There's An AI For That

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

Annotations already establish this as a safe read (readOnlyHint=true, destructiveHint=false, openWorldHint=false), so the bar is low. The description still adds two useful behavioral facts: results are 'public' details only, and returned URLs must be preserved exactly, which is a non-obvious output-handling constraint not encoded anywhere else.

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: the core action first, the URL-preservation caveat second. No filler, nothing repetitive, and the important operating rule is front-loaded rather than buried.

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 single-parameter read tool with an output schema, a complete annotation set, and full schema coverage, the description covers what is needed. It leaves only the company-vs-organization sibling distinction 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 schema field already documents that the slug is the value returned by search_companies. The description only restates 'by slug' without adding format, case-sensitivity, or validity details, so the 3 baseline for fully documented parameters 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 and resource ('Get public details for one AI company by slug'), which is clear and actionable. It does not, however, differentiate itself from the closely named sibling get_organization, leaving an agent to infer how 'company' differs from 'organization' in this dataset.

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?

Saying 'by slug' and having the schema note that the slug comes from search_companies implies a search-then-fetch workflow, but the description itself states no when-to-use condition or alternative. Usage is inferable rather than explicit.

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, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds a real output-fidelity requirement in 'Preserve returned URLs exactly' plus the 'public' scope qualifier, but says nothing about auth, rate limits, or behavior when the slug is unknown.

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, zero filler, with the purpose front-loaded and the output-handling caveat second. Nothing could be removed without losing 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?

With an output schema present, return values need not be described, and annotations cover the safety profile; the single parameter is fully documented in the schema. Only minor gaps remain (no guidance on a missing/invalid slug), so the description is nearly complete for a simple 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 there is a single parameter, so the schema already explains 'slug' as the value returned by search_devices. 'By slug' in the description adds no syntax, format, or constraint detail beyond that.

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 (Get) + resource (AI device details/specifications) with the lookup key named (by slug). This clearly separates it from search_devices and from the get_* siblings for companies, models, etc., though it never names an alternative 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: a single-slug detail fetch naturally follows a search, and the schema note ties the slug to search_devices. The description itself states no when-to-use condition, no when-not, and does not name a sibling alternative.

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 (readOnly, non-destructive, closed-world). The description adds two things annotations cannot: results are limited to 'public' events, and returned URLs must be preserved exactly (implying they are fragile/possibly signed). That is meaningful behavioral context beyond the structured fields.

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, zero filler, with the core action front-loaded and the URL-handling caveat placed as a trailing imperative. Every sentence earns its place.

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 an output schema present, return values need not be explained, and the description correctly covers scope ('public') and the URL-preservation caveat. What is missing is any routing signal relative to search_events, which is the main gap for a low-complexity lookup 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?

Only one parameter and schema description coverage is 100%, so the schema already documents 'slug' and its provenance. The description's 'by slug' adds no syntax, format, or constraint detail beyond the schema; 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 verb ('Get') and resource ('public details for one AI event'), scoped by slug. It is clearly the event variant of the get_* family, though it does not explicitly name or contrast with search_events as an alternative.

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: 'by slug' plus the schema note that the slug comes from search_events tells the agent this is a lookup that follows a search. There is no explicit when-to-use/when-not guidance or statement that this is the only way to fetch a single event.

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, destructiveHint=false, and openWorldHint=false, so safety is covered structurally. The description adds real value beyond that: it signals that only 'public' details are returned and gives an unusual output-handling instruction ('Preserve returned URLs exactly'), which usefully warns the agent not to rewrite returned links.

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, with the core identification clause front-loaded and the output-handling constraint second. Nothing is redundant or padded.

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 an output schema present and annotations covering the read-only safety profile, the description need not explain return values, and it correctly stays brief. It is nearly complete for a one-parameter lookup, though it omits any mention of behavior when the ID does not exist (error/empty result).

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 parameter is fully documented in the schema (including that it is 'returned by search_fundraises'). The description only echoes the 'by ID' idea and adds no format or range detail beyond the schema, so 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 verb ('Get'), resource ('public details for one AI company fundraising round'), and scoping key ('by ID'), which clearly distinguishes it from search_fundraises. The sibling differentiation is achieved only implicitly through 'by ID' rather than by naming the search tool, but an agent can still tell what this does.

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 phrase 'by ID' implies the tool is a single-record lookup that follows a search, which is adequate implied usage. However, no explicit when-to-use guidance or prerequisite (that the ID must come from search_fundraises) is stated in the description itself — that context lives only in the schema parameter description.

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 readOnly, non-destructive, non-open-world behavior, so the safety profile is covered. The description adds real context beyond them: results are limited to 'verified active' investors only, and returned URLs must be preserved exactly, which is a behavioral constraint an agent would otherwise violate.

