research-ingestion

research-ingestion is a skill for Claude Code, Codex from OpenCoven/coven. It costs 56 tokens per session (1,015 once invoked), scanned C, original, MIT.

A workflow for reading research papers and turning their findings into practical agent skills or workflow changes. Research papers are formal reports of academic or technical studies.

In plain words
What is it for?
Use it to analyze a paper from a PDF or URL, extract actionable insights, create OpenClaw skills, and improve agent workflows.
Why use it?
It converts dense research into concrete techniques instead of leaving useful findings buried in a paper.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: mentions subagents; built for openclaw.

Good fit Use it to analyze a paper from a PDF or URL, extract actionable insights, create OpenClaw skills, and improve agent workflows.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/opencoven/coven/research-ingestion
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 OpenCoven/coven --skill research-ingestion
Clone the repo
git clone --depth 1 https://github.com/OpenCoven/coven

Made for: Claude Code, Codex.

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-ingestion

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/opencoven/coven/research-ingestion"><img src="https://agentmods.dev/badge/skills/opencoven/coven/research-ingestion.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 56 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,015 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 3 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 $0.00056 $0.01015
Opus 5 $0.00028 $0.00508
Sonnet 5 $0.00011 $0.00203
Haiku 4.5 $0.00006 $0.00102

Measured 10d ago against content hash 6b1d8f6b0775, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade C, and why

research-ingestion scanned grade C with 3 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.

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.

Downloads and executes remote codehighSupply chain

curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.

curl -sL "<url>" | python3 -c "

Makes network callslowCapability

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

curl -sL "<url>" | python3 -c "

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

result = subprocess.run(['pdftotext', '-', '-'], input=sys.stdin.buffer.read(), capture_output=True)
skills/research-ingestion/SKILL.md · 167 lines

How it starts

The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research Ingestion

Analyze research papers and extract actionable insights for OpenClaw agent workflows.

Trigger Phrases

  • "analyze this paper", "read this research", "extract insights from"
  • "turn this paper into a skill", "what can we learn from this paper"
  • "research to skill", "/research"

Workflow

1. Obtain Paper Text

From URL (arXiv, PDF link, blog post):

# Use the summarize skill for URLs
# Or fetch + extract directly:
curl -sL "<url>" | python3 -c "
import sys
try:
    import fitz  # PyMuPDF
    doc = fitz.open(stream=sys.stdin.buffer.read(), filetype='pdf')
    print('\n'.join(page.get_text() for page in doc))
except ImportError:
    # Fallback: use pdftotext if available
    import subprocess
    result = subprocess.run(['pdftotext', '-', '-'], input=sys.stdin.buffer.read(), capture_output=True)
    print(result.stdout.decode())
"

From local file:

python3 -c "
import fitz
doc = fitz.open('$FILE_PATH')
for page in doc: print(page.get_text())
"

Fallback (no PDF tools): Use the summarize skill or web_fetch tool on the paper's URL. For arXiv papers, use the HTML version: https://arxiv.org/html/<id>.

2. Analyze with Structured Extraction

After obtaining the text, extract these categories:

## Paper: <title>
Authors: <authors>
Published: <date>
Source: <url>

### Core Contribution
<1-2 sentence summary of what's new>

### Key Techniques
- <technique 1>: <how it works, 2-3 sentences>
- <technique 2>: ...

### Agent Workflow Implications
- <how this applies to OpenClaw agent behavior>
- <specific workflow improvements suggested>

### Actionable Insights
1. <concrete thing we can implement>
2. <concrete thing we can implement>

### Skill Candidates
- <potential skill name>: <what it would do, trigger phrases>

### Limitations & Caveats
- <what doesn't apply or needs adaptation>

3. Generate Skill (if requested)

When asked to turn insights into a skill, use this scaffold:

---
name: <skill-name>
description: <one-line description derived from paper insight>
---

# <Skill Name>

Based on: <paper title> (<url>)

## When to Use
<trigger conditions>

## Technique
<extracted technique adapted for OpenClaw context>

## Workflow
<step-by-step procedure>

## Example
<concrete usage example>

Read the full file on GitHub · 167 lines

Files

What ships with it

1 file 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 · 167 lines · 56 tokens per session scan C 6b1d8f6b0775

Subscribe to this mod's changes

research-ingestion is a skill published in the GitHub repository OpenCoven/coven (47 stars, last pushed today), licensed MIT. It adds 56 tokens to every session and 1,015 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 3 findings (downloads and executes remote code, makes network calls, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.