New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Weekly Review

by borghei in borghei/Claude-Skills

Synthesize a week of inputs (calendar, tasks, journal, OKR check-ins) into a structured review with wins, learnings, blockers, and next-week priorities.

MITAuto-check passedBusiness, Finance & HR

Install Weekly Review

skills CLI
$ npx skills add borghei/Claude-Skills --skill weekly-review -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install borghei/Claude-Skills weekly-review --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/personal-productivity/weekly-review .claude/skills/weekly-review && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
weekly-review
GitHub stars
881
Token cost
~899 tokens
SKILL.md length
408 words
Files
4 (incl. scripts, references, assets)
Skills in repo
349
Repo updated
First seen
Licence
MIT

At a glance

Synthesize a week of inputs (calendar, tasks, journal, OKR check-ins) into a structured review with wins, learnings, blockers, and next-week priorities.

  • Works in 3 steps: Fill in assets/weekly_review_input.json… → Run: python… → Save the output as your week's review
  • A Friday/Sunday weekly review
  • SKILL.md covers Keywords, Clarify First, Quick Start and Core Workflows, plus 4 more sections
  • Runs Python scripts from its folder; calls python

What it does

Weekly Review is an agent skill from borghei/Claude-Skills. Synthesize a week of inputs (calendar, tasks, journal, OKR check-ins) into a structured review with wins, learnings, blockers, and next-week priorities. Use for a Friday/Sunday weekly review, GTD review, or OKR check-in.

Its SKILL.md is about 900 tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts, reference files and assets (for example `assets/weekly_review_input.json`, `references/weekly_review_methodology.md` and `scripts/weekly_review_synthesizer.py`).

It sits in Business, Finance & HR, covering Journaling and reflection and OKRs and executive reporting. The repository describes itself as: 385 AI skills, 77 expert agents, and 900 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, research, and a LinkedIn toolkit… The licence is MIT.

When your agent uses it

  • A Friday/Sunday weekly review
  • Tasks that involve Journaling and reflection
  • Tasks that involve OKRs and executive reporting

Example prompts

  • “/weekly-review”

Requirements

  • Python 3

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Fill in assets/weekly_review_input.json with the past week's wins, learnings, blockers, OKR progress
  2. Run: python scripts/weekly_review_synthesizer.py weekly_review_input.json
  3. Save the output as your week's review

What it can do on your machine

Read from SKILL.md and the folder at commit 4a698e8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Weekly Review loads about 899 tokens when it runs, and up to ~2.3k if it reads all its reference files. Until then it costs about 59 tokens; SKILL.md has 408 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~59
When it runs · the whole SKILL.md, loaded when a task matches
~899
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from borghei/Claude-Skills at commit 4a698e8, republished under its MIT licence (© borghei). 408 words, ~899 tokens.

Download SKILL.mdSave it as .claude/skills/weekly-review/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
weekly-review
description
Synthesize a week of inputs (calendar, tasks, journal, OKR check-ins) into a structured review with wins, learnings, blockers, and next-week priorities. Use for a Friday/Sunday weekly review, GTD review, or OKR check-in.
license
MIT + Commons Clause
metadata.version
1.0.0
metadata.author
borghei
metadata.category
personal-productivity
metadata.domain
personal-effectiveness
metadata.updated
2026-05-04
metadata.python-tools
weekly_review_synthesizer.py
metadata.tech-stack
GTD, OKRs, productivity

Weekly Review

Synthesize a week into a structured review covering wins, learnings, blockers, and next-week priorities.

Keywords

weekly review, GTD, getting things done, OKR check-in, retrospective, weekly retro, journal, reflection, end of week, EOW

Clarify First

Before synthesizing the review, confirm these inputs. If any is unknown or vague, ASK — do not assume:

  • The week's raw inputs — actual wins, learnings, and blockers; this is the content the review synthesizes, not invented
  • OKR / goal progress — current numbers vs target drives the check-in section and flags drift
  • Next-week priorities — the top 1-3 commitments the review must end on

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Quick Start

  1. Fill in assets/weekly_review_input.json with the past week's wins, learnings, blockers, OKR progress
  2. Run: python scripts/weekly_review_synthesizer.py weekly_review_input.json
  3. Save the output as your week's review

Core Workflows

Workflow 1: Standard Friday Review (30 min)
  1. Capture 3-5 wins from the past week
  2. Capture 1-3 learnings (what surprised you, what you got wrong)
  3. Capture top 1-3 blockers / risks for next week
  4. Update OKR / goal progress
  5. List top 3 priorities for next week
  6. Run synthesizer

Time Estimate: 30-45 minutes weekly.

