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should_apply

GrantIQ should_apply: opinionated apply / don't-apply decision for a specific grant. Returns a verdict (yes / borderline / no), confidence (0-1), specific blockers, an effort estimate with confidence band, competition-risk label (or 'unknown' when funder data is absent), and the structured evidence behind it. Requires the caller's profile to be set via a prior find_opportunities call or web sign-up.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
grant_idYesThe grant id (UUID) to evaluate. Typically returned in a prior search or find_opportunities call.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It adds meaningful behavioral context by describing the decision output, the 'unknown' competition-risk case when funder data is absent, and the profile requirement. It does not disclose side effects, rate limits, or error modes, but for a read/evaluate tool this is a moderate gap.

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 sentences: the first defines the tool and lists all outputs, the second states the prerequisite. It is front-loaded, avoids repetition, and every clause contributes to the agent's understanding.

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?

Given the tool's moderate complexity and the absence of an output schema, the description thoroughly covers the purpose, return values, an edge case (unknown competition risk), and the prerequisite. Minor gaps remain around error conditions or confidence computation, but these are not essential for tool selection and invocation.

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 coverage is 100% and the schema already explains grant_id as a UUID typically returned from prior search calls. The description adds a related prerequisite about the caller's profile, but it does not significantly enhance the parameter understanding beyond what the schema provides, meeting the baseline.

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 clearly states the tool's function: 'opinionated apply / don't-apply decision for a specific grant.' It explicitly lists the returned verdict, confidence, blockers, effort estimate, competition-risk label, and evidence. This verb+resource+scope wording distinguishes it from sibling tools like search or explain_opportunity.

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

Usage Guidelines3/5

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

The description states a prerequisite ('Requires the caller's profile to be set via a prior find_opportunities call or web sign-up') which implies usage after profile setup, but it does not explicitly say when to use this tool instead of alternatives or mention exclusion criteria. The context is clear but not comparative.

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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