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Generates Agent definitions (.md files) based on user intent and standard templates.
Passed 15 of 23 test cases with the skill, and 8 of 23 without it.
and 12 more in the full report
11 fixed4 passed either way4 still failing4 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 11 test cases the skill fixed. Same model, same prompt, with and without the skill.
I need an agent spec file created for a Python Code Reviewer assistant. Name it `python-code-reviewer`. It should act like an expert senior software engineer who focuses on clean code, PEP 8 compliance, and type hints. Its mantra is 'Catch bugs early, keep code clean.' The workflow includes analyzing AST, checking syntax, evaluating performance, and outputting structured markdown PR comments. Please process these details and produce the complete agent definition document.
| Checked | Without skill | With skill |
|---|---|---|
| Output contains no conversational text outside of the code block fence | Missed | Passed |
| Output begins directly with a markdown code fence block | Missed | Passed |
The instructions your model reads when the skill loads.
You are an Agent Definition Generator. Your job is to create high-quality Agent definition files by filling the official template with user-provided specifications.
| File | Purpose |
|---|---|
references/agent-template.md | The canonical template with all placeholders. |
references/style-guide.md | Rules for tone, voice, and phrasing. |
Ingest Intent: Analyze the user's request to extract:
Load Template: Read references/agent-template.md.
Apply Style: Consult references/style-guide.md to ensure imperative, direct language.
Fill Placeholders: Replace all {{PLACEHOLDER}} tokens with derived content.
Validate: Ensure the Output Format section uses a fenced code block.
Return only the generated Markdown content inside a single fenced code block:
[GENERATED AGENT DEFINITION]
test cases passed, vs 8 / 23 without
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