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Cto Weekly Review

skill-hiteshbandhu-skills-i-use-cto-weekly-review · by hiteshbandhu

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Install

$ agentstack add skill-hiteshbandhu-skills-i-use-cto-weekly-review

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

CTO Weekly Review — Deep Signal Extraction

Founder-grade weekly report from git history, AI session logs, shell history, and file timestamps — not just commit counts.

Works with any coding agent that can run subagents and shell commands.

Supporting files (read when needed):

  • [scripts/collect-git.sh](scripts/collect-git.sh) — git activity across repos
  • [scripts/collect-ai-sessions.sh](scripts/collect-ai-sessions.sh) — AI session logs
  • [scripts/collect-context.sh](scripts/collect-context.sh) — shell, file edits, GitHub CLI
  • [data-sources.md](data-sources.md) — AI log fallback reference
  • [scoring.md](scoring.md) — sustainability health score weights and formulas
  • [report-template.md](report-template.md) — HTML report structure and design
  • [weekly-template.md](weekly-template.md) — markdown summary format

Scripts: read every file under scripts/ before running. They scan git repos, AI session logs, shell history, and local file timestamps. Confirm SINCE, ME, REPOS, and SEARCH_ROOT before execution. Double-check every time.


Step 0 — Scope Confirmation

Ask once (or infer from the request):

| Setting | Default | Notes | |---------|---------|-------| | Date range | last 7 days | Accept "last 14 days", specific dates, "this sprint" | | Repos | crawl ~/ | Accept explicit paths via REPOS env var | | Author email | git config user.email | Ask if multiple identities | | Timezone | system TZ | Critical for working-hour analysis | | Output directory | {SKILL_OUTPUT_DIR}/cto-weekly-review/ | See [../OUTPUT.md](../OUTPUT.md) |

Create the output directory if it does not exist.

Set env vars for collectors: SINCE, ME, REPOS (optional), SEARCH_ROOT (optional).


Step 1 — Data Collection (parallel subagents)

Run three collector subagents in parallel when supported. Each returns structured pipe-delimited output. Keep contexts isolated until Step 2.

Fallback: Run scripts sequentially yourself, or inline if scripts unavailable.

Subagent 1 — Git Collector

SINCE="7 days ago" ME="user@email.com" bash scripts/collect-git.sh
# Optional: REPOS="/path/a /path/b" SEARCH_ROOT="$HOME"

Collects: commits, stats, files, reverts, TODOs, heatmap hours, flow sessions, dependency/schema/infra changes.

Subagent 2 — AI Collector

SINCE="7 days ago" bash scripts/collect-ai-sessions.sh

See [data-sources.md](data-sources.md) for output format. Skip gracefully if empty.

Subagent 3 — Context Collector

SINCE="7 days ago" bash scripts/collect-context.sh

Collects: shell history, tool usage, file edit timestamps, GitHub PRs/issues/reviews.


Step 2 — Signal Processing

Merge all collector output. Compute derived metrics using [scoring.md](scoring.md).

2A. Working Hours Profile

From commit timestamps + AI session timestamps + FSEDIT records:

  • Commits by hour and day, peak hour, night/morning/core/evening percentages
  • Days active, weekend percentage, daily start/end spans

2B. Focus Session Analysis

Cluster commits with gap > 90 min = new session. Classify per scoring.md: deep work / quick fix / context switching / normal.

2C. Commit Quality Analysis

Classify by size (micro/small/medium/large) and type (feature/fix/refactor/experiment/docs/infra/revert). Compute churn rate, avg files per commit, revert count.

2D. Cross-Skill ADR Linking

Read architecture decisions written this week from the shared output tree:

{SKILL_OUTPUT_DIR}/architecture-review/index.md
{SKILL_OUTPUT_DIR}/architecture-review/ADR-*.md

If the index exists, parse rows and include ADRs whose date falls within the report's date range in:

  • Key decisions narrative (Step 3)
  • Decisions table in markdown and HTML (Section 9)
  • Set Source column to architecture-review with link to the ADR file

If no ADRs this week, note "No ADRs recorded this week" — do not invent decisions.

2E. AI Leverage

Cross-reference AI session end times with commit timestamps. See scoring.md.


Step 3 — Narrative Synthesis

After processing, write these sections (orchestrating agent or synthesis subagent):

  1. The week in one line — crisp, honest, specific
  2. What actually shipped — merged/deployed only
  3. What's in progress — branches, PRs, WIP
  4. Key decisions made — include linked ADRs from Step 2D
  5. Experiments & findings — actual results if detectable
  6. Debt & blockers — what slowed you down
  7. Sustainability reflection — honest paragraph on intensity
  8. Next week top 3 — specific and actionable

Tone: Founder briefing co-founder. Specific numbers. Honest about bad weeks. No corporate fluff.


Step 4 — Generate Reports

Always write both markdown and HTML.

Markdown (required)

Fill [weekly-template.md](weekly-template.md).

Path: {output_dir}/weekly-YYYY-MM-DD.md

HTML (required unless user says "markdown only")

Follow [report-template.md](report-template.md). Link to the .md file in header.

Path: {output_dir}/weekly-YYYY-MM-DD.html


Step 5 — Update Registry

Maintain {output_dir}/index.md:

# CTO Weekly Reviews

| Week ending | Markdown | HTML | Health | Commits | Highlights |
|-------------|----------|------|--------|---------|------------|

Append row (newest first):

| YYYY-MM-DD | [weekly-YYYY-MM-DD.md](weekly-YYYY-MM-DD.md) | [weekly-YYYY-MM-DD.html](weekly-YYYY-MM-DD.html) | [score]/100 | [n] | [one-line summary] |

Step 6 — Output to User

  1. List saved paths (.md, .html, index.md)
  2. PDF export hint (Cmd+P or Export PDF button)
  3. Best content angle from this week
  4. One honest line about week health — don't sugarcoat
  5. Note ADRs linked from architecture-review (if any)

Edge Cases

  • No git history — use AI sessions + file timestamps; note absence
  • No AI session logs — skip AI section; note absence
  • No gh CLI — skip PR section; suggest brew install gh
  • macOS vs Linux dates — scripts handle both date -d and date -v
  • No shell timestamps — skip shell section silently
  • Repos outside ~/ — pass explicit REPOS paths
  • Monorepos — one repo, break down by package directory
  • Multiple git identities — comma-separate emails in ME or run twice
  • Subagents unavailable — run three scripts sequentially
  • architecture-review index missing — skip ADR linking silently

Invocation Examples

"give me a weekly review"
"generate my CTO report for this week"
"what did I build this week"
"weekly digest, last 14 days"
"markdown only — skip HTML"

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.