How It Spread

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

Beyond the readOnly/openWorld annotations, the description discloses that auth-gated fields return locked and that a case URL is included for the full record — real behavioral context an agent can't get from annotations. It stops short of describing missing-case or error behavior.

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 sentences, front-loaded with what the record contains, then the access caveat. Little waste; the parenthetical timeline stages are dense but purposeful.

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 read-only single-record tool with no output schema, the description covers return content (timeline, score, citation) and the locked-field caveat. Only edge cases like unknown slugs are unaddressed.

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% and the single slug parameter is fully documented in-schema. The description only reinforces provenance ('from search_cases') without adding format or resolution details, 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?

The description states a specific verb+resource ('One case') and enumerates what comes back: dated spread timeline stages, Spread Score, and citation. It's clearly a single-record read, distinct from search_cases, though it doesn't name the sibling explicitly.

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: you fetch one case, and the slug must come from search_cases, which gives an implicit routing hint. There's no explicit when-to-use versus list_mechanics or search_cases, and no stated preconditions.

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?

The annotations already establish that this is a safe, read-only, non-destructive, closed-world operation. The description adds useful context about the library contents and the fields returned for each case, including Spread Score, dates, platforms, mechanics, image URL, and citation URL. It does not disclose ordering, pagination, default limit behavior, empty-result behavior, or rate limits, so the behavioral disclosure is helpful but incomplete.

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 description is two tightly written sentences with no wasted wording. The search capability and scope are front-loaded, followed by the return fields. Every sentence carries useful information for an agent deciding whether and how to call the 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?

There is no output schema, so the description appropriately explains the returned fields, including the case URL for citation. It also names the library and the searchable dimensions, which is enough for an agent to invoke the tool correctly in most cases. It could be stronger by clarifying the relationship to get_case and list_mechanics, or by explaining limit and ordering behavior.

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%, so the schema already documents query, mechanic, and platform, and the description mostly restates those facets as 'text, kind, mechanic or platform'. It adds some clarity that 'text' maps to free-text search and that results are cases, but it does not explain the kind enum or the limit parameter beyond what the schema provides. A 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 states a specific verb and resource: searching the How It Spread library of viral cases, with examples of case types and search facets. It is immediately clear this is a discovery/search tool rather than a single-record fetch. It does not explicitly distinguish itself from the sibling tools get_case or list_mechanics, so it falls short of a 5.

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 by the listed search dimensions (text, kind, mechanic, platform), which tells an agent how to query the library. However, there is no explicit when-to-use guidance, no when-not-to-use guidance, and no mention of get_case or list_mechanics as alternatives. The agent must infer that this tool is for discovery and get_case is for retrieval by identifier.

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