SciCrucible: Skill for Claude Code

.claude/skills/forge-extract/SKILL.md

forge-extract is a skill for Claude Code from Xinyang-Li666/SciCrucible. It costs 86 tokens per session (6,683 once invoked), scanned A, original, GPL-3.0.

A general framework for extracting structured experimental data from research literature. It starts with a question-and-answer setup, tests the process on a small sample, then searches, extracts, and stores the full dataset.

In plain words
What is it for?
Use it to extract data from papers in materials science, chemistry, physics, and other experimental fields, especially when building a structured or machine-learning dataset.
Why use it?
It helps turn scattered experiment details in papers into organized data suitable for a research dataset or machine-learning database. The description does not specify particular source databases or output formats.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is Xinyang-Li666/SciCrucible's own configuration. It tells Claude Code how to work on SciCrucible itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything SciCrucible configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Xinyang-Li666/SciCrucible. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Xinyang-Li666/SciCrucible/main/.claude/skills/forge-extract/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/Xinyang-Li666/SciCrucible

Made for: Claude Code.

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 forge-extract

README.md
[![agentmods](https://agentmods.dev/badge/skills/xinyang-li666/scicrucible/forge-extract/github.svg)](https://agentmods.dev/skills/xinyang-li666/scicrucible/forge-extract)
Your own site
<a href="https://agentmods.dev/skills/xinyang-li666/scicrucible/forge-extract"><img src="https://agentmods.dev/badge/skills/xinyang-li666/scicrucible/forge-extract/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 forge-extract

Your own site · 80×15
<a href="https://agentmods.dev/skills/xinyang-li666/scicrucible/forge-extract"><img src="https://agentmods.dev/badge/skills/xinyang-li666/scicrucible/forge-extract.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,683 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 unknown 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 $0.00086 $0.06683
Opus 5.5 $0.00034 $0.02673
Sonnet 5.5 $0.00017 $0.01337
Haiku 4.5 $0.00009 $0.00668

Measured 1mo ago against content hash c1bc7055ac67, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

forge-extract 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 1mo ago.

The scan reads SKILL.md. This mod also ships 6 executable files (scripts/dedup_check.py, scripts/extract_pdf_to_md.py, scripts/merge_to_db.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.

.claude/skills/forge-extract/SKILL.md · 631 lines

The source is not reproduced here

Licensed GPL-3.0

The repository is licensed GPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

Files

What ships with it

7 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. 1mo ago First seen · 631 lines · 86 tokens per session scan A c1bc7055ac67

Subscribe to this mod's changes

forge-extract is a skill published in the GitHub repository Xinyang-Li666/SciCrucible (13 stars, last pushed 3mo ago), licensed GPL-3.0. It adds 86 tokens to every session and 6,683 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-30.

Related

Other skills, from other repositories

refactor-research-code

Clean research code for public release while preserving reported results. Uses releaseaudit.py to separate safe mechanical cleanup from ask-first behavior risks and identity leaks. Use for release-ready repos, dead experiment branches, config extraction, documented entrypoints, and double-blind code cleanup.

ShaishavMaisuria/research-paper-lifecycle-skills · 60 tokens

prepare-artifacts

Prepares a reproducibility artifact (code/data) for submission and badging. Use when a researcher says "artifact evaluation", "artifact appendix", "reproducibility", "badge", "Artifacts Available/Evaluated/Functional/Reusable", "Results Reproduced/Replicated", "ACM badging", "USENIX/OSDI/SOSP AE", "SIGMOD ARI"…

ShaishavMaisuria/research-paper-lifecycle-skills · 225 tokens

simulate-reviewers

Venue-calibrated peer-review simulation. Use when a researcher says "simulate reviewers", "mock review", "review my paper like a NeurIPS reviewer", "what would Reviewer 2 say", "red-team my paper", "find weaknesses before I submit", "peer review my paper", "strengths and weaknesses / pros and cons of my paper", "what…

ShaishavMaisuria/research-paper-lifecycle-skills · 239 tokens

verify-results

Check whether reported paper metrics are consistent with outputs from the local code artifact. Use for result reproduction checks, artifact evaluation, reproducibility checklists, code-versus-paper audits, table or claim metric comparisons, and badge-readiness review.

ShaishavMaisuria/research-paper-lifecycle-skills · 50 tokens

anonymize-paper

Deep anonymization sweep for double-blind paper submissions, plus clean de-anonymization for camera-ready. Use when a researcher says "anonymize my paper", "double-blind check", "blind this submission", "remove author names", "did I leak my identity" — or, after acceptance, "de-anonymize" / "restore authors for…

ShaishavMaisuria/research-paper-lifecycle-skills · 219 tokens

make-slides

Builds a conference talk deck (Beamer or Marp markdown) from a paper draft - problem-first narrative, one claim per slide, figures reused straight from the paper's LaTeX source, sized to the real slot (12-20 minute full talk vs 5-minute lightning). Use when the user asks to make slides, build a presentation or talk…

ShaishavMaisuria/research-paper-lifecycle-skills · 189 tokens