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Execute

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alirezarezvani
execute

/cs:execute <decision> — Generate a 90-day execution plan with weekly milestones, DRIs, and check-in cadence from an approved decision. Use when a logged decision needs to become an operating plan — e.g. turning an approved market-entry call into weekly milestones with DRIs.

Overview

Publisheralirezarezvani
Repositoryclaude-skills
Skill nameexecute
Stars
28K
Forks
3.9K
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 alirezarezvani on GitHub. Read the source before you install it.

Installation

Install the Execute 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/alirezarezvani/claude-skills/tree/main/c-level-agents/skills/execute
  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/alirezarezvani/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/c-level-agents/skills/execute .claude/skills/execute
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Execute 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 Execute 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 Execute 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.

/cs:execute — 90-Day Execution Plan

Command: /cs:execute <decision-path>

Turns an approved decision into a 90-day plan with weekly milestones, named DRIs, and a check-in cadence. Where most decisions die: between "we decided" and "what's next Monday?"

Pipeline Position

/cs:office-hours  →  /cs:brief  →  /cs:boardroom  →  /cs:decide  →  /cs:execute  →  /cs:post-mortem
                                                                       ↑ you are here

Input

An approved decision record (output of /cs:decide).

Output Plan Format

Saved to ~/.claude/execution/YYYY-MM-DD-<slug>.md:

markdown
# Execution Plan: <decision title>
**Decision:** <link to /cs:decide record>
**Owner (Sponsor):** <founder or exec>
**Start:** YYYY-MM-DD
**Checkpoint:** YYYY-MM-DD (90d)

## Outcome (binding)
[Copied from decision: success + kill criteria]

## Workstreams
| Workstream | DRI | Success Metric | Status |
|---|---|---|---|
| <e.g., Pricing rollout> | <name> | <metric, threshold> | Not started |
| <e.g., Comms> | <name> | <metric> | Not started |
| <e.g., Eng changes> | <name> | <metric> | Not started |

## Weekly Milestones
| Week | Milestone | DRI | Definition of Done |
|---|---|---|---|
| 1 | <e.g., positioning locked> | <name> | <observable outcome> |
| 2 | <e.g., draft launched> | <name> | <observable> |
| 3 | ... | | |
| 12 | <e.g., checkpoint review> | <name> | <observable> |

## Cadence
- **Weekly:** Owner reviews status (15 min)
- **Bi-weekly:** Cross-functional sync (30 min)
- **Day 30 / 60 / 90:** Checkpoint with cs-chief-of-staff

## Dependencies
- Internal: <list>
- External: <vendors, regulators, customers>

## Risk Register
| Risk | Likelihood | Impact | Owner | Mitigation |
|---|---|---|---|---|
| <e.g., delayed legal review> | M | H | <name> | <plan> |

## Kill Criteria Watch
[Copied from decision; reviewed at every checkpoint]
- <metric, threshold, action>

Workflow

  1. Read the decision record
  2. Decompose the chosen option into 3-6 workstreams
  3. Name a DRI for each workstream
  4. Reverse-engineer 12 weekly milestones from the checkpoint date
  5. Set the cadence (weekly + bi-weekly + 30/60/90 checkpoints)
  6. Build the risk register (cross-reference original Phase 4 devil's-advocate concerns)
  7. Save and notify DRIs

Why 90 Days

  • Long enough to show real signal (not just activity)
  • Short enough to course-correct before damage compounds
  • Matches quarterly OKR cycle, fundraise sprints, and most board cadences

Routing

  • /cs:post-mortem <decision> — at day 90 (or earlier if kill criteria trigger)
  • /cs:boardroom — if a checkpoint reveals a need to re-decide

Related


Version: 1.0.0

Frequently asked questions

What does the Execute AI skill do?

/cs:execute <decision> — Generate a 90-day execution plan with weekly milestones, DRIs, and check-in cadence from an approved decision. Use when a logged decision needs to become an operating plan — e.g. turning an approved market-entry call into weekly milestones with DRIs.

Why use Execute on TypingMind?

Because you install it once and use it with any model. Execute 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 Execute in TypingMind?

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

Which AI models can use Execute?

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 Execute?

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

Is the Execute AI skill free?

Yes. It is published on GitHub by alirezarezvani 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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