin that ships this one along with the rest of its 5 skills, 22 commands.

Wrote 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.

agentmods badge for clinicaltrials-extraction

README.md
[![agentmods](https://agentmods.dev/badge/skills/usathyan/epistract/clinicaltrials/github.svg)](https://agentmods.dev/skills/usathyan/epistract/clinicaltrials)
Your own site
<a href="https://agentmods.dev/skills/usathyan/epistract/clinicaltrials"><img src="https://agentmods.dev/badge/skills/usathyan/epistract/clinicaltrials/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for clinicaltrials-extraction

Your own site · 80×15
<a href="https://agentmods.dev/skills/usathyan/epistract/clinicaltrials"><img src="https://agentmods.dev/badge/skills/usathyan/epistract/clinicaltrials.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 83 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,249 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00083 $0.04249
Opus 5 $0.00042 $0.02124
Sonnet 5 $0.00017 $0.00850
Haiku 4.5 $0.00008 $0.00425

Measured 10d ago against content hash 102ea2c12e9d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

clinicaltrials-extraction 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 10d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (enrich.py, epistemic.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

domains/clinicaltrials/SKILL.md · 530 lines

How it starts

The opening of the file, as written. The whole thing — 530 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Clinical Trials Extraction Skill

NCT ID Capture

For any Trial entity, the name field MUST be the NCT identifier (format: NCT followed by 8 digits, e.g. NCT04303780) when one is present in the document. Study acronyms ("CodeBreaK 200"), sponsor-assigned codes ("AMG 510 study"), and descriptive titles ("Phase 3 study of sotorasib in NSCLC") go into attributes.trial_acronym or attributes.descriptive_title — not into name.

If no NCT ID is present, fall back to the study acronym. Only use a descriptive title as name as a last resort, and set confidence <= 0.6.

This rule exists because the post-build enrichment step resolves Trial nodes against ClinicalTrials.gov via their NCT ID. Nodes without an NCT ID cannot be enriched.

Output Format

Return a DocumentExtraction JSON envelope. The document_id field is REQUIRED. All entities and relations are lists of objects.

{
  "document_id": "nct04303780_protocol",
  "entities": [
    {
      "name": "NCT04303780",
      "entity_type": "Trial",
      "confidence": 0.95,
      "context": "Phase 3 CodeBreaK 200 trial evaluating sotorasib vs docetaxel",
      "attributes": {
        "trial_acronym": "CodeBreaK 200",
        "study_type": "Interventional"
      }
    },
    {
      "name": "sotorasib",
      "entity_type": "Compound",
      "confidence": 0.95,
      "context": "AMG 510; KRAS G12C inhibitor evaluated as experimental arm",
      "attributes": {
        "inn": "sotorasib",
        "sponsor_code": "AMG 510"
      }
    }
  ],
  "relations": [
    {
      "source_entity": "NCT04303780",
      "target_entity": "sotorasib",
      "relation_type": "tests",
      "confidence": 0.95,
      "evidence": "Trial NCT04303780 evaluates sotorasib in the experimental arm"
    }
  ]
}

Field Requirements

Entity fields

  • name (required): Canonical identifier. For Trial, use NCT ID. For Compound, use INN. For Condition, use MeSH term.
  • entity_type (required): Must match one of the 12 types in domain.yaml exactly (case-sensitive).
  • confidence (required): Float 0.0–1.0. See Confidence Calibration section.
  • context (required): Short excerpt or paraphrase from the source document justifying extraction.
  • attributes (optional): Dict of domain-specific metadata (e.g. trial_acronym, sponsor_code, phase, dose).

Read the full file on GitHub · 530 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 10d ago First seen · 530 lines · 83 tokens per session scan A 102ea2c12e9d

Subscribe to this mod's changes

clinicaltrials-extraction is a skill published in the GitHub repository usathyan/epistract (8 stars, last pushed 25d ago), licensed MIT. It adds 83 tokens to every session and 4,249 once invoked, about $0.0004 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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