Install
$ agentstack add skill-capawesome-team-skills-skill-creator ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Skill Authoring Procedure
Follow these steps to generate a skill that adheres to the agentskills.io specification and progressive disclosure principles.
Step 1: Initialize and Validate Metadata
- Define a unique
name: 1-64 characters, lowercase, numbers, and single hyphens only. - Draft a
description: Max 1,024 characters, written in the third person, including negative triggers. - Execute Validation Script: Run the validation script to ensure compliance before proceeding:
python3 scripts/validate-metadata.py --name "[name]" --description "[description]"
- If the script returns an error, self-correct the metadata based on the
stderroutput and re-run until successful.
Step 2: Structure the Directory
- Create the root directory using the validated
name. - Initialize the following subdirectories:
scripts/: For tiny CLI tools and deterministic logic.references/: For flat (one-level deep) context like schemas or API docs.assets/: For output templates, JSON schemas, or static files.
- Ensure no human-centric files (README.md, INSTALLATION.md) are created.
Step 3: Draft Core Logic (SKILL.md)
- Use the template in
assets/skill-template.mdas the starting point. - Write all instructions in the third-person imperative (e.g., "Extract the text," "Run the build").
- Enforce Progressive Disclosure:
- Keep the main logic under 500 lines.
- If a procedure requires a large schema or complex rule set, move it to
references/. - Command the agent to read the specific file only when needed: "Read references/api-spec.md to identify the correct endpoint."
Step 4: Identify and Bundle Scripts
- Identify "fragile" tasks (regex, complex parsing, or repetitive boilerplate).
- Outline a single-purpose script for the
scripts/directory. - Ensure the script uses standard output (stdout/stderr) to communicate success or failure to the agent.
Step 5: Final Logic Validation
- Review the
SKILL.mdfor "hallucination gaps" (points where the agent is forced to guess). - Verify all file paths are relative and use forward slashes (
/). - Cross-reference the final output against
references/checklist.md.
Error Handling
- Metadata Failure: If
scripts/validate-metadata.pyfails, identify the specific error (e.g., "STYLE ERROR") and rewrite the field to remove first/second person pronouns. - Context Bloat: If the draft exceeds 500 lines, extract the largest procedural block and move it to a file in
references/.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: capawesome-team
- Source: capawesome-team/skills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.