--- name: deployment-frequency-tracker description: "Deployment frequency tracker: compute DORA metrics from git history, LLM identifies bottlenecks and improvement opportunities. Read-only. Trigger: /deploy-freq" trigger: /deploy-freq --- # /deploy-freq DORA metrics from local git history. No external API needed. ## What this is for - Deployment frequency, lead time, change failure rate, time to restore - Bottlenecks: long-running PRs, deployment batches, rollback patterns - **Read-only skill.** No CI changes, no deployment automation. ## PROTECTION RULE - never ~/.claude/ Read-only skill. Guard required if write mode added later. ## What You Must Do When Invoked During analysis, assign a confidence level to each finding: proven (confirmed by evidence), likely (strong signal, needs review), or suspected (weak signal). If `/deploy-freq -help` or `/deploy-freq -h` (without further arguments) is invoked: output the `## Usage` section unchanged and stop. Otherwise follow these steps in order, skipping none. ### Step 1 - Help check If invoked with `-help` or `-h`, output the `## Usage` section unchanged and stop. ### Step 2 - Clarify target Clarify `-ProjectDir`. Get confirmation. ### Step 3 - Scan ```powershell & "/scripts/dora-scan.ps1" -ProjectDir "" ``` ### Step 4 - Analysis Read each metric: - How does it compare to DORA benchmarks (elite/high/medium/low)? - What is the #1 bottleneck? - Are deploys risky (high change failure rate + low freq) or healthy? ### Step 5 - Write report File `deployment-frequency-report.md` in current working directory: 1. **Summary** - metrics vs DORA benchmarks, trend arrows. 2. **Bottleneck analysis** - blocking patterns with examples. 3. **Recommendations** - smaller batches, feature flags, faster CI, deployment automation. 4. **Open questions**. ### Step 6 - Summarize State report path, highlight the #1 improvement opportunity. ## Usage ``` /deploy-freq # interactive /deploy-freq # scan project /deploy-freq -help ```