research-extraction

research-extraction is a skill for Claude Code from geronimo-iia/agent-skills. It costs 87 tokens per session (7,173 once invoked), scanned A, original, MIT.

A workflow for extracting structured knowledge from a collection of research sources such as papers, theses, and reports. It records findings across several topics and marks how confidently each claim is supported.

In plain words
What is it for?
Turning multiple source documents into structured knowledge files covering areas such as architecture, messages, algorithms, or forms.
Why use it?
It organizes large research collections and checks each extraction step with a reviewer, making the resulting knowledge easier to trace back to its sources.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: reads .claude/ paths; mentions subagents; mentions Claude Code.

Part of the geronimo-skills plugin — 9 skills shipped together

Good fit Turning multiple source documents into structured knowledge files covering areas such as architecture, messages, algorithms, or forms.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/geronimo-iia/agent-skills/research-extraction
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 geronimo-iia/agent-skills --skill research-extraction
Clone the repo
git clone --depth 1 https://github.com/geronimo-iia/agent-skills

Made for: Claude Code.

Or install geronimo-skills, the plugin that ships this one along with the rest of its 9 skills.

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 research-extraction

README.md
[![agentmods](https://agentmods.dev/badge/skills/geronimo-iia/agent-skills/research-extraction/github.svg)](https://agentmods.dev/skills/geronimo-iia/agent-skills/research-extraction)
Your own site
<a href="https://agentmods.dev/skills/geronimo-iia/agent-skills/research-extraction"><img src="https://agentmods.dev/badge/skills/geronimo-iia/agent-skills/research-extraction/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 research-extraction

Your own site · 80×15
<a href="https://agentmods.dev/skills/geronimo-iia/agent-skills/research-extraction"><img src="https://agentmods.dev/badge/skills/geronimo-iia/agent-skills/research-extraction.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 87 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,173 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. 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 $0.00087 $0.07173
Opus 5 $0.00044 $0.03587
Sonnet 5 $0.00017 $0.01435
Haiku 4.5 $0.00009 $0.00717

Measured 4d ago against content hash 751346518cbb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

research-extraction scanned grade A with 1 finding 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

"Bash(curl *)",
skills/research-extraction/SKILL.md · 679 lines

How it starts

The opening of the file, as written. The whole thing — 679 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research Extraction

Apply kb-conventions skill for annotation markers, KB directory layout, frontmatter schema, and synthesis impact rules.

Multi-axis, confidence-annotated extraction from a research corpus using a Workflow that fans out extractor subagents and gates progression through a reviewer agent after each axis.

Prerequisites

Add to .claude/settings.json (or .claude/settings.local.json) before running:

{
  "permissions": {
    "allow": [
      "Bash(xberg *)",
      "Bash(uvx marker-pdf *)",
      "Bash(curl *)",
      "Bash(mkdir *)",
      "Bash(cp *)",
      "Bash(cat *)"
    ]
  }
}

For fully unattended runs (CI, cron), launch the Claude Code session with --dangerously-skip-permissions instead.

When to use

  • Multiple raw source files (theses, papers, reports) covering one system
  • Claims must be traceable to exact source sections with confidence markers
  • Extraction spans multiple axes too large for one context window
  • You want reviewer-gated, disk-persisted progression (not manual session seeds)
  • Resuming a partial run — pass resumeFromRunId (preferred over manual restart; completed phases return from cache instantly)

Core architecture

Workflow
  phase("Step 0")
    → extractor agent: reads ALL sources, writes reading summary + working memory dump
    → reviewer agent: checks summary completeness, returns confirmed facts JSON

  phase("Axis N")   [sequential, one per axis]
    → extractor agent: reads seed (confirmed facts from prior phases), writes extract-<axis>.md
    → reviewer agent: runs checklist, returns {pass: bool, issues: string[], confirmed_facts: ...}
    → if !pass: re-run extractor with issues until pass (max 2 retries)

  phase("Formalization")
    → extractor agent: reads all confirmed extract-*.md, produces code sketches
    → reviewer agent: checks sketch coverage

Each phase writes its output to disk before the next begins. Reviewer is a separate agent — independent read of the output file, no shared context with extractor.

Read the full file on GitHub · 679 lines

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. 4d ago Changed · +72 lines 751346518cbb
  2. 9d ago First seen · 607 lines · 87 tokens per session scan A 20afdee1b6d1

Subscribe to this mod's changes

research-extraction is a skill published in the GitHub repository geronimo-iia/agent-skills (2 stars, last pushed 9d ago), licensed MIT. It adds 87 tokens to every session and 7,173 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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