FindAIforWork

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds genuinely new behavioral information: unknown slugs are surfaced in a "missing" field rather than silently resolved, which tells the agent how partial failures behave.

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 zero filler; the cardinality constraint is front-loaded and the edge-case behavior follows. Nothing redundant with the schema or annotations.

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 must carry return-value context, and it does partially by naming the missing field for unresolved slugs. It doesn't say what a successful comparison result actually contains (what fields are compared), leaving a minor gap for a tool with no output schema.

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 minItems/maxItems bounds (2-5) are already enforced structurally, so the baseline is 3. The description adds semantic value by explaining what happens to invalid slug values (reported in missing, not guessed), which the schema does not express.

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 ("Compare") and resource ("published tools") plus an explicit cardinality scope ("two to five"). The multi-tool scope cleanly separates it from the singular get_tool sibling without needing to name it.

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 "two to five published tools side by side" phrasing implies when this is appropriate (multi-tool comparison rather than single-tool lookup), but no sibling is named and no explicit when-not guidance is given. Usage is inferable rather than stated.

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=true and openWorldHint=false, so safety is covered; the description adds genuine value by disclosing the return payload (Markdown copy, related tools), which matters since there is no output schema. It omits any note on missing-slug behavior or error handling, keeping it below 5.

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 the resource, key parameter, and return contents in that order. No 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?

For a simple single-parameter read tool with full annotations and schema documentation, the description covers purpose and payload. Without an output schema, a brief note on error/not-found behavior would round it out.

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 documented with an example ('chatgpt'), so the schema does the heavy lifting. The description only restates 'by slug' without adding format or matching rules, matching the baseline 3 for high-coverage schemas.

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?

Specific verb and resource: 'Return the full public listing for one tool by slug', with the payload named (Markdown copy, related tools). It clearly contrasts with list/search siblings by being a single-item fetch, though it doesn't name them 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 only implied: the 'by slug' phrasing suggests calling this after a search_tools lookup, but there is no explicit when-to-use, prerequisites, or pointer to compare_tools/search_tools as alternatives.

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=true and openWorldHint=false, so the safety profile is covered. The description adds real behavioral context beyond that: only "active" categories are returned, and the count reflects published tools only — an implicit filtering rule an agent would otherwise not know. It does not mention ordering, pagination, or empty-result 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?

A single front-loaded sentence with zero waste; the returned fields are packed into the same clause rather than spread across filler text.

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 parameters and no output schema, the description usefully compensates by naming every returned field (slug, description, published tool count) and the active-only filter. Only ordering and volume/pagination expectations are left unstated, which is minor for a zero-arg listing 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?

The tool takes zero parameters, so there is nothing to disambiguate and the baseline is 4. The description correctly adds no spurious parameter talk.

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 a specific verb ("List") and a specific resource ("categories") and enumerates the fields returned (slug, description, published tool count). The resource is wholly disjoint from the sibling tools (compare_tools, get_tool, search_tools), so an agent can differentiate it without opening a schema, though no sibling is named 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?

There is no statement of when to call this versus search_tools or get_tool, and no prerequisites or exclusions. Usage is only inferable from the description of what is returned (a category taxonomy), which is weak guidance for a discovery-type tool.

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, and the description adds useful behavioral context by saying the tool returns a total plus compact summaries rather than full records. It does not cover pagination or auth constraints, but for a read-only search tool this is largely sufficient.

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 only two sentences and front-loads the core action and filters before the return behavior. Every sentence contributes directly to selecting and understanding 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?

With no output schema, the description appropriately states that results include a total and compact summaries. It omits some details such as pagination behavior and what fields a compact summary contains, but it is complete enough for an agent to invoke this search 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 coverage is 100%, so all five parameters are documented in the schema. The description names three of the filter dimensions (free text, category slug, pricing model) but adds no syntax or semantic detail beyond what the schema already provides, so 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 ("Search published AI software listings") plus the supported filter dimensions and return shape. It is clear what the tool does, though it does not explicitly distinguish itself from siblings like get_tool or list_categories.

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 "Search" and the listed filter inputs, but there is no explicit guidance on when to use this versus get_tool or list_categories, nor any exclusions. An agent can infer intent but must decide alternatives on its own.

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