f3b9d008fe
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>
54 lines
2.5 KiB
Markdown
54 lines
2.5 KiB
Markdown
---
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name: retro-analysis
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description: "Analyse sprint delivery data and produce a structured retrospective brief. Use when asked to run a retrospective, analyse sprint data, prepare a retro brief, or turn sprint metrics into discussion prompts. Produces a data-grounded retrospective brief with completion stats, pattern analysis, Start/Stop/Continue prompts, and one concrete experiment for next sprint."
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---
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# Retrospective Analysis Skill
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Generate a data-grounded retrospective brief that separates facts from feelings, so the team spends retro time on solutions rather than debating what happened.
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## Required Inputs
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Ask the user for these if not provided:
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- **Sprint tickets: planned vs. completed**
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- **Carry-over tickets and reasons** (if known)
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- **Tickets reopened after closing** (quality signal)
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- **Any incidents or unplanned work** (scope creep signal)
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- **Sprint velocity vs. historical average** (trend context)
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## Process
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1. Calculate: completion rate, carry-over rate, unplanned work percentage
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2. Identify patterns: which ticket types were most likely to carry over? Which caused blockers?
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3. Note any process or communication breakdowns visible in the data
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4. Prepare 3 "Start / Stop / Continue" prompts based on the data — not generic, specific to this sprint
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5. Suggest 1 concrete experiment for the next sprint based on the biggest friction point
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6. **Validate** — Confirm each prompt is specific to this sprint (not a recycled generic prompt), and that the recommended experiment is concrete and measurable
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## Output Structure
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### Sprint [Number] Retrospective Brief
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**By the Numbers:**
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- Planned: [n] tickets | Completed: [n] | Carry-over: [n] | Completion rate: [%]
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- Unplanned work: [n] tickets ([%] of capacity)
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- Velocity: [points] vs. [average] average
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**What the Data Suggests:**
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[2-3 observations grounded in the numbers above]
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**Discussion Prompts:**
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- Start: [specific prompt based on this sprint's data]
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- Stop: [specific prompt based on this sprint's data]
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- Continue: [specific prompt based on this sprint's data]
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**Suggested Experiment for Next Sprint:**
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[One concrete, testable process change — with a specific success metric]
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## Quality Checks
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- [ ] Each Start/Stop/Continue prompt names a specific behaviour, not a vague category
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- [ ] The recommended experiment is testable in one sprint
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- [ ] Carry-over analysis identifies the ticket type or cause, not just the count
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- [ ] Data observations don't assign blame — they describe patterns
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- [ ] Velocity trend is mentioned in context (is this a one-off or a pattern?)
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