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

With no annotations, the description carries the full burden and does real work: it discloses row contents, warns that 'Provider claims are not independently observed listing links,' and states that 'Blank/unknown stays unknown' rather than being inferred. It omits return shape, result volume, and pagination behavior for a 10-param listing tool.

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?

Purpose and dataset are front-loaded in the first sentence, and the subsequent sentences are substantive caveats rather than filler. It is slightly dense and run-on (mixing row content, evidence caveats, and workflow advice), but almost every clause 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?

For a 10-parameter tool with no output schema and no annotations, the description covers data caveats and one recommended filter but leaves much of the filtering surface and the return shape unexplained. It is adequate to call the tool, but not complete enough to predict results.

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 only 40% across 10 params, so the description must compensate, and it partially does: it explains checked=true ('source-backed eligibility and free-tier options; not guaranteed approval') and the reliability semantics behind link_evidence values such as provider_claim and unknown. However, eight other filters (query, free, dofollow, link_type, product_type, requires_account, ai_agent_friendly, badge_requirement) get no clarification beyond their names/enums.

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 and resource ('List directories and listing sites where an indie product can be submitted') plus the data provenance (open launch-directories dataset, CC BY 4.0). The resource is narrow enough to separate it from siblings like list_categories or search_projects, and it names run_launch_check as a companion step.

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?

Gives concrete usage guidance: 'Use checked=true for source-backed options' and 'Run run_launch_check on the product site before submitting,' which places it in a workflow. It lacks any when-not-to-use guidance or explicit contrast with the other list/search siblings, so it stops short of a 5.

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