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draft_application_section

Destructive

Generate an AI first-draft for one section of YOUR application, grounded in the funding notice and your org profile, and save it into that section (prior content snapshotted first). Requires a paid API key. This is the only tool that runs the grant writer, so it is metered heavily. Returns the drafted text. Use get_my_application for section_keys.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
section_keyYesWhich section to draft (see get_my_application).
document_typeNoDraft a short Letter of Inquiry ("loi") or a full section ("full"). Defaults to the application's submission stage.
application_idYesApplication UUID.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already mark the tool as destructive (destructiveHint: true) and non-read-only, and the description adds valuable behavioral context beyond that: it snapshots prior content before saving, requires a paid API key, and is heavily metered. It also states the return value ('Returns the drafted text'), covering what the agent can expect.

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 compact and front-loaded: it leads with the primary action and storage effect, then covers cost/metering, return value, and parameter guidance. Every sentence adds necessary information without fluff.

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 a state-changing tool with no output schema, the description is fairly complete: it explains the drafting behavior, the save/snapshot side effect, cost constraints, and return value. It could slightly improve by explicitly contrasting with update_application_section for manual edits, but the core usage is covered.

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 the schema already documents all three parameters. The description adds a small but useful pointer for section_key ('Use get_my_application for section_keys'), but it does not materially expand on document_type or application_id beyond what the schema provides.

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 states a specific action ('Generate an AI first-draft for one section'), identifies the resource ('your application'), and clarifies the side effect ('save it into that section'). It also differentiates from siblings by calling itself 'the only tool that runs the grant writer,' which separates it from update_application_section.

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 usage context: it requires a paid API key, is metered heavily, and should be used for drafting rather than manual edits. It also directs the agent to get_my_application for valid section_keys. However, it does not explicitly state when not to use this tool or name update_application_section as the alternative for manual edits.

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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