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

Annotations already declare readOnlyHint, idempotentHint and non-destructive, so safety needs no restating. The description adds value beyond them by disclosing what comes back — ranked picks with pricing and real example apps — which matters because no output schema exists.

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

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

Three sentences, front-loaded with the use trigger, followed by the return contract and a compact example call. Every sentence earns its place and nothing is repeated from the schema.

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

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

For a six-parameter read-only recommendation tool with no output schema, the description covers purpose, return contents, and an example invocation. The only gap is that it never explains how the optional filters (platform, experience, budget, preferred_harness) influence ranking or whether they are hard constraints versus ranking signals.

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

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

Schema description coverage is 100%, so every parameter including the enums, the limit bounds, and the budget_usd_month '0 = free tiers' semantics is already documented structurally. The description only echoes the idea parameter through its sample payload and adds no meaning beyond the schema, so the baseline applies.

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

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

States a specific verb (recommend) and resource (AI coding tool / app builder) and names concrete candidates (Cursor, Claude Code, Lovable, Bolt, Replit, v0) so the agent knows the domain instantly. It also states the return shape (ranked picks with pricing and real example apps), which no sibling tool claims.

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

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

The trigger is explicit: use when the user wants to build an app and asks which AI coding tool or app builder to use. It does not, however, contrast itself with nearby siblings like find_tool_for_task or compare_tools, so the agent must infer the boundary from names alone.

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