AI Tool Directory

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral detail: it returns a status ('active, deceased, or acquired'), date/cause if shut down, and live alternatives. No contradictions; the description enriches the annotation information.

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 sentences, highly focused, and front-loaded with the purpose. Every phrase earns its keep—no fluff, no repetition of 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?

Given the tool has one simple parameter, no output schema, and rich annotations, the description fully covers what an agent needs: what the tool does, what it returns, and when to use it. No gaps.

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% with a clear description and example for the single parameter 'tool'. The description does not add additional parameter semantics beyond what the schema already provides, so baseline rating of 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 uses a specific verb ('Check'), a concrete resource (tool status), and explicitly lists return categories (active, deceased, acquired). It distinguishes itself from siblings like search_tools and get_tool by focusing on lifecycle status, so an agent can easily tell when to use this tool.

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 provides a clear usage context: 'Use this before recommending a tool to avoid suggesting one that no longer exists.' While it gives a when-to-use, it does not explicitly mention when not to use it or compare to alternatives, but the context is strong enough.

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 description adds behavioral context beyond annotations by specifying the returned fields (profile details and head-to-head verdict when available). Annotations already indicate it's read-only and idempotent, and the description reinforces that with the comparative, non-destructive nature.

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 sentences, concise and well-structured. Every word serves a purpose: the first states the core function, the second details the output. No filler or redundancy.

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?

Given the tool has two simple string parameters and no output schema, the description adequately explains the purpose and return values. It covers what the agent needs to know, though it could mention handling of invalid slugs or empty results for completeness.

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 input schema already provides full descriptions for both parameters (slugA, slugB) with 100% coverage. The description only mentions 'by their directory slugs,' which adds no new semantic detail beyond the schema, so a baseline score of 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 clearly states the tool's purpose: comparing two AI tools by directory slugs. It specifies the action (compare), the resource (two AI tools), and the method (by slugs). It also details the return fields, distinguishing it effectively from siblings like get_tool or search_tools.

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 implies when to use the tool (for comparing two tools), but it does not explicitly state when not to use it or mention alternatives. It lacks guidance on choosing between this and sibling tools like find_alternatives or get_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 indicate safe read operation (readOnlyHint, idempotentHint, destructiveHint false). The description adds behavioral nuance: returns live replacements if the tool has shut down, enhancing transparency.

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, each carrying essential information. Front-loaded with the core action, followed by a key conditional. No redundant or unnecessary content.

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 tool with one parameter and no output schema, the description covers primary behavior and a notable edge case. Could mention output format but not critical.

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% for the single parameter 'slug', which is well-described. The description mentions 'by its directory slug' but adds no new semantic meaning beyond the schema.

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 clearly states the verb 'find' and resource 'curated alternatives', with a specific means 'by directory slug'. It distinguishes from siblings by highlighting the alternative-finding function, and includes a conditional behavior for shut-down tools.

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 usage example: 'Good for "what should I use instead of X" questions.' This gives clear context, but does not explicitly state when not to use or contrast with siblings.

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, openWorldHint=true, idempotentHint=true, destructiveHint=false. The description adds value by listing the exact data returned (description, pricing, features, verdict, rating, verification date, lifecycle status, URL), providing behavioral context beyond safe read.

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 a single sentence that front-loads the action ('get the full profile') and lists key data fields efficiently, with no wasted words.

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?

Given the simple input (one required slug) and no output schema, the description fully covers what the tool returns, including all major fields, making it complete for an agent to understand the tool's value.

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?

With 100% schema coverage, the description adds an example slug format and hints that it comes from search_tools, making the parameter's purpose and origin clearer than the schema alone.

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 clearly states the tool's purpose: to get the full profile of one AI tool by its directory slug, listing specific fields (description, pricing, key features, verdict, etc.). It differentiates from siblings like search_tools and list_tools by targeting a single tool by slug.

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 mentions the slug comes from search_tools, implying a typical workflow, but does not explicitly state when to use this tool versus alternatives like compare_tools or when not to use it. Still, the usage context is clear.

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, idempotentHint, openWorldHint, and destructiveHint=false. Description adds that tools are 'top-rated' and 'active', which is useful context. However, it does not clarify ranking criteria or behavior when both category and role are provided.

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 efficient sentences: first defines the action and filters, second gives example use cases. No redundant words or information.

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?

Given the 4 optional parameters and no output schema, the description covers the core function and provides examples. It lacks details on sorting, pagination, or category-role interaction, but with extensive annotations, the information gap is minor.

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 has 100% description coverage for all 4 parameters. Description restates that filtering by category/role and pricing is possible, but adds no new semantic detail beyond what the schema provides. Baseline of 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?

Description clearly states the verb 'list' and resource 'top-rated active AI tools' with scope (category/role) and optional pricing filter. Distinguishes from siblings like search_tools (general search) and get_tool (single tool).

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 concrete example queries ('what are the best AI tools for sales', 'free tools in <category>'), which implicitly guide when to use. Does not explicitly exclude alternatives or mention when not to use, but the context is clear for an agent.

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, openWorldHint, idempotentHint, and destructiveHint. Description adds beyond: hybrid semantic search, ranking, specific return fields. No contradiction.

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, no filler. First sentence explains function, second provides usage guidance. Efficiently front-loaded with key information.

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?

Return fields are listed, but no mention of pagination or ordering details beyond 'ranked.' Given 2 params and no output schema, description covers essential aspects for a search tool. Could mention limit enforcement or result ordering.

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 baseline is 3. Description does not add significant meaning beyond schema descriptions; 'hybrid semantic search' gives search behavior context but not parameter-specific insight.

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?

Description clearly states the tool searches a catalog of 2,000+ AI tools with hybrid semantic search, and specifies returned fields (slug, description, pricing, rating). It differentiates from siblings like get_tool (full detail) and list_tools (likely unranked listing).

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?

Explicitly advises 'Use this to discover tools, then get_tool for full detail,' providing a clear workflow. Lacks explicit when-not-to-use or direct comparisons to siblings like find_alternatives or compare_tools, but still offers strong guidance.

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