Milestone Review logo

Milestone Review

CommunityPopular
Donchitos
milestone-review

Milestone progress review — completeness, quality metrics, risk, go/no-go recommendation. At checkpoints or before a deadline.

Overview

PublisherDonchitos
RepositoryClaude-Code-Game-Studios
Skill namemilestone-review
Stars
25.8K
Forks
3.7K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Donchitos on GitHub. Read the source before you install it.

Installation

Install the Milestone Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Donchitos/Claude-Code-Game-Studios/tree/main/.claude/skills/milestone-review
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Donchitos/Claude-Code-Game-Studios.git /tmp/Claude-Code-Game-Studios
mkdir -p .claude/skills
cp -r /tmp/Claude-Code-Game-Studios/.claude/skills/milestone-review .claude/skills/milestone-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Milestone Review in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Milestone Review on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Milestone Review is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

!bash "${CLAUDE_SKILL_DIR}/../../hooks/yaml-helper.sh" resolve_config --keys review_mode,automation,workflow

Resolved above — use as-is; --review overrides review_mode for this run. No block → defaults in .claude/docs/config-resolution.md.

Insufficient input — check this before producing any report

If the inputs this skill needs do not exist, the answer is "could not run" — not a filled-in report. Check first, and stop if the check fails.

  1. List the inputs this skill reads (data files, prior reports, profiler output, test results, registries, source code).
  2. For each, record FOUND or ABSENT — not "assumed present".
  3. If any input required for a section is ABSENT, that section is NOT ASSESSED — NO DATA. Do not estimate it, do not infer it from an adjacent artifact, and do not leave a mandated cell to be filled by whoever reads the template next.
  4. If every required input is ABSENT, stop and report NOT ASSESSED — NO DATA as the whole verdict, naming what was missing and which skill produces it.

A verdict of NOT ASSESSED is a success. It is the correct, useful answer to "what does the data say?" when there is no data. The failure mode this prevents is specific and has been observed in practice: report templates whose verdict enum had no "could not run" state produced false clean passes — an asset audit returning COMPLIANT on a project with no assets and no standards, and a performance profile reporting ">99% headroom against a 16.67ms budget" with zero profiler data and no budget ever set.

Absence of evidence is never evidence of absence. A scan that finds no matches because there are no files to scan has not verified anything. Say which of the two happened — a reader cannot tell from a green result.


Phase 0: Parse Arguments

Extract the milestone name (current or a specific name).

See .claude/docs/director-gates.md for the full check pattern. Individual gate definitions live in .claude/docs/director-gates/[gate-id].md — the spawned agent reads its own gate file; do not read it in the parent session.

Every AskUserQuestion call follows .claude/docs/automation-modes.md (collaborative asks always · guided major-only · autonomous logs and proceeds; automation_always_ask categories always prompt).


Phase 1: Load Milestone Data

Read the milestone definition from production/milestones/ if it exists. If the argument is current, use the most recently modified milestone file.

No skill writes production/milestones/ — definitions are authored by hand from .claude/docs/templates/milestone-definition.md, so most projects have none. When the directory is absent or empty, say so and review against the sprint reports alone; do not fabricate a definition. Take care with current: this skill writes its own output as [milestone-name]-review.md, so a most-recently-modified match can be a previous review rather than a definition. Skip files ending -review.md when selecting.

Gather the sprint reports for sprints within this milestone from production/sprints/. Establish the denominator (glob them, count N), then scan the sections a milestone review actually aggregates rather than reading each report whole:

Grep pattern="^## (Sprint Goal|Capacity|Tasks|Carryover|Risks|Progress|Burndown Assessment|Emerging Risks|Definition of Done)" glob="production/sprints/sprint-*.md" output_mode="content" -A 12

These alternates are copied from /sprint-plan's emitted headings — keep them in sync with it, not with what a milestone review wishes existed. The previous pattern asked for Summary|Goal|Velocity|Completed|Blockers| Retrospective, none of which /sprint-plan writes (it emits ## Sprint Goal, not ## Goal). Only Carryover matched — and that was the trap: a non-zero match count meant the zero-match escape hatch below could never fire, so every milestone review silently aggregated carryover tables and nothing else while reporting full coverage.

Full-read a single sprint report when its scanned sections point outside themselves, or when it matched nothing — a zero-match report predates the template and must be read, never silently dropped from the milestone's history. Report any sprint that contributed nothing: a milestone summary that quietly omits a sprint understates the work and the slippage both.

Blocked stories — the Blocked table and the blocked story count passed to PR-MILESTONE — are not in the sprint reports' scanned sections. Read them where they are recorded: the status: blocked stories in production/sprint-status.yaml (with their blocker field) and, for stories outside that sprint, one grep:

Grep pattern="^> \*\*Status\*\*: Blocked|BLOCKED:" glob="production/epics/**/story-*.md" output_mode="content"

Each blocked story goes in the Blocked table under the feature its epic folder implements, with its blocker (the yaml blocker field or the story's BLOCKED: note). With no story files and no sprint-status.yaml, the Blocked table and the blocked story count are NOT ASSESSED — NO DATA, not zero.


