Improve api-proposal skill using skill-creator analysis#125494
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eiriktsarpalis merged 1 commit intomainfrom Mar 17, 2026
Merged
Improve api-proposal skill using skill-creator analysis#125494eiriktsarpalis merged 1 commit intomainfrom
eiriktsarpalis merged 1 commit intomainfrom
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Apply improvements to the api-proposal skill informed by the Anthropic skill-creator skill's methodology for critiquing and optimizing skills. Changes: - Optimize description with trigger phrases (api-suggestion, api-needs-work) and a DO NOT USE FOR boundary to reduce false triggers against sibling skills - Remove generic slop warning (gh pr review --approve) that was not specific to this skill's purpose; reframe prototype-first warning with reasoning - Add Common Pitfalls section warning about LLM-specific failure modes: verbosity creep, invented scenarios, raw ref dumps, non-compilable examples - Restructure proposal template from 10 sections to 5, matching the format used in real api-approved issues (Background, API Proposal, API Usage, Alternative Designs, Risks); fold related issues and scope into Background, design decisions and open questions into Alternative Designs, prototype link into API Proposal section Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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Pull request overview
This PR updates the .github/skills/api-proposal skill documentation to better match how api-suggestion/api-approved proposals are typically structured and reviewed in dotnet/runtime, emphasizing prototype-backed design and adding LLM-specific drafting guidance.
Changes:
- Expands the skill trigger description and clarifies intended/non-intended use cases.
- Adds a “Common Pitfalls” section focused on common LLM proposal failure modes.
- Restructures the proposal template sections to align more closely with the current API issue template (Background, API Proposal, Usage, Alternative Designs, Risks) and adds guidance for linking related issues and prototypes.
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stephentoub
approved these changes
Mar 16, 2026
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Apply skill-creator methodology to improve the api-proposal skill: optimize description triggers, remove generic warnings, add LLM anti-patterns section, and restructure proposal template to match real api-approved issue format.