Workflow 2: Bootstrap (First Time)
  1. Read references/weekly_review_methodology.md
  2. Decide cadence (Friday afternoon vs Sunday evening — both work)
  3. Block 30-45 min recurring on calendar
  4. Use input template; tune over 4 weeks until format works for you

Time Estimate: 1 hour to set up; 30-45 min weekly thereafter.

Show full SKILL.md (148 more words)Show less
Workflow 3: Quarterly Pattern Review
  1. Save weekly reviews in a single folder
  2. Quarterly: read all 12-13 weeks
  3. Look for patterns: recurring blockers, energy patterns, OKR drift
  4. Adjust cadence, cadence, or commitments based on patterns

Time Estimate: 1-2 hours quarterly.

Tools

weekly_review_synthesizer.py

Reads structured weekly input JSON and produces a markdown weekly review.

bash
python scripts/weekly_review_synthesizer.py input.json
python scripts/weekly_review_synthesizer.py input.json --json

Reference Guides

  • references/weekly_review_methodology.md — GTD weekly review, OKR check-in patterns, common pitfalls

Templates

  • assets/weekly_review_input.json — Input template

Best Practices

  • Block the time. 30 min recurring; defend against rescheduling.
  • Same time each week. Habits stick when the trigger is consistent.
  • Capture the pattern, not the noise. Weekly review is a layer above the moment-to-moment task list.
  • OKR check-in over chase. Weekly OKR progress is signal; quarterly is the action moment.
  • Compound across weeks. Reviews are most useful when read in batches.
  • Don't over-format. A messy review you actually do beats a perfect one you skip.

© borghei, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references, assets) in personal-productivity/weekly-review of borghei/Claude-Skills.

  • SKILL.md
  • assets/weekly_review_input.json
  • references/weekly_review_methodology.md
  • scripts/weekly_review_synthesizer.py

Open the folder on GitHubat commit 4a698e8

Compare with similar skills

Weekly Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Weekly Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Weekly Review this skillborghei/Claude-Skills881—~899Automated safety check: PassMIT
Trading As Businessagentii-ai/agentii-investment-intelligence207—~655Automated safety check: PassApache-2.0
Tradeupstash/botstreet1121 repos~1.1kAutomated safety check: PassNone
Agency Dashboardindranilbanerjee/digital-marketing-pro8551 repos~2.5kAutomated safety check: PassMIT
Analytics Strategyrampstackco/claude-skills9401 repos~2.4kAutomated safety check: PassMIT
Pine BacktesterTradersPost/pinescript-agents1701 repos~3.9kAutomated safety check: PassNone

Similar skills

  • Trading As Business

    agentii-ai/agentii-investment-intelligence

    Trading as a business, performance review process, trade journaling, capital allocation discipline, business infrastructure for traders, KPI tracking for trading operations

    207 GitHub stars~655 tokensUpdated 9 days ago
    Business, Finance & HRAuto-check passed

  • Trade

    upstash/botstreet

    Official

    Execute the daily virtual trading process. An agent skill from upstash/botstreet.

    112 GitHub starsUsed in 1 repo~1.1k tokens
    Business, Finance & HRAuto-check passed

  • Agency Dashboard

    indranilbanerjee/digital-marketing-pro

    Generate a portfolio-level dashboard across ALL client brands — per-client RAG health scores, campaign activity, budget pacing, aggregate KPIs, team utilization, pending approvals, upcoming…

    855 GitHub starsUsed in 1 repo~2.5k tokens
    Productivity & AutomationAuto-check passed

  • Analytics Strategy

    rampstackco/claude-skills

    Design measurement frameworks including event taxonomy, KPI hierarchy, dashboard architecture, attribution models, and analytics implementation strategy.

    940 GitHub starsUsed in 1 repo~2.4k tokens
    Business, Finance & HRAuto-check passed

  • Pine Backtester

    TradersPost/pinescript-agents

    Implements comprehensive backtesting and performance metrics.

