본문으로 건너뛰기
cccskills
무료GitHub에 공개

release-planning

Build a velocity-based release roadmap with risk buffers. Use when the user says "release plan", "when will we ship", "plan the next release", "map sprints to milestones", "estimate our release date", "how many sprints until done", or wants to translate a backlog into a delivery timeline - even if they don't say "release planning". Based on "Agile Estimating and Planning" by Mike Cohn (velocity, story points, cone of uncertainty, risk buffers).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(1)

  • SKILL.md5.4 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Overview

Based on "Agile Estimating and Planning" by Mike Cohn. The core insight: release dates are not commitments - they are probabilistic forecasts. Velocity is a lagging indicator that gets more reliable over time (the cone of uncertainty narrows). A good release plan gives a date range, not a single date, and explicitly buffers for unknowns. Single-date commitments made from a backlog on day one are fiction.

Workflow

Step 1: Establish velocity baseline

Ask the user for sprint velocity data. You need at least 3 sprints of history for a meaningful average.

Sprint | Story Points Completed
-------|----------------------
S-1    | [number]
S-2    | [number]
S-3    | [number]

Calculate:

  • Average velocity: sum / number of sprints
  • Velocity range: min to max (this defines your planning range)

If no historical data exists, flag this: "No velocity history means your first release plan has a high cone of uncertainty. Revisit after 2-3 sprints."

Step 2: Size the remaining backlog

Ask for the current backlog in story points. If the backlog is not estimated, do not attempt to generate a plan - ask the user to size the top items first.

Group the backlog:

  • Must have (P0): work required for the release to ship
  • Should have (P1): high-value, included if time permits
  • Nice to have (P2): deferred if velocity is lower than expected

Step 3: Calculate the release forecast

Using the velocity range from Step 1:

Optimistic date:  P0 points / max velocity = [N] sprints
Realistic date:   P0 points / avg velocity = [N] sprints
Conservative date: (P0 + P1 points) / min velocity = [N] sprints

Convert sprints to calendar dates using sprint length (ask user: 1-week, 2-week, or 3-week sprints?).

Output format:

RELEASE FORECAST - [your program]
==================================
Optimistic:   Ship by [date] (P0 scope only, best-case velocity)
Realistic:    Ship by [date] (P0 scope, average velocity)
Conservative: Ship by [date] (P0+P1 scope, worst-case velocity)

Recommended commitment: [realistic date] with [conservative date] as contingency

Step 4: Apply risk buffers

Cohn's rule: buffer 20% for unknowns if the team is mature and the codebase is known. Buffer up to 50% for:

  • New team (< 3 sprints together)
  • Greenfield build with no precedent
  • External dependencies not yet confirmed
  • Compliance, security, or legal review required

Add the buffer to the realistic estimate:

Buffered release date = realistic date + (realistic duration × buffer %)

Explicitly state what the buffer covers:

  • "[X]% buffer for [integration risk with third-party API / new team ramp-up / unknown legacy behavior]"

Step 5: Identify sprint-by-sprint milestones

Break the release into checkpoints. Use Cohn's planning horizon principle: plan in detail for the next 1-2 sprints, rough milestones for the rest.

SPRINT MILESTONES
Sprint 1-2: [specific deliverables - detailed]
Sprint 3-4: [milestone checkpoint - e.g., "core feature complete, integration testing starts"]
Sprint 5:   [scope decision point - P1 items in or out based on velocity trend]
Sprint 6:   [release candidate, regression, final go/no-go]

Step 6: Define the go/no-go criteria

State explicitly what must be true on the release date for the team to ship:

  • P0 stories: all accepted
  • Critical defects: zero Sev 1, fewer than [N] Sev 2
  • Performance: [metric] meets [threshold]
  • External dependencies: [list] confirmed resolved

Anti-Patterns

1. Committing to a single date from day one Bad: "We will ship on March 15th" based on a rough backlog estimate. Good: "Our realistic forecast is March 15th ± 2 sprints. We will tighten this after Sprint 3."

2. Planning without velocity data Bad: Generating a release date when the team has never shipped together. Good: Flag the uncertainty, provide a range 2x wider than normal, revisit after 3 sprints.

