Skill WriterCAUTION
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Overview
Tensors and Dynamic neural networks in Python with strong GPU acceleration
fa50ad16b062OBSERVED · 2026-10-27Install
Commands as the repository documents them. They are shown, not run.
pip install package-name
Host compatibility
What the documentation claims. We have not run a compatibility test.
| Host | Status | Notes |
|---|---|---|
| claude-code | mentioned |
What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
---
name: skill-writer
description: Guide users through creating Agent Skills for Claude Code. Use when the user wants to create, write, author, or design a new Skill, or needs help with SKILL.md files, frontmatter, or skill structure.
---
# Skill Writer
This Skill helps you create well-structured Agent Skills for Claude Code that follow best practices and validation requirements.
## When to use this Skill
Use this Skill when:
- Creating a new Agent Skill
- Writing or updating SKILL.md files
- Designing skill structure and frontmatter
- Troubleshooting skill discovery issues
- Converting existing prompts or workflows into Skills
## Instructions
### Step 1: Determine Skill scope
First, understand what the Skill should do:
1. **Ask clarifying questions**:
- What specific capability should this Skill provide?
- When should Claude use this Skill?
- What tools or resources does it need?
- Is this for personal use or team sharing?
2. **Keep it focused**: One Skill = one capability
- Good: "PDF form filling", "Excel data analysis"
- Too broad: "Document processing", "Data tools"
### Step 2: Choose Skill location
Determine where to create the Skill:
**Personal Skills** (`~/.claude/skills/`):
- Individual workflows and preferences
- Experimental Skills
- Personal productivity tools
**Project Skills** (`.agents/skills/`; `.claude/skills` links here for Claude Code):
- Team workflows and conventions
- Project-specific expertise
- Shared utilities (committed to git)
### Step 3: Create Skill structure
Create the directory and files:
```bash
# Personal
mkdir -p ~/.claude/skills/skill-name
# Project
mkdir -p .agents/skills/skill-name
```
For multi-file Skills:
```
skill-name/
├── SKILL.md (required)
├── reference.md (optional)
├── examples.md (optional)
├── scripts/
│ └── helper.py (optional)
└── templates/
└── template.txt (optional)
```
### Step 4: Write SKILL.md frontmatter
Create YAML frontmatter with required fields:
```yaml
---
name: skill-name
description: Brief description of what this does and when to use it
---
```
**Field requirements**:
- **name**:
- Lowercase letters, numbers, hyphens only
- Max 64 characters
- Must match directory name
- Good: `pdf-processor`, `git-commit-helper`
- Bad: `PDF_Processor`, `Git Commits!`
- **description**:
- Max 1024 characters
- Include BOTH what it does AND when to use it
- Use specific trigger words users would say
- Mention file types, operations, and context
**Optional frontmatter fields**:
- **allowed-tools**: Restrict tool access (comma-separated list)
```yaml
allowed-tools: Read, Grep, Glob
```
Use for:
- Read-only Skills
- Security-sensitive workflows
- Limited-scope operations
### Step 5: Write effective descriptions
The description is critical for Claude to discover your Skill.
**Formula**: `[What it does] + [When to use it] + [Key triggers]`
**Examples**:
✅ **Good**:
```yaml
description: Extract text and tables from PDF files, fill forms, merge documents. Use when working with PDF files or when the user mentions PDFs, forms, or document extraction.
```
✅ **Good**:
```yaml
description: Analyze Excel spreadsheets, create pivot tables, and generate charts. Use when working with Excel files, spreadsheets, or analyzing tabular data in .xlsx format.
```
❌ **Too vague**:
```yaml
description: Helps with documents
description: For data analysis
```
**Tips**:
- Include specific file extensions (.pdf, .xlsx, .json)
- Mention common user phrases ("analyze", "extract", "generate")
- List concrete operations (not generic verbs)
- Add context clues ("Use when...", "For...")
### Step 6: Structure the Skill content
Use clear Markdown sections:
```markdown
# Skill Name
Brief overview of what this Skill does.
## Quick start
Provide a simple example to get started immediately.
## Instructions
Step-by-step guidance for Claude:
1. First step with clear action
2. Second step with expected outcome
3. Handle edge cases
## Examples
Show concrete usage examples with code or commands.
## Best practices
- Key conventions to follow
- Common pitfalls to avoid
- When to use vs. not use
## Requirements
List any dependencies or prerequisites:
```bash
pip install package-name
```
## Advanced usage
For complex scenarios, see [reference.md](reference.md).
```
### Step 7: Add supporting files (optional)
Create additional files for progressive disclosure:
**reference.md**: Detailed API docs, advanced options
**examples.md**: Extended examples and use cases
**scripts/**: Helper scripts and utilities
**templates/**: File templates or boilerplate
Reference them from SKILL.md:
```markdown
For advanced usage, see [reference.md](reference.md).
Run the helper script:
\`\`\`bash
python scripts/helper.py input.txt
\`\`\`
```
### Step 8: Validate the Skill
Check these requirements:
✅ **File structure**:
- [ ] SKILL.md exists in correct location
- [ ] Directory name matches frontmatter `name`
✅ **YAML frontmatter**:
- [ ] Opening `---` on line 1
- [ ] Closing `---` before content
- [ ] Valid YAML (no tabs, correct indentation)
- [ ] `name` follows naming rules
- [ ] `description` is specific and < 1024 chars
✅ **Content quality**:
- [ ] Clear instructions for Claude
- [ ] Concrete examples provided
- [ ] Edge cases handled
- [ ] Dependencies listed (if any)
✅ **Testing**:
- [ ] Description matches user questions
- [ ] Skill activates on relevant queries
- [ ] Instructions are clear and actionable
### Step 9: Test the Skill
1. **Restart Claude Code** (if running) to load the Skill
2. **Ask relevant questions** that match the description:
```
Can you help me extract text from this PDF?
```
3. **Verify activation**: Claude should use the Skill automatically
4. **Check behavior**: Confirm Claude follows the instructions correctly
### Step 10: Debug if needed
If Claude doesn't use the Skill:
1. **Make description more specific**:
- Add trigger words
- Include filTrust audit
CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | WARN |
| L1 | Static analysis of the code | PASS |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (5)
.claude/skills
.dockerignore
.github/ci_commit_pins/triton.txt
AGENTS.md
docs/requirements.txt
Gates applied: no_behavioural_pass.
fa50ad16b062full audit observations/trust-audit/skill/pytorch__skill-writer.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-27 | fa50ad16b062 | CAUTION | B | 89 | first audit |
Questions
What does the skill-writer — pytorch/pytorch skill do?
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Is skill-writer — pytorch/pytorch safe to install?
With care. The audit graded it B (89/100) and found 5 things worth knowing before you trust this skill, listed below with the exact line each was found on.
What can skill-writer — pytorch/pytorch access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
Which assistants does skill-writer — pytorch/pytorch work with?
Its documentation mentions claude-code. That is what the text claims, not a compatibility test we ran.
How current is this page?
The grade is for one exact copy of the source (fa50ad16b062), read on 2026-10-27. The repository is watched, and a new audit runs when it changes — this is the first audit.
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Shows this page's audit result and links back to it. It updates when the audit does.
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