mohitagw15856
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>
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name, description
| name | description |
|---|---|
| retro-analysis | 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. |
Retrospective Analysis Skill
Generate a data-grounded retrospective brief that separates facts from feelings, so the team spends retro time on solutions rather than debating what happened.
Required Inputs
Ask the user for these if not provided:
- Sprint tickets: planned vs. completed
- Carry-over tickets and reasons (if known)
- Tickets reopened after closing (quality signal)
- Any incidents or unplanned work (scope creep signal)
- Sprint velocity vs. historical average (trend context)
Process
- Calculate: completion rate, carry-over rate, unplanned work percentage
- Identify patterns: which ticket types were most likely to carry over? Which caused blockers?
- Note any process or communication breakdowns visible in the data
- Prepare 3 "Start / Stop / Continue" prompts based on the data — not generic, specific to this sprint
- Suggest 1 concrete experiment for the next sprint based on the biggest friction point
- Validate — Confirm each prompt is specific to this sprint (not a recycled generic prompt), and that the recommended experiment is concrete and measurable
Output Structure
Sprint [Number] Retrospective Brief
By the Numbers:
- Planned: [n] tickets | Completed: [n] | Carry-over: [n] | Completion rate: [%]
- Unplanned work: [n] tickets ([%] of capacity)
- Velocity: [points] vs. [average] average
What the Data Suggests: [2-3 observations grounded in the numbers above]
Discussion Prompts:
- Start: [specific prompt based on this sprint's data]
- Stop: [specific prompt based on this sprint's data]
- Continue: [specific prompt based on this sprint's data]
Suggested Experiment for Next Sprint: [One concrete, testable process change — with a specific success metric]
Quality Checks
- Each Start/Stop/Continue prompt names a specific behaviour, not a vague category
- The recommended experiment is testable in one sprint
- Carry-over analysis identifies the ticket type or cause, not just the count
- Data observations don't assign blame — they describe patterns
- Velocity trend is mentioned in context (is this a one-off or a pattern?)