How It Spread

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so safety is covered. The description goes further by disclosing plan-dependent response content: free accounts receive every event while Pro unlocks the playbook, sourced numbers and sources — a behavioral trait an agent cannot infer from the annotations.

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, front-loaded with the resource and its returned artifacts, with no filler. The second sentence is dense but each clause carries distinct information about what is and isn't available.

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?

There is no output schema, so the description carries the return-value burden and does so well by naming the timeline stages, Spread Score, citation and tier-gated extras. It omits failure behavior (e.g. unknown slug) and any pagination/size note, which keeps it short of a 5 for a read tool.

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% and the single slug parameter is already documented as 'The case slug from search_cases'. The description adds no format, casing or validity detail beyond that, so the baseline 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?

States a specific resource (one case) and enumerates its payload — dated spread timeline, Spread Score, citation, plus tier-gated playbook and sources. The singular 'One case' implicitly contrasts with the list-shaped sibling search_cases, but no sibling is named, so the distinction is inferred rather than stated.

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?

The description contains no when-to-use or when-not-to-use guidance and never mentions search_cases or list_mechanics. The only routing hint — that the slug comes from search_cases — lives in the input schema, not the description, so an agent gets no in-description workflow direction.

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 the safety profile (readOnlyHint=true, destructiveHint=false) and openWorldHint=false. The description adds non-obvious behavioral context beyond that: the vocabulary is closed/exhaustive and each entry includes a definition plus a count of cases using it, which tells the agent this is a canonical reference, not a filtered sample.

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 sentence with zero padding, front-loading the key property ('closed vocabulary') and then the payload (definitions + case counts). Nothing redundant.

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 zero-parameter list tool with no output schema, the description supplies the essential return-value context (definitions and usage counts) that would otherwise be missing. It could go slightly further by noting whether counts are filtered or absolute, but it is sufficient to call the tool 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?

The tool takes zero parameters, which sets the baseline at 4. No parameter meaning needs to be conveyed, and the description's job is purely to characterize the returned content.

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 names the resource (spread mechanics) and states exactly what each entry carries: a definition and a case-usage count. It is clear what the tool returns, though it never explicitly uses a listing verb or references the siblings get_case/search_cases, so an agent gets no direct differentiation cue beyond the distinct resource name.

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 statement and no mention of alternatives. Usage is only implied: calling this to discover the closed vocabulary of mechanics before interpreting or filtering cases. Adequate inference is possible, but the description does no routing work.

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 declare readOnlyHint and openWorldHint=false, so safety is covered; the description adds real value beyond that by disclosing the return payload (Spread Score, dates, platforms, mechanics, image URL, citable case URL), which matters because no output schema exists.

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 dense sentences: capability and filter axes first, return contract second. Every clause carries information and nothing is repeated from the 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?

With no output schema, the description responsibly covers the return fields an agent needs to cite results. Minor gaps remain around result count/pagination and unstated default limit, but overall it is sufficient to invoke the tool 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 60%, and the description's 'by text, kind, mechanic or platform' maps to the query/kind/mechanic/platform params but adds no syntax or semantics beyond them; the limit param (default 10, max 50) is undocumented in both, leaving a gap the description does not close.

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 (Search) and resource (the How It Spread library of viral cases) and enumerates the four filter dimensions (text, kind, mechanic, platform), which lets an agent distinguish it from get_case (single fetch) and list_mechanics (taxonomy listing) without reading schemas.

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?

The filter axes imply how to narrow a query, but there is no explicit when-to-use/when-not guidance and no routing to siblings such as 'use get_case once you have a case URL' or 'call list_mechanics to resolve a mechanic id' — that pointer appears only in the schema, not the description.

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