    170 GitHub starsUsed in 1 repo~3.9k tokens
    Business, Finance & HRAuto-check passed

  • Onboarding Planner

    bpinheiroms/dotfiles

    Plan high-conversion mobile app onboarding flows from scratch.

    108 GitHub stars~5.4k tokensUpdated 4 mo ago
    Business, Finance & HRAuto-check passed

More from borghei/Claude-Skills

All 349 skills in this repo

  • Agents In The Team

    borghei/Claude-Skills

    Run delivery when AI coding and ops agents take tickets. An agent skill from borghei/Claude-Skills.

    881 GitHub stars~4.2k tokensUpdated yesterday
    Auto-check passed

  • AI Content Disclosure

    borghei/Claude-Skills

    Check AI-generated marketing content and reviews for required disclosures under the EU AI Act, FTC rules and platform AI-label policies.

    881 GitHub stars~3.4k tokensUpdated yesterday
    Auto-check passed

  • AI Prototyping

    borghei/Claude-Skills

    Idea to AI-generated prototype to customer validation to engineering handoff.

    881 GitHub stars~3.6k tokensUpdated yesterday
    Auto-check passed

  • Analytics Engineer

    borghei/Claude-Skills

    Analytics engineering across data modeling, dbt, transformation, and semantic layers.

    881 GitHub stars~3.4k tokensUpdated yesterday
    Auto-check passed

  • Ansoff Matrix

    borghei/Claude-Skills

    Ansoff Matrix — 4-quadrant framework for growth options: market penetration, market/product development, and diversification.

    881 GitHub stars~2.2k tokensUpdated yesterday
    Auto-check passed

  • Brainstorm Okrs

    borghei/Claude-Skills

    OKR brainstorming and validation using the Radical Focus framework — outcome objectives, measurable key results, counter-metrics.

    881 GitHub stars~1.4k tokensUpdated yesterday
    Auto-check passed

Categories

Questions about Weekly Review

What does Weekly Review do?

Synthesize a week of inputs (calendar, tasks, journal, OKR check-ins) into a structured review with wins, learnings, blockers, and next-week priorities. Weekly Review is an agent skill from borghei/Claude-Skills. Synthesize a week of inputs (calendar, tasks, journal, OKR check-ins) into a structured review with wins, learnings, blockers, and next-week priorities.

When should I use Weekly Review?

Weekly Review fits situations like: A Friday/Sunday weekly review; tasks that involve Journaling and reflection; tasks that involve OKRs and executive reporting.

How do I install Weekly Review in Claude Code?

Run `npx skills add borghei/Claude-Skills --skill weekly-review -a claude-code`. Or copy the skill folder (personal-productivity/weekly-review in borghei/Claude-Skills) into .claude/skills/weekly-review in your project. Claude Code loads it when a task matches its description.

How do I install Weekly Review in Codex?

Run `npx skills add borghei/Claude-Skills --skill weekly-review -a codex`. Or copy the skill folder (personal-productivity/weekly-review in borghei/Claude-Skills) into .agents/skills/weekly-review in your project. Codex loads it when a task matches its description.

Can I use Weekly Review in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add borghei/Claude-Skills --skill weekly-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/weekly-review, .gemini/skills/weekly-review, .github/skills/weekly-review and .opencode/skills/weekly-review in your project.

What does Weekly Review need to run?

Going by SKILL.md and its folder, Weekly Review needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Weekly Review access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Weekly Review safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Weekly Review use?

Weekly Review is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Weekly Review use?

About 899 tokens (SKILL.md is roughly 3.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.4k tokens, read only when the agent opens those files.

What are the alternatives to Weekly Review?

Skills that share tags, products or a category with Weekly Review: Trading As Business (agentii-ai/agentii-investment-intelligence, 207 stars), Trade (upstash/botstreet, 112 stars), Agency Dashboard (indranilbanerjee/digital-marketing-pro, 855 stars) and Analytics Strategy (rampstackco/claude-skills, 940 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Weekly Review?

borghei (a GitHub user) maintains it in borghei/Claude-Skills, which has 881 GitHub stars. The repository holds 349 skills in this directory. The repository was last updated on October 7, 2026.

Source: borghei/Claude-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.