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feat: 100 skills milestone — 7 new skills + quality improvements across all 93

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New skills added:
- teaching-lesson-plan: structured lesson plans for any subject/audience/setting
- seo-content-brief: complete SEO briefs with intent, competitor gaps, and outline
- media-pitch: story-first journalist pitches with angle development framework
- change-management-plan: stakeholder analysis, comms strategy, adoption metrics
- workshop-facilitation-guide: activity instructions, decision protocols, facilitator moves
- sales-forecasting-model: pipeline model, scenario analysis, assumption log
- tax-planning-checklist: year-end tax planning across income, pension, CGT, reliefs

Quality improvements across all 93 existing skills:
- Standardised description format: "Verb the thing. Use when X. Produces Y."
- Added Required Inputs section to all skills missing it (prompts for missing info)
- Added Quality Checks section to all skills missing it (specific, not generic)
- Fixed broken multiline YAML descriptions
- Removed non-standard frontmatter keys (tool_integration, metadata blocks)

README updated to v6.0.0 with 100-skill count, new skill tables, and article series

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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2026-04-20 20:52:31 +01:00
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skills/ai-product-canvas/SKILL.md
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---
name: ai-product-canvas
description: Structures AI and ML product decisions including model selection, data requirements, evaluation frameworks, and responsible AI considerations. Use when building AI-powered features, evaluating LLM integrations, designing AI products, or assessing AI readiness. Triggers on "AI product", "LLM feature", "AI canvas", "build with AI", "AI integration", "AI-powered", "machine learning feature".
description: "Structure AI and ML product decisions with the rigour of any product decision. Use when building AI-powered features, evaluating LLM integrations, designing AI products, or assessing AI readiness. Produces a complete AI product canvas covering problem definition, model approach, data requirements, evaluation framework, UX design, responsible AI checklist, and launch monitoring plan."
---
# AI Product Canvas Skill
@@ -143,3 +143,19 @@ Before building, flag if any of these apply:
- Responsible AI checklist must be completed before launch, not after
- Include latency in success metrics — a 5-second AI response is often worse than no AI at all
- Recommend starting with a human-in-the-loop design and automating only when accuracy is proven
## Required Inputs
Ask the user for these if not provided:
- **Feature or product description** (what the AI is intended to do)
- **User problem** (what problem the AI is solving for users)
- **Available data** (what training/inference data exists)
- **ML/AI lead** (who owns the technical implementation)
## Quality Checks
- [ ] "Why AI?" is answered clearly (not "because we can")
- [ ] Minimum acceptable accuracy threshold is defined before build begins
- [ ] Fallback UX is specified for model failures or low-confidence outputs
- [ ] Responsible AI checklist is completed (not deferred to post-launch)
- [ ] Monitoring plan includes both model performance and user engagement metrics