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Engagement Pricing

Community
anotb
engagement-pricing

Price consulting engagements and evaluate delivery economics. Use for fee models, rate cards, margin floors, realization, retainers, discounts, payment schedules, and the commercial section of a proposal or SOW.

Overview

Publisheranotb
Repositorymanagement-consulting-plugin
Skill nameengagement-pricing
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 Engagement Pricing 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/engagement-pricing
  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/engagement-pricing .claude/skills/engagement-pricing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Engagement Pricing 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 Engagement Pricing 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 Engagement Pricing 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.

Engagement Pricing

Develop a commercially credible price that fits the scope, delivery cost, value to the client, and available alternatives. Start with the user's requested pricing decision; preserve an agreed model or terms unless a material problem needs to be raised.

Use the supplied scope, cost basis, capacity, rate card, target margins, budget, and procurement context. Continue a draft with explicit unknowns when inputs are missing; ask only for information that prevents a defensible calculation or recommendation. Do not substitute generic rate or margin benchmarks for firm data.

Select the commercial model

Assess scope certainty, duration, deliverables, dependence on client actions, outcome measurability, attribution, and payment risk. Fixed fees fit bounded deliverables when delivery risk can be estimated. T&M fits evolving work; caps need an explicit scope or effort boundary. Retainers fit continuing access or delivery with defined capacity and service expectations, including a new client when that arrangement is suitable.

Distinguish pricing based on value from payment contingent on outcomes. A fixed value-based fee need not depend on measuring realized results; an outcome-linked fee needs a defensible baseline, measurement rules, attribution, timing, and treatment of external factors. Hybrid structures can share uncertainty without leaving all costs at risk.

Model the economics

Define what each cost includes before adding it. If personnel cost already includes benefits and allocated overhead, do not allocate that overhead again. Separate direct delivery costs, incremental external costs, allocated overhead, and risk contingency. Make the allocation basis explicit. Do not use billing rates as personnel costs.

Calculate the relevant measures with available tools and state their definitions:

  • Delivery margin amount = fee minus defined direct delivery cost; percentage = that amount divided by fee.
  • Profit after allocations = fee minus all included costs, counted once; percentage = profit divided by fee.
  • Minimum fee for target margin m on that cost basis = included cost / (1-m), for m < 1.
  • Realization = actual fee / rate-card value of actual delivery effort. Explain write-offs, discounts, and scope growth.
  • Effective daily rate = fee / total person-days. Confirm the workday length and distinguish headcount from effort.

Show the effect of overrun, scope change, discount, and payment timing where they change the decision. A contingency is a disclosed allowance derived from risks, not an automatic percentage added to an already risk-adjusted estimate.

Propose terms and trade-offs

Use commercial structures and negotiation for payment, retainer, outcome, and concession detail. Respect supplied contract terms and the firm's approval authority. Present proposed terms as proposals, not universal legal requirements or commitments already made.

Tie payment timing to the delivery cost curve, exposure to delayed acceptance, and procurement constraints. Quantify financing costs where material instead of imposing a universal Net 30 or final-payment cap. Make scope, client dependencies, change control, acceptance, and exit terms specific to the engagement.

For the client's value case, distinguish benefit-cost multiple (benefits / costs) from net ROI ((benefits-costs)/costs). Include relevant client implementation and operating costs, not only the consulting fee. Explain whether benefits are cash savings, released capacity, incremental contribution, or risk reduction. Claim attribution only where supported.

Deliver

Present the recommended fee and structure, included scope, assumptions, cost and margin basis, downside exposure, payment schedule, and decisions needed. Offer alternative tiers only when they represent useful scope or risk choices. Keep numerical tables compact and put the rationale beside the choice. Producing a quote does not authorize submitting it or agreeing concessions with a client.

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 Engagement Pricing AI skill do?

Price consulting engagements and evaluate delivery economics. Use for fee models, rate cards, margin floors, realization, retainers, discounts, payment schedules, and the commercial section of a proposal or SOW.

Why use Engagement Pricing on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/anotb/management-consulting-plugin/tree/main/skills/engagement-pricing. 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 Engagement Pricing?

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 Engagement Pricing?

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

Is the Engagement Pricing 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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