Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/beita6969-skill-creator
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: security, writing, agent-building
Reviews
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What's inside
- Skill name
skill-creator- Description
- Create, edit, improve, or audit AgentSkills. Use when creating a new skill from scratch or when asked to improve, review, audit, tidy up, or clean up an existing skill or SKILL.md file. Also use when editing or restructuring a skill directory (moving files to references/ or scripts/, removing stale content, validating against the AgentSkills spec). Triggers on phrases like "create a skill", "author a skill", "tidy up a skill", "improve this skill", "review the skill", "clean up the skill", "audit the skill".
- License
- MIT
- Instructions
- 369 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Agent Skills spec issues
- files: referenced but missing: scripts/rotate_pdf.py, references/finance.md, references/mnda.md, references/policies.md, references/api_docs.md
Files (7)
- SKILL.md
- license.txt
- init_skill.py · scripts/
- package_skill.py · scripts/
- quick_validate.py · scripts/
- test_package_skill.py · scripts/
- test_quick_validate.py · scripts/
SKILL.md (first lines)
# Skill Creator
This skill provides guidance for creating effective skills.
## About Skills
Skills are modular, self-contained packages that extend Codex's capabilities by providing
specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific
domains or tasks—they transform Codex from a general-purpose agent into a specialized agent
equipped with procedural knowledge that no model can fully possess.
### What Skills Provide
1. Specialized workflows - Multi-step procedures for specific domains
2. Tool integrations - Instructions for working with specific file formats or APIs
3. Domain expertise - Company-specific knowledge, schemas, business logic
4. Bundled resources - Scripts, references, and assets for complex and repetitive tasks
## Core Principles
### Concise is Key
The context window is a public good. Skills share the context window with everything else Codex needs: system prompt, conversation history, other Skills' metadata, and the actual user request.
**Default assumption: Codex is already very smart.** Only add context Codex doesn't already have. Challenge each piece of information: "Does Codex really need this explanation?" and "Does this paragraph justify its token cost?"
Prefer concise examples over verbose explanations.
### Set Appropriate Degrees of Freedom
Match the level of specificity to the task's fragility and variability:
**High freedom (text-based instructions)**: Use when multiple approaches are valid, decisions depend on context, or heuristics guide the approach.
**Medium freedom (pseudocode or scripts with parameters)**: Use when a preferred pattern exists, some variation is acceptable, or configuration affects behavior.
**Low freedom (specific scripts, few parameters)**: Use when operations are fragile and error-prone, consistency is critical, or a specific sequence must be followed.
Think of Codex as exploring a path: a narrow bridge with cliffs needs specific guardrails (low freedom), while an open field allows many routes (high freedom).
### Anatomy of a Skill
Every skill consists of a required SKILL.md file and optional bundled resources:
```
skill-name/
├── SKILL.md (required)
│ ├── YAML frontmatter metadata (required)
│ │ ├── name: (required)
│ │ └── description: (required)
│ └── Markdown instructions (required)
└── Bundled Resources (optional)
├── scripts/ - Executable code (Python/Bash/etc.)
├── references/ - Documentation intended to be loaded into context as needed
└── assets/ - Files used in output (templates, icons, fonts, etc.)
```
#### SKILL.md (required)
Every SKILL.md consists of:
- **Frontmatter** (YAML): Contains `name` and `description` fields. These are the only fields that Codex reads to determine when the skill gets used, thus it is very important to be clear and comprehensive in describing what the skill is, and when it should be used.
- **Body** (Markdown): Instructions and guidance for using the skill. Only loaded AFTER the skill triggers (if at all).
#### Bundled Resources (optional)
##### Scripts (`scripts/`)
Executable code (Python/Bash/etc.) for tasks that require deterministic reliability or are repeatedly rewritten.
- **When to include**: When the same code is being rewritten repeatedly or deterministic reliability is needed
- **Example**: `scripts/rotate_pdf.py` for PDF rotation tasks
- **Benefits**: Token efficient, deterministic, may be executed without loading into context
- **Note**: Scripts may still need to be read by Codex for patching or environment-specific adjustments
##### References (`references/`)
Documentation and reference material intended to be loaded as needed into context to inform Codex's process and thinking.
- **When to include**: For documentation that Codex should reference while working
- **Examples**: `references/finance.md` for financial schemas, `references/mnda.md` for company NDA template, `references/policies.md` for company policies, `references/api_docs.md` for API specifications
- **Use cases**: Database schemas, API documentation, domain knowledge, company policies, detailed workflow guides
- **Benefits**: Keeps SKILL.md lean, loaded only when Codex determines it's needed
- **Best practice**: If files are large (>10k words), include grep search patterns in SKILL.md
- **Avoid duplication**: Information should live in either SKILL.md or references files, not both. Prefer references files for detailed information unless it's truly core to the skill—this keeps SKILL.md lean while making information discoverable without hogging the context window. Keep only essential procedural instructions and workflow guidance in SKILL.md; move detailed reference material, schemas, and examples to references files.
