Agent Distribution

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds that the read returns live coverage, preflight pricing, and limits, which is useful, but says nothing about freshness, auth requirements, or whether preflight pricing has side effects.

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?

A single front-loaded sentence with no filler. It is arguably too terse for terms like 'coverage' and 'preflight pricing', but every word carries information and nothing is wasted.

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?

An output schema exists, so return values need not be spelled out, and annotations carry the safety profile. However, the description leaves the meaning of 'coverage' and the relationship to plan_distribution undefined, which for a zero-param info tool is a noticeable gap.

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 the baseline of 4 applies; there is nothing semantically to document. The description correctly implies the call is argument-free.

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 gives a clear verb ('Read') and names the specific content returned: coverage, preflight pricing, and release limits. It is concrete enough to distinguish from a generic info tool, but it never mentions the sibling plan_distribution or clarifies the boundary between reading service info and planning a distribution.

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 indication of when to call this versus plan_distribution, no prerequisites, and no exclusions. The agent is left to infer usage entirely from the name and the list of returned data.

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 establish the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description earns credit for adding behavior not covered there: the output is a plan/preview, it is built from public data, and it explicitly does NOT publish or verify URLs. That 'does not X' disclosure prevents misreading this as an execution tool, though no permission-gathering flow is described beyond the returned 'missing permissions'.

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 tight sentences, fully front-loaded: the action first, then the return value and the scope exclusion. Every clause carries information; nothing is redundant with the title or schema.

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?

An output schema exists, so return values need not be explained and the readOnly/idempotent annotations cover safety. The remaining gap is the wholly undescribed 'product' object, which is the only input and is left to the agent to reverse-engineer from the schema alone.

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 0% and the single 'product' parameter is a nested object whose required fields (name, website, description, kind) and optional fields (mcp_url, a2a_card_url) are entirely undocumented. The description only gestures at 'public product data', supplying no field-level meaning, formats, or length constraints, so it fails to compensate for the coverage gap.

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 ('Build a free plan') plus what it consumes ('from public product data') and produces ('channel candidates and missing permissions'). The scope boundary 'does not publish or verify URLs' sharpens it further, but it never differentiates itself from the sibling get_service_info, so an agent must infer the split.

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?

Usage is implied rather than stated: the agent can infer this is the tool for generating a distribution plan from a product. There is no explicit when-to-use, no mention of get_service_info as an alternative, and the only exclusion ('does not publish or verify URLs') bounds the operation rather than routing between tools.

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