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MVP Timeline ROI Calculator

calculate_mvp_timeline_roi
Read-onlyIdempotent

Compares a Holston AI fixed-price 2–4 week build against a traditional ~6-month build. Returns build costs, labor savings captured, cost of delay, developer-weeks freed, payback week, and a month-by-month cumulative net position over the analysis window.

Input Schema

NameRequiredDescriptionDefault
dev_headcountYesNumber of in-house developers who would be assigned to a traditional build.
project_scopeYesTarget project scope. Websites: website_launch (up to 5 pages, 5 days) | website_growth (up to 10 pages, 10 days) | website_commerce (online store, 15–20 days). Small app: small_app (2 wks). Apps & AI agents: lean (2 wks) | standard (3 wks) | complex (4 wks).
automation_rateNoFraction of the manual hours eliminated once the software is live, 0–1 (default 0.7).
dev_annual_cost_usdNoFully loaded annual cost per in-house developer (default $150,000).
manual_hourly_cost_usdNoFully loaded hourly cost of the staff doing the manual work (default $45).
analysis_horizon_monthsNoLength of the comparison window in months (default 6).
holston_fixed_price_usdNoA specific fixed-price quote from Holston AI. If omitted, the scope's standard starting price is used.
traditional_timeline_weeksNoDelivery timeline of the traditional path in weeks (default: 6–12 for websites, 26 ≈ 6 months for apps/agents).
traditional_vendor_cost_usdNoExternal agency/vendor spend on the traditional path, on top of in-house dev time (default 0).
holston_internal_involvementNoShare of the in-house dev team's time needed during a Holston build, 0–1 (default 0.1).
manual_process_hours_per_weekYesHours per week your team currently spends on the manual process the software will replace.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint and closed-world, so the safety profile is covered. The description adds real value by enumerating the computed outputs (build costs, labor savings, cost of delay, payback week, cumulative net position), which matters since there is no output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no waste, with the comparison framing front-loaded and the return values listed second. Every clause carries information an agent would otherwise have to guess.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 11-parameter read-only calculator with no output schema, the description covers what the tool computes and what comes back. The main gap is the absence of routing guidance relative to sibling cost/quote tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so every parameter including defaults and enum scopes is already documented. The description adds no syntax or meaning beyond the schema, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (compares) and resource (Holston AI fixed-price build vs traditional build ROI), and enumerates the outputs produced. It is clearly distinct from siblings like build_quote and calculate_manual_work_cost, though it never names or contrasts them explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to choose this over build_quote or calculate_manual_work_cost, nor any prerequisites such as needing a fixed-price quote first. Usage must be inferred entirely from the title and parameter list.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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