##### Assets (`assets/`)
Files not intended to be loaded into context, but rather used within the output Codex produces.
- **When to include**: When the skill needs files that will be used in the final output
- **Examples**: `assets/logo.png` for brand assets, `assets/slides.pptx` for PowerPoint templates, `assets/frontend-template/` for HTML/React boilerplate, `assets/font.ttf` for typography
- **Use cases**: Templates, images, icons, boilerplate code, fonts, sample documents that get copied or modified
- **Benefits**: Separates output resources from documentation, enables Codex to use files without loading them into context
#### What to Not Include in a Skill
A skill should only contain essential files that directly support its functionality. Do NOT create extraneous documentation or auxiliary files, including:
- README.md
- INSTALLATION_GUIDE.md
- QUICK_REFERENCE.md
- CHANGELOG.md
- etc.
The skill should only contain the information needed for an AI agent to do the job at hand. It should not contain auxiliary context about the process that went into creating it, setup and testing procedures, user-facing documentation, etc. Creating additional documentation files just adds clutter and confusion.
### Progressive Disclosure Design Principle
Skills use a three-level loading system to manage context efficiently:
1. **Metadata (name + description)** - Always in context (~100 words)
2. **SKILL.md body** - When skill triggers (<5k words)
3. **Bundled resources** - As needed by Codex (Unlimited because scripts can be executed without reading into context window)
#### Progressive Disclosure Patterns
Keep SKILL.md body to the essentials and under 500 lines to minimize context bloat. Split content into separate files when approaching this limit. When splitting out content into other files, it is very important to reference them from SKILL.md and describe clearly when to read them, to ensure the reader of the skill knows they exist and when to use them.From beita6969/ScienceClaw, MIT.
More from beita6969/ScienceClaw
- 0.608score
scienceclaw-benchmark-for51
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Use when a task asks to predict a phonon property of inorganic crystals from their structure, for example the frequency of the last peak of the phonon density…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for44
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Use when a task gives a covariate table plus, for each of many simulated observational datasets, a binary treatment vector and an outcome vector, and asks for…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for43
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Use when a task gives noisy OCR text of historical newspapers, periodicals or books (several languages, with metadata and a set of labelled OCR/ground-truth…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for34
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Use when predicting a binary molecular property such as HIV replication inhibition (OGB ogbg-molhiv, MoleculeNet-style activity) from SMILES strings and…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for42
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Use when a task gives hourly ICU records (vitals, labs, demographics, one stay per patient) with sepsis labels and asks for causal hour-by-hour sepsis alarms…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for33
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Use when forecasting day-ahead hourly electricity load of individual buildings (residential and commercial smart-meter data, BuildingsBench-style) from the…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for32
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Use when segmenting the hippocampus into anterior and posterior parts in small 3-D T1-weighted brain MRI crops (Medical Segmentation Decathlon Task04) from a…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for35
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Use when forecasting monthly tourism, visitor or other seasonal business and service series (Monash Tourism Monthly, 24-month horizon, period 12) from each…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
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Index of the 23 discipline skills (FoR30-FoR52) that mirror the disciplines of the companion ScienceClaw-Eval benchmark: find which discipline skill fits a…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for30
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Use when segmenting top-down field or UAV RGB images of crops (sugar beet, PhenoBench-style) into soil / crop / weed semantics plus crop-plant and crop-leaf…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for31
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Use when ranking or predicting the fitness effect of single amino-acid substitutions in a protein (deep mutational scanning, ProteinGym-style assays) from…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for46
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Use when a task gives Python programming problems (a function stub with docstring or a task description, an entry-point name, a few public assert tests) and…
SkillAFreshness: A★ 1KClaude Code +9
Signals
- Stars
- 1,019
- Forks
- 109
- Open issues
- 1
- Last commit (this folder)
- Mar 12, 2026 (7 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/beita6969/ScienceClaw
- Website
- scienceclaw.science
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Use when forecasting day-ahead hourly electricity load of individual buildings (residential and commercial smart-meter data, BuildingsBench-style) from the…
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scienceclaw-benchmark-for34
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Use when predicting a binary molecular property such as HIV replication inhibition (OGB ogbg-molhiv, MoleculeNet-style activity) from SMILES strings and…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for30
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Use when segmenting top-down field or UAV RGB images of crops (sugar beet, PhenoBench-style) into soil / crop / weed semantics plus crop-plant and crop-leaf…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for32
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Use when segmenting the hippocampus into anterior and posterior parts in small 3-D T1-weighted brain MRI crops (Medical Segmentation Decathlon Task04) from a…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark
beita6969
Index of the 23 discipline skills (FoR30-FoR52) that mirror the disciplines of the companion ScienceClaw-Eval benchmark: find which discipline skill fits a…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for35
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Use when forecasting monthly tourism, visitor or other seasonal business and service series (Monash Tourism Monthly, 24-month horizon, period 12) from each…
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Cite this page
skill-creator. Agent Mart. https://agentmart.dev/skills/beita6969-skill-creator (last updated 2026-10-24)