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

No annotations are provided, so the description carries the full behavioral burden. It adds meaningful traits beyond the schema: results are 'ranked by real community engagement, not by advertising,' unknown filter names are an error, and the recommended recovery is to list the taxonomy vocabulary first. This gives an agent important runtime expectations.

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 dense sentences with no filler. The purpose and usage trigger are front-loaded, followed by ranking behavior, filter validation, and output fields. Every sentence earns its place.

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?

Given seven optional parameters, no annotations, and no output schema, the description covers the main operational concerns: when to call, how filters are validated, error risk, ranking behavior, and the URL fields on returned products. It omits a few details like exact response shape or result-count behavior, but it is largely complete for an agent to invoke correctly.

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 coverage is 100%, so the baseline is 3. The description adds valuable parameter semantics by tying filter values to appboard_browse_taxonomy names, warning that unknown names are errors, and advising the agent to list vocabulary first. This is genuinely useful context beyond the schema's per-parameter descriptions.

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?

The description opens with a specific verb and resource: 'Search AppBoard for software products by need, category, use case, platform, audience or pricing model.' It names the entity type and the relevant search dimensions, and the real-world phrasing 'a free email API' makes the tool's intent unmistakable to an agent.

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 description explicitly says 'Use this whenever the user asks what tool to use for a job,' giving clear when-to-use guidance. It does not, however, state when not to use it or contrast it with siblings like appboard_alternatives_to or appboard_trending, so it stops short of full alternative routing.

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