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Market Sizing Sanity Check
Build and reconcile independent market estimates, audit units, expose uncertainty, and test decision thresholds.
$5
Works with the AI Agents you already use
Market Sizing Sanity Check
Example session with this skill installed
Fictional training scenario; no real client data.
Use $market-sizing-sanity-check to audit our claim that the UK mid-market compliance workflow software market will be worth £50m in year three. Show an independent cross-check and tell us whether a £4m revenue target is credible.
- Read your context and instructions
- Compiled the market sizing sanity
Fictional worked illustration from the public repository, not a recorded agent run or a verified client outcome. Any additional figures, thresholds and market signals are scenario assumptions, not observed results. No generated PDF or finished deck is included.
Sample output
All inputs are fictional. The calculation fixture is example-calculations.json; the full method is in the worked example.
Executive answer
The model gives a £31.8m year-three base and a £13.5–52.4m scenario range. £50m is near the upside case, not a supported base. The £20m entry threshold fails in the downside, and the £4m entrant target requires 397 active customers versus 240 supported by current sales capacity.
Primary estimate
7,500 eligible firms
x 70% workflow fit
x 60% paid adoption
x 14 seats per firm
x £720 annual realized price
= £31.752m annual supplier revenue (approximately £31.8m)
The units reconcile to pounds per year. Paid adoption and seats per firm are the least certain drivers.
Independent cross-check
4 scaled providers x £5.0m UK revenue
+ 8 specialists x £1.2m UK revenue
= £29.6m current supplier revenue
The cross-check uses provider revenue bands rather than customer and seat assumptions. The base is 7.27% above it, but the figures describe different periods. No growth or scope bridge has been supplied, so retain the wide scenario range rather than manufacturing convergence.
| Calculation | Exact result |
|---|---|
| Low year-three supplier revenue | £13.5135m |
| Base year-three supplier revenue | £31.752m |
| High year-three supplier revenue | £52.416m |
| Current supply-side revenue | £29.6m |
| Customers required (rounded up) | 397 |
| Customers supported before churn | 240 |
| Revenue supported before churn | £2.4192m |
Decision sensitivity
| Assumption | Decision threshold | Current evidence | Implication |
|---|---|---|---|
| Serviceable market | £20m | £13.5–52.4m; £31.8m base | Base passes; downside fails |
| Customers required | About 397 | 240 supported by current capacity | Revenue plan fails |
| Paid adoption at other base inputs | 37.79% | 60% fictional base | Validate adoption and seats before investment |
Next evidence
Run 15–20 buyer interviews, verify bundled-module revenue, and rebuild the channel plan around a credible path to 400 active customers before approving full entry investment.
Connects securely to your tools. The creator never sees your data.
About this skill
Build a defensible market range from explicit boundaries and units. Use an independent cross-check, reconcile scope and period differences, and show which adoption or capacity assumptions change the decision.
What you get
SKILL.md, sizing-method reference, fictional worked calculation example, agent metadata and MIT LICENSE.
Primary deliverable: Triangulated market range and sensitivity audit.
How to use
Unzip the package into your compatible agent's skills folder. Ask the agent to use market-sizing-sanity-check and supply your decision, evidence and constraints. Review the result before acting on it.
Open source and purchase transparency
Version 1.1.0. The same skill is available free under the MIT license in Consulting Skills Lab. This optional $5 purchase supports the creator and provides the packaged download through Agensi; it is not exclusive content and does not include an AI-model subscription, hosted service, consulting engagement or guaranteed future support. The MIT license is included in the ZIP.
Example and limits
The listing demo is a fictional worked illustration, not a recorded agent benchmark or a real customer result. Read the public example.
Does not supply proprietary market data or verify inputs automatically. A large TAM does not establish serviceable or obtainable demand. Estimates and forecasts remain conditional on supplied sources, scope and assumptions; specialist validation may be required.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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