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Evaluate project scope

evaluate_project_scope

Estimates project scope from interview answers, then finalizes and stores the confirmed scope to advance the session.

Instructions

Draft or finalize the project's scope. Without finalize, returns a heuristic guess at the scope from the interview answers. With finalize: true and data, stores the human-confirmed scope and advances the session.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
finalizeNo
session_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does a decent job: it discloses that the tool can return a heuristic guess, can store data, and advances the session. It stops short of describing return shape, whether draft mode mutates state, or whether finalize overwrites an existing scope.

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?

The description is two tight sentences with no filler. The draft/finalize distinction is front-loaded, and each clause adds a distinct behavioral fact.

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

Completeness2/5

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

The tool has nested parameters, no output schema, and no annotations, so the description alone must make it fully usable. It covers the core flow but omits practical details: what the heuristic guess returns, what data fields are expected for finalization, and how the session advancement affects subsequent tool calls.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for the parameter schema. It explains that finalize:true plus data triggers persistence, but it does not explain the meaning of the many nested data fields (one_liner, platforms, estimated_scale, etc.) or what session_id must look like. This leaves a large semantic gap for agents choosing how to populate the input.

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

Purpose5/5

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

The description names the resource ('project's scope') and gives a specific, dual-mode verb: 'Draft or finalize.' It clearly distinguishes itself from sibling lifecycle tools like propose_architecture and generate_roadmap by focusing on scope capture and confirmation.

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

Usage Guidelines4/5

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

The description gives clear context for use: use it to produce a draft heuristic from interview answers, then use it with finalize:true to persist the human-confirmed scope. It does not explicitly name alternatives or state when not to use the tool, but the mode-based guidance is sufficient for basic routing.

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