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velocity-tracker
Track development velocity, cycle times, and identify trends for PM decision-making
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
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Track development velocity, cycle times, and identify trends for PM decision-making
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
Seed JSON configuration files into database. Use ONCE at BAZINGA session initialization, BEFORE spawning PM.
Database operations for BAZINGA orchestration system. This skill should be used when agents need to save or retrieve orchestration state, logs, task groups, token usage, or skill outputs. Replaces file-based storage with concurrent-safe SQLite database. Use instead of writing to bazinga/*.json files or docs/orchestration-log.md.
Analyzes codebase to find similar features, reusable utilities, and architectural patterns
Build complete agent prompts deterministically via Python script. Use BEFORE spawning any BAZINGA agent (Developer, QA, Tech Lead, PM, etc.).
Analyze existing tests to identify patterns, fixtures, and conventions before writing new tests
Assembles relevant context for agent spawns with prioritized ranking. Ranks packages by relevance, enforces token budgets with graduated zones, captures error patterns for learning, and supports configurable per-agent retrieval limits.
SOC 職業分類に基づく
| name | velocity-tracker |
| description | Track development velocity, cycle times, and identify trends for PM decision-making |
| version | 1.0.0 |
| allowed-tools | ["Bash","Read"] |
You are the velocity-tracker skill. When invoked, you analyze historical project data to provide quantitative metrics for PM decision-making.
Invoke this skill when:
Do NOT invoke when:
When invoked:
Use the Bash tool to run the pre-built tracking script.
On Unix/macOS:
bash .claude/skills/velocity-tracker/scripts/track.sh
On Windows (PowerShell):
pwsh .claude/skills/velocity-tracker/scripts/track.ps1
Cross-platform detection: Check if running on Windows (
$env:OScontains "Windows" orunamedoesn't exist) and run the appropriate script.
This script will:
bazinga/bazinga.db)bazinga/artifacts/{SESSION_ID}/skills/project_metrics.jsonbazinga/artifacts/{SESSION_ID}/skills/historical_metrics.jsonUse the Read tool to read the generated report:
bazinga/artifacts/{SESSION_ID}/skills/project_metrics.json
Extract key information:
current_run.velocity - Story points completedcurrent_run.percent_complete - Progress percentagetrends.velocity - Velocity trendwarnings - Any 99% rule violationsrecommendations - Action itemsReturn a concise summary to the calling agent:
Velocity Metrics:
- Current velocity: {velocity} story points (historical avg: {historical_avg})
- Trend: {improving/stable/declining}
- Cycle time: {avg_minutes} minutes average
- Completion: {percent}%
{If warnings exist:}
⚠️ Warnings:
- {warning 1}
- {warning 2}
Top Recommendations:
1. {recommendation 1}
2. {recommendation 2}
3. {recommendation 3}
Details saved to: bazinga/artifacts/{SESSION_ID}/skills/project_metrics.json
Scenario 1: Normal Progress Check
Input: PM agent requests velocity check after completing task group G002
Expected output:
Velocity Metrics:
- Current velocity: 12 story points (historical avg: 10.5)
- Trend: improving
- Cycle time: 45 minutes average
- Completion: 40%
Top Recommendations:
1. Current velocity exceeds historical average - good progress
2. Estimated remaining time: 3.5 hours
Details saved to: bazinga/artifacts/{SESSION_ID}/skills/project_metrics.json
Scenario 2: 99% Rule Violation Detected
Input: PM agent checks why task G003 is taking too long
Expected output:
Velocity Metrics:
- Current velocity: 8 story points (historical avg: 10.5)
- Trend: declining
- Cycle time: 125 minutes average
- Completion: 30%
⚠️ Warnings:
- 99% Rule Violation: Task G003 taking 3x longer than expected (135 min vs 45 min estimate)
Top Recommendations:
1. Escalate G003 to Tech Lead for investigation
2. Velocity below average - may need task breakdown
3. Database tasks pattern: taking 2.5x estimate
Details saved to: bazinga/artifacts/{SESSION_ID}/skills/project_metrics.json
If script fails:
bazinga/bazinga.db exists and contains PM stateIf no completed groups:
If historical data missing: