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Client Deliverables

Community
anotb
client-deliverables

Create and refine consulting reports, decision memos, and executive presentations, including storylines, exhibits, visual design, and artifact review. Use for PowerPoint decks, executive summaries, board readouts, investment committee memos, steering updates, and final reports. For sales proposals and pitch decks, use proposal-development when available.

Overview

Publisheranotb
Repositorymanagement-consulting-plugin
Skill nameclient-deliverables
Stars
62
Forks
9
Bundled files
5
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.

  • 5 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 Client Deliverables 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/client-deliverables
  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/client-deliverables .claude/skills/client-deliverables
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Client Deliverables 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 Client Deliverables 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 Client Deliverables 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.

Client Deliverables

Turn the analysis into an artifact that enables the intended decision and survives scrutiny. Establish the audience, decision, evidence base, requested format, and reading or presentation conditions from the user's context. Preserve supplied templates, branding, section order, accessibility needs, and length constraints.

Use available evidence and complete the portions it supports. Mark missing proof points or pending decisions where they matter; ask only when a missing answer blocks a useful result. Do not invent a number, source, owner, date, testimonial, or case result to fill a design. Distinguish proposed actions from agreed commitments.

Build the argument

Lead with the answer, decision request, or the uncertainty that prevents a decision. Organize supporting arguments by what the audience needs to assess the recommendation. Situation-complication-question-answer can help develop the story; it does not require delaying the answer or showing those labels.

Use takeaway titles for analytical sections and slides when they aid comprehension. Keep navigational labels or prescribed headings where the template requires them. The headline must be supported by the exhibit and its qualifications. Do not turn an association into a causal claim or a forecast into an achieved result.

Connect each consequential claim to its source or calculation. Keep units, periods, definitions, and scenario names consistent throughout. Show contradictions and decision-changing limitations near the claim they qualify. Separate observed results, forecasts, judgment, and illustrative examples. A conditional sentence still needs a basis if it asserts an empirical pattern.

Concentrate detail on the trade-offs, financial and operational implications, and actions that determine this decision. Use compact tables for comparisons and prose for reasoning. There is no required sentence count, supporting-argument count, or deck length.

Choose the artifact

Follow an explicit format request. If the format is open, a memo or report suits asynchronous scrutiny; a presentation suits a discussion with visual evidence. A read-ahead deck needs more self-contained explanation than a projected presentation. Produce multiple formats only when requested or needed for the stated use.

  • For reports, decision briefs, and investment committee memos, read written reports.
  • For executive decks, exhibit selection, discussion design, and backup, read executive presentations.
  • When designing or substantially revising slides, read slide design for visual direction, composition, analytical emphasis, and review across the deck.
  • When producing a PowerPoint file with code, read PPTX generation. The optional bridge helper is a tool-specific implementation, not a requirement for other presentation tools.

Use the host's available document, spreadsheet, or presentation tools and relevant format skills if available. This skill supplies consulting content and review criteria; it does not depend on a particular agent or installed plugin. For a requested file, create the file when tools permit. If creation or rendering is unavailable, state the limitation and deliver the usable portion without claiming a finished artifact.

Check before delivery

Check that the executive summary stands alone, the recommendation follows from the evidence, and the requested decision is explicit. Reconcile figures across prose, tables, charts, and appendices. Test that a chart actually represents the intended relationship, not merely that it renders.

For files, open or parse the saved artifact, refresh calculations where supported, and inspect rendered pages or slides. Check clipping, overlap, legibility, pagination, source notes, and navigation at the intended reading size. Inspect material revisions again, stopping once the affected checks pass. Give the user the artifact and a concise account of material assumptions or verification limits.

For decks, also inspect the slides together. A sequence of correctly aligned but repetitive text boxes can still be a weak presentation. Use layout, scale, and visual emphasis to make the argument easier to understand while retaining the client's visual identity. Keep drafting and validation commentary out of the delivered content.

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 Client Deliverables AI skill do?

Create and refine consulting reports, decision memos, and executive presentations, including storylines, exhibits, visual design, and artifact review. Use for PowerPoint decks, executive summaries, board readouts, investment committee memos, steering updates, and final reports. For sales proposals and pitch decks, use proposal-development when available.

Why use Client Deliverables on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/anotb/management-consulting-plugin/tree/main/skills/client-deliverables. 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 Client Deliverables?

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 Client Deliverables?

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

Is the Client Deliverables 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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