engagement-pricing

engagement-pricing is a skill for Claude Code from anotb/management-consulting-plugin. It costs 45 tokens per session (819 once invoked), scanned A, original, MIT.

A consulting-pricing workflow for setting fees, rate cards, payment schedules, margins, and contract terms. It covers fixed-price, hourly, retainer, value-based, outcome-based, and mixed engagements.

In plain words
What is it for?
Use it to choose a pricing model, build or defend a rate card, estimate engagement profitability, plan payments, and set liability limits.
Why use it?
It helps connect the price to the actual work, team costs, client budget, alternatives, and desired profit instead of choosing a fee without modeling the economics.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the management-consulting plugin — 16 skills shipped together

Good fit Use it to choose a pricing model, build or defend a rate card, estimate engagement profitability, plan payments, and set liability limits.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/anotb/management-consulting-plugin/engagement-pricing
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add anotb/management-consulting-plugin --skill engagement-pricing
Clone the repo
git clone --depth 1 https://github.com/anotb/management-consulting-plugin

Made for: Claude Code.

Or install management-consulting, the plugin that ships this one along with the rest of its 16 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for engagement-pricing

README.md
[![agentmods](https://agentmods.dev/badge/skills/anotb/management-consulting-plugin/engagement-pricing/github.svg)](https://agentmods.dev/skills/anotb/management-consulting-plugin/engagement-pricing)
Your own site
<a href="https://agentmods.dev/skills/anotb/management-consulting-plugin/engagement-pricing"><img src="https://agentmods.dev/badge/skills/anotb/management-consulting-plugin/engagement-pricing/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for engagement-pricing

Your own site · 80×15
<a href="https://agentmods.dev/skills/anotb/management-consulting-plugin/engagement-pricing"><img src="https://agentmods.dev/badge/skills/anotb/management-consulting-plugin/engagement-pricing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 819 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00045 $0.00819
Opus 5 $0.00023 $0.00409
Sonnet 5 $0.00009 $0.00164
Haiku 4.5 $0.00005 $0.00082

Measured 2d ago against content hash a23555a9b031, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

engagement-pricing scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/engagement-pricing/SKILL.md · 48 lines

How it starts

The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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.

Read the full file on GitHub · 48 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago Changed · -219 lines · -55 tokens per session a23555a9b031
  2. 10d ago First seen · 267 lines · 100 tokens per session scan A 32e97fd66e08

Subscribe to this mod's changes

engagement-pricing is a skill published in the GitHub repository anotb/management-consulting-plugin (52 stars, last pushed 4d ago), licensed MIT. It adds 45 tokens to every session and 819 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.