Datacircle

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world behavior, so safety is covered. The description adds genuinely useful context beyond that: each returned item carries plan and provider counts, which matters because there is no output schema declaring the return shape.

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?

Two short sentences with no filler; the purpose and the returned fields come first and the routing hint second. 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?

With no output schema, the description correctly compensates by naming what each entry contains (plan and provider counts) and how to proceed afterward. Minor gaps (ordering, pagination, whether the list is exhaustive) remain but do not block correct invocation.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 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+resource (list the GTM APIs) and what each entry contains (plan and provider counts), and explicitly names the sibling tool search_plans, so the agent can distinguish the two. The phrase 'on Datacircle's sheet' is slightly vague about the data source but does not obscure the purpose.

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?

Provides a workflow handoff ('Pass an API's name to search_plans'), which implies this tool is the discovery step that precedes plan lookup. However, it never states when to call this tool directly or any exclusion conditions, so usage is only implied rather than spelled out.

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

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

Annotations already cover readOnly, idempotent, non-destructive and closed-world, so safety is handled. The description adds genuine behavioral context beyond that: it discloses the row-per-plan-per-call return shape and pagination semantics ('total counts every row found, plans holds up to limit of them from offset'), which matters since there is no output schema.

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?

Two content sentences plus a docs pointer, with the return structure front-loaded. The first sentence is long and comma-dense, but every clause carries information and nothing is redundant filler.

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?

With no output schema, the description appropriately carries the return-value burden, enumerating the row keys and pagination fields (total/plans) and linking to the field reference. The one soft spot is the vague phrase 'each call,' which is never defined, but overall an agent has enough to invoke and interpret 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 description coverage is 100%, so the schema already documents all five parameters (including the api enum and sort/limit/offset defaults). The description reinforces limit/offset paging behavior but adds little syntax or format detail beyond what the schema provides, so the baseline of 3 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?

The title and description establish that this searches API plans, and the body specifies the resource in detail: rows, one per plan per call, with provider, plan, billing, price, score, rate limits, speed, and returned fields. It's clear what the tool surfaces, though the text spends more energy on return structure than on stating the verb+resource action, and it never names the list_apis sibling to differentiate scope.

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?

There is no explicit when-to-use or when-not-to-use guidance, and no mention of the list_apis alternative or how the two relate. Usage must be inferred from the optional filters (api, query, sort).

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