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GitHub Stars
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Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.
Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill getsentry/warden --skill agent-prompt- SKILL.md1.7 KB
Overview
This skill is a practical reference for writing effective agent prompts and building Warden skills. It codifies prompt structure, evaluation criteria, and architecture guidance so creators can produce reliable, reviewable prompts. Use it to speed up authoring, review quality, and align prompts with Warden's operational model.
How this skill works
The skill inspects prompt structure, role statements, task descriptions, and severity definitions to ensure clarity and safety. It checks for common anti-patterns, enforces structured output formats, and recommends model-specific optimizations for Claude 4.x. It also maps prompts to agentic patterns when tool use or multi-step reasoning is required.
When to use it
- Creating a new agent prompt or skill for Warden
- Reviewing or auditing existing prompts for clarity and safety
- Designing structured JSON outputs or integrating tools
- Optimizing prompts for Claude 4.x or similar models
- Training reviewers on prompt engineering best practices
Best practices
- Start with a concise role statement and a clear single-sentence task objective
- Define concrete acceptance criteria and severity levels tied to impact
- Prefer structured, example-driven output schemas over free-form text
- Avoid vague or open-ended instructions; constrain scope and expected steps
- Explicitly separate system-level context from user-facing instructions
- Test prompts with representative edge cases and refine using model feedback
Example use cases
- Authoring a skill that inspects source code for security or style issues
- Converting a manual checklist into an automated reviewer with tool calls
- Creating a prompt that returns a validated JSON report for downstream tooling
- Reviewing a prompt that chains tools and needs guardrails to prevent hallucination
- Adapting a prompt to leverage Claude 4.x strengths like instruction-following and long context
FAQ
Tie each severity to clear impact criteria and remediation steps so reviewers and agents can rank findings consistently.
Should outputs be free-form or structured?
Prefer structured JSON for machine consumption and include a short human summary when helpful; provide a schema and examples.