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

Beyond the annotations (readOnly, idempotent, openWorld, non-destructive), the description discloses that results are checked live today with specific states (up, moved, parked, gone, login first, submit form), ranked by Tranco popularity, sourced from the awesome-submitlist catalog, that failures return an error with a run ID, that an APIFY_TOKEN is required, and that billing is per place row. This is exactly the kind of context annotations cannot convey.

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 purpose is front-loaded in the first clause, and the subsequent sentences cover returns, data source, error handling, auth, and billing without filler. The first sentence is dense and long, but virtually every detail is load-bearing for an agent deciding whether to call this billed tool.

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 14-parameter, no-output-schema tool, the description covers what comes back (link, price, dofollow status, audience, rules, fit score, live status), how it is ranked, where the data comes from, and the cost/auth/error behavior. An agent has everything needed to decide and 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 description coverage is 100%, so every parameter is already documented with defaults and enums. The description adds only marginal parameter meaning – it implies product_description drives the fit score and that GitHub lists are optional – but says nothing about keywords, categories, state_key/only_new, max_rows, proxy_mode, or include_rank beyond what the schema already states. Baseline 3 is appropriate.

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 ('Build a ranked list of places to submit a product launch') and enumerates the resource types covered (directories, launch sites, newsletters, communities, subreddits, marketplaces, press/review pages, optional GitHub lists). This is far more specific than a restatement of the title and leaves no ambiguity about what the tool produces.

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 gives a clear usage context – describe the product and receive a ranked submission list with live status – and notes the tool is read-only and requires an APIFY_TOKEN. It does not state when not to use the tool, but with no sibling tools there are no alternatives to route against, so the missing exclusion is minor.

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