A proposed weekly rhythm for the Techies engineering team: developers submit a changelog and self-set targets, Claude Code audits GitHub to quantify performance, and achievement is tracked against target — all aligned to our AI-oriented SDLC.
What we are proposing and why.
Each developer submits a short weekly report combining a narrative changelog and self-set targets with a % achievement. In parallel, Claude Code automatically audits GitHub to produce objective metrics across all four KPI categories (productivity, quality, AI adoption, delivery). The developer's self-report and the machine audit sit side by side, giving us a fast, fair, weekly read on performance that is hard to game and cheap to run.
Changelog + targets + claimed % achievement. Owned by the developer.
Claude Code reads GitHub and quantifies the same period objectively.
Manager compares the two, coaches on the gap, rolls up a team view.
A repeatable five-step loop, every week.
A lightweight Markdown template, committed to the repo so it is versioned and visible.
WEEKLY-REPORT.md# Weekly Report — [Name] — Week of [YYYY-MM-DD] ## 1. Targets set this week - [ ] Target 1: ... - [ ] Target 2: ... - [ ] Target 3: ... ## 2. Changelog (what shipped) - Feature/fix: ... (PR #__) - Feature/fix: ... (PR #__) - Refactor / AI-assisted: ... (PR #__) ## 3. Blockers & risks - ... ## 4. AI usage notes - Where Claude Code helped / where it didn't ... ## 5. Self-rated achievement - Overall: __ % (rationale: ...)
Format proposed: Markdown for the narrative + an Excel tracker (Component C) for the numbers. Both can be generated as starter files once approved.
An automated weekly read of GitHub that quantifies each developer across all KPI aspects — proposed design, not yet built.
/weekly-audit) runs against the GitHub repos for a given author and date range.| Category | Auto-pulled from GitHub |
|---|---|
| Productivity & velocity | Merged PRs, cycle time, median PR size, time-to-first-review |
| Code quality | Change failure rate, review pass rate, reverts/hotfixes, rework within 21 days |
| AI adoption | % of PRs flagged AI-assisted, CLAUDE.md / shared prompt contributions |
| Delivery & reliability | Deploy frequency, lead time, CI pass rate, MTTR on linked incidents |
# Saved as a Claude Code slash command: /weekly-audit
Audit GitHub activity for AUTHOR=[username] over the last 7 days
(REPO=[org/repo...]). For that window, compute and report:
Productivity : merged PRs, median cycle time, median PR size, time-to-first-review
Quality : change-failure rate, review pass rate, reverts, 21-day rework
AI adoption : % AI-assisted PRs (by label), CLAUDE.md / prompt contributions
Delivery : deploy frequency, lead time, CI pass rate, MTTR (linked incidents)
Output a one-page scorecard table: metric | this week | target | % to target | trend.
Flag any metric >20% off target. Do not infer effort from commit count or LOC.
Devs and manager run /weekly-audit manually each Friday. Simplest; no infra. Recommended to start.
A recurring weekly task runs the audit automatically and posts the scorecard. More automated; set up after the command is proven.
An Excel tracker where each developer sets weekly targets and achievement is calculated against the audited result.
| Column | Source | Example |
|---|---|---|
| KPI / target | Dev sets Monday | Cycle time < 2 days |
| Target value | Dev | 2.0 |
| Actual (audited) | Claude Code audit | 2.4 |
| % achievement | Auto-formula | 83% |
| Self-rated % | Dev | 90% |
| Gap / note | Manager | Reviews slow mid-week |
% achievement auto-calculates from target vs audited actual, so the number is objective. The self-rated column captures the developer's own view; the gap between the two is the coaching signal.
Illustrative output of the audit + tracker for one developer. Numbers are placeholders.
| Metric | This week | Target | % to target | Trend |
|---|---|---|---|---|
| Merged PRs | 6 | 5 | 120% | ▲ |
| Cycle time (days) | 2.4 | 2.0 | 83% | ▼ |
| Change failure rate | 10% | <15% | on target | ▲ |
| Review pass rate | 78% | 85% | 92% | — |
| AI-assisted PRs | 67% | growth | ▲ vs last wk | ▲ |
| CI pass rate | 88% | 90% | 98% | ▲ |
| Self-rated achievement: 90% · Audited composite: ~88% · Gap: small, well-calibrated | ||||
Sets targets Mon · records changelog · submits Fri · runs self-audit · self-rates % achievement.
Runs consolidated team audit · compares self-report vs audit · coaches on gaps · maintains team rollup.
Receive the rolled-up trend · approve targets and weightings · use the data for review cycles, not weekly policing.
What we need directors to approve before building anything.
| Decision | Options | Recommendation |
|---|---|---|
| GitHub audit access | Read scope, who holds the connection | Read-only, manager-held to start |
| Automation level | On-demand command vs scheduled job | Start on-demand, schedule later |
| Targets & weights | Per the KPI policy weights | Baseline 4 weeks before grading |
| Use of the data | Coaching vs formal review | Coaching first; formal at quarter |
WEEKLY-REPORT.md template and the Excel tracker./weekly-audit Claude Code command on one repo.