Phase 2: Scan Codebase Health

  • Scan for TODO, FIXME, HACK markers that indicate incomplete work
  • Count open bugs by severity for Quality Metrics from production/qa/bugs/ (one grep of the **Severity** and **Status** lines, as /bug-triage does); with no bug files, the bug lines are NOT ASSESSED — NO DATA, not zero
  • Check the risk register at production/risk-register/ if it exists (hand-authored from .claude/docs/templates/risk-register-entry.md; no skill writes it, so absence is normal — note it rather than skipping risk assessment silently)

Phase 3: Generate the Milestone Review

markdown
# Milestone Review: [Milestone Name]

## Overview
- **Target Date**: [Date]
- **Current Date**: [Today]
- **Days Remaining**: [N]
- **Sprints Completed**: [X/Y]

## Feature Completeness

### Fully Complete
Only a feature whose Status is `Complete` goes here or counts toward the completion percentage; a Deferred feature stays in its denominator, named with the milestone it moved to.

| Feature | Acceptance Criteria | Test Status |
|---------|-------------------|-------------|

### Partially Complete
| Feature | % Done | Remaining Work | Risk to Milestone |
|---------|--------|---------------|------------------|

### Blocked
A started feature whose stories are Blocked goes here, not under Partially
Complete — name the blocker, so the review says why it stalled, not only that
the count moved.

| Feature | Blocked Stories | Blocker | Next Action / Owner |
|---------|----------------|---------|---------------------|

### Not Started
| Feature | Priority | Can Cut? | Impact of Cutting |
|---------|----------|----------|------------------|

## Quality Metrics
- **Open S1 Bugs**: [N] -- [List]
- **Open S2 Bugs**: [N]
- **Open S3 Bugs**: [N]
- **Test Coverage**: [X%]
- **Performance**: [Within budget? Details]

## Code Health
- **TODO count**: [N across codebase]
- **FIXME count**: [N]
- **HACK count**: [N]
- **Technical debt items**: [List critical ones]

## Risk Assessment
| Risk | Status | Impact if Realized | Mitigation Status |
|------|--------|-------------------|------------------|

## Velocity Analysis
- **Planned vs Completed** (across all sprints): [X/Y tasks = Z%]
- **Trend**: [Improving / Stable / Declining]
- **Adjusted estimate for remaining work**: [Days needed at current velocity]

## Scope Recommendations
### Protect (Must ship with milestone)
- [Feature and why]

### At Risk (May need to cut or simplify)
- [Feature and risk]

### Cut Candidates (Can defer without compromising milestone)
- [Feature and impact of cutting]

## Go/No-Go Assessment

**Recommendation**: [NOT ASSESSED / GO / CONDITIONAL GO / NO-GO]

**Conditions** (if conditional):
- [Condition 1 that must be met]
- [Condition 2 that must be met]

**Rationale**: [Explanation of the recommendation]

## Action Items
| # | Action | Owner | Deadline |
|---|--------|-------|----------|

Phase 3b: Producer Risk Assessment

Review mode check — apply before spawning PR-MILESTONE:

  • solo → skip. Note: "PR-MILESTONE skipped — Solo mode." Present the Go/No-Go section without a producer verdict.
  • lean → skip (not a PHASE-GATE). Note: "PR-MILESTONE skipped — Lean mode." Present the Go/No-Go section without a producer verdict.
  • full → spawn as normal.

Before generating the Go/No-Go recommendation, spawn producer via Agent using gate PR-MILESTONE (.claude/docs/director-gates/pr-milestone.md).

Pass: milestone name and target date, current completion percentage, blocked story count, velocity data from sprint reports (if available), list of cut candidates.

Present the producer's assessment inline within the Go/No-Go section. The producer's verdict (ON TRACK / AT RISK / OFF TRACK) informs the overall recommendation.

If OFF TRACK, use AskUserQuestion before generating the recommendation:

  • Prompt: "Producer verdict: OFF TRACK. The milestone is in jeopardy. This review will recommend NO-GO. How do you want to proceed?"
  • Options:
    • [A] Accept NO-GO — generate the full review with that recommendation
    • [B] Override to CONDITIONAL GO — I'll document the accepted risks myself
    • [C] Stop — I want to address blockers before generating the review

If AT RISK, use AskUserQuestion:

  • Prompt: "Producer verdict: AT RISK. Milestone may slip. How should the Go/No-Go section be framed?"
  • Options:
    • [A] CONDITIONAL GO — include producer's conditions in the review
    • [B] NO-GO — conditions cannot be met in time
    • [C] GO — I accept the risk and want to proceed

If NOT ASSESSED: name the missing input — it is not ON TRACK, and never recommend GO on it. Supply the input and re-run PR-MILESTONE, or recommend NOT ASSESSED — or CONDITIONAL GO / NO-GO where the review's own findings call for one (the rank in .claude/docs/director-gates.md).

Do not issue a GO against an OFF TRACK verdict; issue CONDITIONAL GO only if the user explicitly selects [B] above.


Phase 4: Save Review

Present the review to the user.

Ask: "May I write this to production/milestones/[milestone-name]-review.md?"

If yes, write the file, creating the directory if needed. Verdict: COMPLETE — milestone review saved.

If no, stop here. Verdict: BLOCKED — user declined write.


Phase 5: Next Steps

  • Run /gate-check for a formal phase gate verdict if this milestone marks a development phase boundary.
  • Run /sprint-plan to adjust the next sprint based on the scope recommendations above (at workflow: minimal, which has no sprints, adjust the brief's build order instead).

Frequently asked questions

What does the Milestone Review AI skill do?

Milestone progress review — completeness, quality metrics, risk, go/no-go recommendation. At checkpoints or before a deadline.

Why use Milestone Review on TypingMind?

Because you install it once and use it with any model. Milestone Review is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Milestone Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Donchitos/Claude-Code-Game-Studios/tree/main/.claude/skills/milestone-review. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Milestone Review?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Milestone Review?

As many as you like. As long as a model supports skills, you can use Milestone Review with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Milestone Review AI skill free?

Yes. It is published on GitHub by Donchitos under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