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AutoSci: Skill for Claude Code

.claude/skills/prefill/SKILL.md

prefill is a skill for Claude Code from skyllwt/AutoSci. It costs 24 tokens per session (1,609 once invoked), scanned A, original, MIT.

A command for adding foundational background pages to a research wiki. It covers established concepts in areas such as natural-language processing, computer vision, machine learning systems, and robotics.

In plain words
What is it for?
Use it to seed a domain's standard methods and concepts in the wiki's foundations directory.
Why use it?
It prevents later research notes from repeatedly creating pages for basic textbook concepts.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: reads .claude/ paths.

This is skyllwt/AutoSci's own configuration. It tells Claude Code how to work on AutoSci 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 AutoSci configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 tools/fetch_wikipedia.py summary "<title>".

not rated 1.7krepo 1mo ago A scan SkillSpector: warn 24 tokens original MIT
View source ↗ skyllwt/AutoSci
About the project

AutoSci is an AI research platform organized around a wiki, with an agent that supports stages of scientific work such as reading, experimentation, writing, and retaining knowledge across projects. It is for people building or using AI-assisted research workflows, with Claude Code, Codex, and OpenCode adaptations available. The catalogue add-ons extend those agent-specific workflows.

skyllwt/AutoSci · 1,706 stars · on GitHub

Reuse

Borrowing it

Nothing to install: this file belongs to skyllwt/AutoSci. 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/skyllwt/AutoSci/main/.claude/skills/prefill/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/skyllwt/AutoSci

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 prefill

README.md
[![agentmods](https://agentmods.dev/badge/skills/skyllwt/autosci/prefill/github.svg)](https://agentmods.dev/skills/skyllwt/autosci/prefill)
Your own site
<a href="https://agentmods.dev/skills/skyllwt/autosci/prefill"><img src="https://agentmods.dev/badge/skills/skyllwt/autosci/prefill/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 prefill

Your own site · 80×15
<a href="https://agentmods.dev/skills/skyllwt/autosci/prefill"><img src="https://agentmods.dev/badge/skills/skyllwt/autosci/prefill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,609 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. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Anti-Refusal · line 53
    Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.
    Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
How audits are shown
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 $0.00024 $0.01609
Opus 5.5 $0.00010 $0.00644
Sonnet 5.5 $0.00005 $0.00322
Haiku 4.5 $0.00002 $0.00161

Measured 2mo ago against content hash 66a888d5bf42, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

prefill 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 2mo 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.

.claude/skills/prefill/SKILL.md · 161 lines

How it starts

The opening of the file, as written. The whole thing — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/prefill

Sediments foundational background (seminal methods, common practice, standard architectures) into wiki/foundations/ as terminal pages. Foundations are single-direction by design: other pages link to them, foundations write no reverse links.

Trigger

Manual: /prefill [domain] or /prefill --add "concept name".

Inputs

  • domain (positional, optional): research domain — one of general, NLP, CV, ML Systems, Robotics. If omitted, infer from wiki/topics/ tags; if wiki/topics/ is empty, prompt the user.
  • --add "<concept>": skip the catalog and seed exactly one foundation by name.

Outputs

  • wiki/foundations/{slug}.md — one page per seeded concept
  • Updated wiki/index.md (foundations section regenerated by rebuild-index)
  • wiki/log.md entry

Wiki Interaction

Reads

  • wiki/topics/*.md — for domain inference (when domain is omitted)
  • wiki/foundations/*.md — to skip already-seeded concepts (idempotent)
  • .claude/skills/prefill/foundations-catalog.yaml — seed list

Writes

  • wiki/foundations/{slug}.md (new only — never overwrite)
  • wiki/index.md (via tools/research_wiki.py rebuild-index)
  • wiki/log.md (via tools/research_wiki.py log)

Workflow

Pre-conditions: working directory contains wiki/, tools/, .claude/. Set WIKI_ROOT=wiki/.

Step 1: Resolve domain

  1. If domain argument given → use it.
  2. Else if --add mode → domain is general unless the user specified one.
  3. Else: read all wiki/topics/*.md frontmatter tags; if a single dominant domain is detected, use it; otherwise ask the user.

Step 2: Load seeds

  • Catalog mode: read .claude/skills/prefill/foundations-catalog.yaml. Pick all entries under domains.{domain} plus everything under domains.general (general foundations apply to every research field).
  • --add mode: synthesize a single seed entry {slug: <slugified concept>, title: <concept>, summary: ""}. Use python3 tools/research_wiki.py slug "<concept>" to derive the slug.

Read the full file on GitHub · 161 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. 2mo ago First seen · 161 lines · 24 tokens per session scan A 66a888d5bf42

Subscribe to this mod's changes

prefill is a skill published in the GitHub repository skyllwt/AutoSci (1,706 stars, last pushed 1mo ago), licensed MIT. It adds 24 tokens to every session and 1,609 once invoked, about $0.0001 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.

Research
Related

prefill compared with skills from other repositories

prefill next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
prefillskyllwt/AutoSciSkill1.7k1mo agoMITA24Claude Code
imagegenopenai/codexSkill133kyesterdayApache-2.0A113Codex
playwright-climicrosoft/playwrightSkill99kyesterdayApache-2.0A19Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginnersSkill79k4d agoMITA200Claude Code, Codex
systematic-debuggingobra/superpowersSkill313k3d agoMITA21Claude Code
next-cache-components-adoptionvercel/next.jsSkill143ktodayMITA95Claude Code
next-partial-prefetching-adoptionvercel/next.jsSkill143ktodayMITA103Claude Code