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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds no behavioral context of its own: nothing about AI inference cost, latency, whether the input dataset is mutated, or what a 'fit score' represents. It largely restates the title.

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?

The first sentence is duplicated verbatim, which is pure waste in a four-sentence description. The useful content ('Paste a dataset ID') is buried at the end rather than front-loaded.

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 tool with a nested input object, no output schema, and only two annotation hints, the description should say more about the accepted input shape and what the returned fit score means. It conveys the gist but leaves the agent guessing on specifics.

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 one genuinely useful nugget, 'Paste a dataset ID', which tells the agent the input is an Apify dataset identifier rather than raw domains, but it gives no format, prefix, or example.

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 states a specific transformation: scraper results in, tech stacks plus fit scores out. That is a clear verb+resource, but it never distinguishes itself from near-neighbors like b2b_company_enrichment or google_maps_lead_enricher, which plausibly consume the same Maps/LinkedIn output.

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?

It hints at the upstream context (works with any Maps or company scraper output) but gives no when-to-use vs when-not guidance and names no alternative tool. An agent cannot tell from this text whether to route to this or to a sibling enricher.

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