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Weekly

Community
kv0906
weekly

Weekly review — 3-phase process (Collect/Reflect/Plan). Reviews shipped items, blockers, decisions, and plans next week. Use on Fridays or Mondays.

Overview

Publisherkv0906
Repositorypm-kit
Skill nameweekly
Stars
140
Forks
35
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by kv0906 on GitHub. Read the source before you install it.

Installation

Install the Weekly AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/kv0906/pm-kit/tree/main/.claude/skills/weekly
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/kv0906/pm-kit.git /tmp/pm-kit
mkdir -p .claude/skills
cp -r /tmp/pm-kit/.claude/skills/weekly .claude/skills/weekly
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Weekly in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Weekly on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Weekly is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

/weekly — Weekly Review

Facilitates your weekly review by collecting the past week's data, reflecting on progress, and planning the next week.

Context

Today's date: !date +%Y-%m-%d

Config: @_core/config.yaml Processing logic: @_core/PROCESSING.md Product judgment: @_core/judgment.md Knowledge and evidence: @_core/knowledge.md

Reference template: @_templates/sprint-retro.md

Session Task Progress

Create tasks at skill start with dependencies:

TaskCreate: "Phase 1: Collect"
  description: "Gather daily notes, shipped items, blockers from past week"
  activeForm: "Collecting weekly data..."

TaskCreate: "Phase 2: Reflect"
  description: "Analyze patterns, what worked/didn't"
  activeForm: "Reflecting on weekly performance..."

TaskCreate: "Phase 3: Plan"
  description: "Set next week priorities, identify top risks"
  activeForm: "Planning next week..."

Set dependencies:

TaskUpdate: "Phase 2", addBlockedBy: [phase-1-id]
TaskUpdate: "Phase 3", addBlockedBy: [phase-2-id]

Phase 1: Collect

  1. Read all daily notes from the past 7 days
  2. For each active project, aggregate:
    • Shipped items
    • Items carried over (WIP)
    • Blockers resolved
    • Blockers still open
  3. Read recent decisions and relevant linked product docs, customer feedback, and metric observations
  4. Load relevant approved judgment examples and personal preferences; keep proposed lessons separate
  5. Separate delivered work, learning, and measured outcomes; cite original sources, dates, and scope
  6. Identify patterns in standup data without treating repeated mentions of one source as independent evidence

Phase 2: Reflect

  1. Identify what went well / didn't go well
  2. Surface recurring patterns (e.g., same blocker type)
  3. Compare expected outcomes with observed results; include metric definition, period, segment, baseline, and source when available
  4. Check: which blockers slowed progress most?
  5. Mark missing outcome data as unmeasured; distinguish correlation from causal evidence and surface conflicting signals
  6. Note decisions or assumptions that need revisiting and the evidence behind each proposed change
  7. Propose scoped lessons with sources and exceptions; do not silently update personal judgment rules
  8. Compare results with the recorded decision rule and guardrails; propose scale, iterate, stop, or investigate only when evidence supports it
  9. Identify which existing decision, opportunity map, or metric assumption the evidence should change; a report alone does not close the learning loop

Phase 3: Plan

  1. Propose up to 3 priorities with rationale, owner, and due date; mark missing ownership or dates as unknown
  2. Use /prioritize only when competing work requires a structured comparison; avoid scoring a simple next step
  3. Identify decisions that need to be made and evidence needed to resolve them
  4. Anticipate blockers (risk watchlist) and note carry-over items
  5. Identify the next outcome check or discovery step. Ask approval before changing shared priorities, publishing, or updating personal rules

Output

Create weekly review note using template:

  • Filename: reports/{date}-sprint-retro.md
  • Keep the template's type: retro and status: active; the note status does not approve its proposed priorities
  • Include separate Delivered, Learning, and Outcomes sections; use "No new evidence" or "Unmeasured" rather than invented conclusions
  • Reuse an existing review for the same date when appropriate; preserve human edits

Export (Optional)

Supports --xlsx, --pdf, --pptx flags. See .claude/rules/export-formats.md for layout specs and workflow. Complete normal processing first, then generate the formatted file.

Integration

Works with:

  • /daily - Reviews daily notes from the week
  • /push - Commit after completing review
  • /onboard - Load context for informed review
  • /progress - Detailed project status during review

Frequently asked questions

What does the Weekly AI skill do?

Weekly review — 3-phase process (Collect/Reflect/Plan). Reviews shipped items, blockers, decisions, and plans next week. Use on Fridays or Mondays.

Why use Weekly on TypingMind?

Because you install it once and use it with any model. Weekly is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Weekly in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kv0906/pm-kit/tree/main/.claude/skills/weekly. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Weekly?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Weekly?

As many as you like. As long as a model supports skills, you can use Weekly with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Weekly AI skill free?

Yes. It is published on GitHub by kv0906 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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