3. Forgetting to account for interrupt work Bad: Planning every story point of velocity for feature work. Good: Reserve 15-20% of velocity for bugs, support escalations, and unplanned work - especially for teams with external customers.

4. No scope buffer - only time buffer Bad: Fixed scope + fixed date with only a time buffer. Good: Designate P1 items as scope buffer. If velocity is low, cut P1 - don't extend the date.

5. Milestones too far apart Bad: "Done by Q3" with no intermediate checkpoints. Good: A milestone every 2-3 sprints so you detect drift early, not at the end.

Quality Checklist

  • Velocity baseline uses at least 3 sprints of data (or uncertainty is flagged)
  • Forecast includes optimistic, realistic, and conservative dates - not a single date
  • Risk buffer is sized and labeled (what it covers, not just a percentage)
  • Backlog is divided into P0 / P1 / P2 for scope flexibility
  • Sprint-by-sprint milestones defined for at least the first half of the release
  • Go/no-go criteria are explicit and measurable

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Rate any product, feature, or experience on the 11-star scale (Brian Chesky's Airbnb thought experiment). Use when user says "rate this experience", "11-star", "star rating", "experience audit", "how good is this", "experience rating", "product audit", "quality assessment", or wants to evaluate product quality and identify improvement paths. Also trigger when user wants to benchmark a feature, assess where a product stands, or map out what "great" looks like - even if they don't explicitly say "11-star".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

qa-aman/claude-skills212026년 10월 19일 업데이트

Generate A/B copy variants grounded in Eugene Schwartz's awareness and market-sophistication stages and John Caples' tested-headline discipline. Every variant declares its angle, the awareness stage it targets, and a falsifiable hypothesis, and the skill recommends which pair to test first and what delta counts as signal. Use when the user says "A/B test this", "write variants", "give me options", "test different angles", "copy variants", "ab copy", "test this headline", "multiple versions", "which version is better", or wants to test copy before publishing. For reviewing copy that already exists, see copy-review. For sample size and stopping rules, see growth-experiment. For diagnosing a page rather than its words, see page-cro. For full paid ad sets by platform, see ad-campaign-writer.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

qa-aman/claude-skills212026년 10월 19일 업데이트

Design statistically rigorous experiments to test data science hypotheses. Use when the user says "design an A/B test", "run an experiment", "test this hypothesis", "is this difference significant", "how many samples do I need", "randomized controlled trial", "causal inference", "uplift test", "holdout group", "significance test", "power calculation", "avoid p-hacking", or needs to determine whether an observed effect is real before making a product or model decision. For lean build-measure-learn product experiments without the statistics, use experiment-design instead.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

qa-aman/claude-skills212026년 10월 19일 업데이트

Write measurable acceptance criteria for requirements or user stories. Use when the user says "write acceptance criteria", "definition of done", "how do we test this", "fit criteria", "given when then", "Gherkin scenarios", "what does done look like", "testable conditions", "how will we know this works" - even if they don't explicitly say "acceptance criteria".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

qa-aman/claude-skills212026년 10월 19일 업데이트

Build a strategic account plan for winning, retaining, or expanding a named account. Use when the user says "build an account plan", "strategic account planning", "how do I grow this account", "account expansion strategy", "whitespace analysis", "QBR prep", "key account review", "map the stakeholders in this account", "land and expand plan", "how do I break into [company]", or wants a structured strategy for a specific account.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

qa-aman/claude-skills212026년 10월 19일 업데이트

Write paid ad copy for LinkedIn, Google, Meta, and YouTube. Produces multiple variants per platform, each targeting a different Eugene Schwartz awareness level and Cialdini persuasion principle. Use when the user asks for ad copy, ad variants, "write LinkedIn ads", Google ads, Meta ads, paid social copy, ad headlines, or wants creative for a paid campaign. Reads brand voice, ICP, and positioning from knowledge/. For organic social posts, see linkedin-post or social-calendar. For the landing page the ad points at, see landing-page-writer. For testing variants, see ab-copy-writer.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

qa-aman/claude-skills212026년 10월 19일 업데이트

qa-aman의 스킬 모두 보기

이 스킬의 문제 신고