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Project-specific test strategy. Defines what to verify beyond generic dogfooding: domain-specific checks, content rendering, build validation, and error boundaries. Use alongside the dogfood skill which provides the methodology.
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Basé sur la classification professionnelle SOC
| name | test-strategy |
| description | Project-specific test strategy. Defines what to verify beyond generic dogfooding: domain-specific checks, content rendering, build validation, and error boundaries. Use alongside the dogfood skill which provides the methodology. |
| allowed-tools | ["Bash","Read","Grep","Glob"] |
What to check on this project, on top of dogfood's generic exploratory testing. This skill defines the WHAT. The dogfood skill defines the HOW.
{CONFIGURE: Stack context — tech stack, routing structure, content architecture}
At each page, inspect network requests:
agent-browser network requests --status 4xx --session {SESSION}
agent-browser network requests --status 5xx --session {SESSION}
Flag:
/nonexistent-page renders custom 404 with working nav back to homeTest at desktop (1280x720) and mobile (375x812):
Run before or after browser testing to catch non-visual issues:
Report pass/fail for each. If any check fails, diagnose but do NOT auto-fix.
{CONFIGURE: Known gotchas and edge cases}
When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' or 'optimize for Claude/Gemini.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema-markup.
Open two files side by side in VSCodium diff view. Use when comparing original vs modified, before vs after, or any two files.
When the user wants to plan a content strategy, decide what content to create, or figure out what topics to cover. Also use when the user mentions "content strategy," "what should I write about," "content ideas," "blog strategy," "topic clusters," "content planning," "editorial calendar," "content marketing," "content roadmap," "what content should I create," "blog topics," "content pillars," or "I don't know what to write." Use this whenever someone needs help deciding what content to produce, not just writing it. For writing individual pieces, see copywriting. For SEO-specific audits, see seo-audit. For social media content specifically, see social-content.
When the user wants to write, rewrite, or improve marketing copy for any page — including homepage, landing pages, pricing pages, feature pages, about pages, or product pages. Also use when the user says "write copy for," "improve this copy," "rewrite this page," "marketing copy," "headline help," "CTA copy," "value proposition," "tagline," "subheadline," "hero section copy," "above the fold," "this copy is weak," "make this more compelling," or "help me describe my product." Use this whenever someone is working on website text that needs to persuade or convert. For email copy, see email-sequence. For popup copy, see popup-cro. For editing existing copy, see copy-editing.
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.
First-run onboarding for a new project. Scans for unfilled {CONFIGURE:} placeholders, asks project-specific questions, fills them in, and logs decisions.