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Implementation Planning

Community
anotb
implementation-planning

Turn an agreed recommendation into a feasible roadmap and implementation plan. Use for sequencing, workstreams, dependencies, resources, rollout gates, recovery plans, and the business case needed to fund execution.

Overview

Publisheranotb
Repositorymanagement-consulting-plugin
Skill nameimplementation-planning
Stars
62
Forks
9
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Implementation Planning 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/anotb/management-consulting-plugin/tree/main/skills/implementation-planning
  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/anotb/management-consulting-plugin.git /tmp/management-consulting-plugin
mkdir -p .claude/skills
cp -r /tmp/management-consulting-plugin/skills/implementation-planning .claude/skills/implementation-planning
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Implementation Planning 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 Implementation Planning 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 Implementation Planning 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.

Implementation Planning

Produce a plan that respects funding, capacity, dependencies, and the decision already made. Enter at the requested stage: compare execution approaches, secure funding, design a roadmap, detail workstreams, or recover a slipping plan. Do not repeat strategy or build a new business case when the direction and funding are already approved.

Use the supplied recommendation, constraints, milestones, resource availability, and baseline. Mark unknowns and proceed with supported portions. Ask only when a missing input prevents a useful or defensible plan. Label estimated durations, proposed owners, and unapproved dates explicitly; do not invent commitments.

Choose the feasible approach

Where execution choices are open, compare materially different approaches, including defer or continue current operations when relevant. Screen hard constraints before weighted preferences. A high score cannot compensate for missing legal eligibility, unaffordable peak funding, or unavailable capacity. Use weights only when they represent the decision-maker's priorities; test whether plausible changes alter the choice.

If funding analysis is requested, show incremental costs and benefits, timing, downside, and funding need against a consistent baseline. Distinguish released capacity from cash savings, and revenue from contribution. Use financial-modeling if available for substantial calculations; this workflow does not depend on that skill being installed. Do not invent a hurdle rate or add a standard contingency percentage to make a plan look complete.

Sequence the work

Define outcomes and acceptance criteria before assigning activities. Group workstreams by manageable responsibility and explicit interfaces. Map dependencies, required client decisions, vendor lead times, and business calendar constraints before committing dates.

Use scheduling and resourcing for critical paths, effort, capacity, and recovery. Distinguish target dates from feasible forecasts. Protect business continuity and account for parallel operations, training, adoption, support, and benefit measurement where relevant.

Choose rollout gates that release commitment as evidence improves. State the evidence needed, authority, and responses: proceed, proceed with bounded conditions, revise, or stop. These are gates for executing the plan, not prerequisites for drafting later phases. Provisional later phases can remain useful while earlier evidence is pending.

Assign ownership and control

Give each deliverable an accountable role and the people doing the work. In a RACI, normally assign one A and at least one R, with combined A/R allowed on small teams. Confirm how joint legal authorities or mandated approvals are represented without hiding them in a simplified matrix. Keep consulted roles limited to those whose input changes the work.

Use the client's existing governance where supplied. Set escalation by materiality, remaining decision time, and authority rather than generic two-week or 10% cutoffs. For ongoing reporting, project-governance can help when available. Separate consulting recommendations from client approval and spending authority.

Deliver and check

Present the outcome, sequence, workstreams, milestone evidence, dependencies, capacity, budget, risks, and immediate decision or action at the requested depth. A short roadmap does not require a full program handbook.

Verify dates follow dependencies, resource demand fits availability, budgets reconcile, and benefits have a measurement owner. Show the limiting constraint and the consequence of delay. For a recovery plan, distinguish the original baseline, current forecast, and proposed reset; do not erase slippage by silently replacing the baseline. State the trigger and fallback for the risks that could defeat the plan.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Implementation Planning AI skill do?

Turn an agreed recommendation into a feasible roadmap and implementation plan. Use for sequencing, workstreams, dependencies, resources, rollout gates, recovery plans, and the business case needed to fund execution.

Why use Implementation Planning on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/anotb/management-consulting-plugin/tree/main/skills/implementation-planning. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Implementation Planning?

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 Implementation Planning?

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

Is the Implementation Planning AI skill free?

Yes. It is published on GitHub by anotb 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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