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, front-loaded with the action and the key, with the URL-preservation caveat placed after. Nothing is redundant or padded.

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-shape explanation is unnecessary, and the annotations carry the safety profile. The description covers the entity scope and the one critical constraint; only failure behavior (e.g., missing/invalid slug or unverified investor) is left unstated.

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 a single parameter at 100% schema description coverage, the schema already documents the slug and its origin. The description adds no format, validation, or edge-case detail about the slug beyond the word 'by slug', 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 verb and resource (get one investor's public details) plus a retrieval key (slug), which clearly separates it from the plural siblings like search_investors. The scope qualifiers 'verified active AI investor' further narrow what will come back, though the description never names search_investors as the counterpart.

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: an agent can infer this is the detail lookup that follows a search. There is no explicit when-to-use/when-not statement, and the dependency on a slug from search_investors 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.

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

Annotations already declare readOnlyHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is covered. The description adds one useful behavioral note ('Preserve returned URLs exactly'), which signals output-handling expectations, but nothing about scope limits beyond 'public' or failure behavior when a slug is unknown.

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 compact sentences with zero filler; the core purpose is front-loaded and the URL-preservation instruction follows, each earning its place.

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 one-parameter lookup with an output schema and full annotation coverage, the description is nearly sufficient. It clarifies the lookup is limited to public data and how to handle returned URLs, though it says nothing about behavior for invalid or missing slugs.

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?

There is a single parameter with 100% schema description coverage, and the schema already explains that the slug is the identifier returned by search_mcps. The description adds no format, case-sensitivity, or validation detail beyond that baseline, so this stays at the standard 3.

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 ('Get public details for one MCP server') scoped by slug, so an agent knows exactly what it retrieves. It does not differentiate itself from the many parallel get_* siblings (get_tool, get_model, get_repository), relying on the noun to do the routing work.

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 schema notes the slug comes from search_mcps, which hints at a search-then-fetch flow, but the description never says when to call this versus search_mcps or other get_* tools. No explicit when/when-not guidance is present.

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, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds two real behavioral facts beyond that: only public details are returned (scope limitation) and returned URLs must be preserved exactly (fidelity constraint for downstream use).

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, no filler. The core operation leads and the URL-preservation caveat follows; both carry information an agent needs.

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 annotations cover safety. The description supplies the scope caveat ('public details') and the URL handling instruction, leaving little an agent needs missing; only an explicit sibling routing statement is absent.

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?

Single parameter with 100% schema description coverage, so the schema fully documents 'slug' as the value returned by search_models. The description adds no format, casing, or sourcing detail beyond the schema, so 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 verb and resource ('Get public details for one AI model') plus the keying mechanism ('by slug'), which cleanly separates it from the search_* siblings. It does not explicitly name an alternative like search_models, so it falls just short of the top band.

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 'by slug' phrasing implies the prerequisite (you must have a slug, which the schema says comes from search_models), but the description itself never states when to use this versus search_models or get_company-style siblings. Usage is inferable rather than stated, which is the definition of minimum viable.

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, destructiveHint=false, and openWorldHint=false, so safety is covered. The description adds a non-obvious behavioral constraint beyond the annotations: only 'public' details are returned, and callers must 'preserve returned URLs exactly' — a real instruction about handling output that structured fields do not convey.

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, front-loaded sentences with no filler: the purpose first, then the output-handling caveat. Every clause earns its place.

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 described, and the single required parameter is fully documented. The only remaining gap is the lack of differentiation from the numerous get_* siblings, which would help an agent over a larger toolset.

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% for the single parameter, and the schema already explains that the slug is 'returned by search_organizations'. The description adds only the word 'organization' as qualifier, so it neither compensates for a gap nor adds meaningful syntax or format detail. 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 verb ('Get') and resource ('public details for one AI organization'), plus the keying parameter (slug). It is distinguishable from the sibling search_organizations, but among the many 'get_*' siblings (get_company, get_model, etc.) it does not explicitly articulate what makes an 'organization' distinct from those entities.

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 phrase 'by slug' plus the schema note 'slug returned by search_organizations' implicitly chains this after a search, which is useful routing. However, there is no explicit when-to-use statement or when-not guidance relative to the other get_* 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, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds the genuinely useful constraint 'Preserve returned URLs exactly,' but says nothing about rate limits, permissions, 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 short sentences, front-loaded with the core purpose and a distinct behavioral caution. 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?

An output schema exists, so return values need not be explained, and the single required parameter is fully covered by the schema. The description supplies purpose plus the URL-preservation caveat, leaving only minor gaps in usage routing.

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 fully documented in the schema, including its provenance from search_papers. The description's 'by slug' phrasing adds no meaning 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 verb (get), resource (AI research paper), and scope (public details, one published paper, by slug). It implicitly separates itself from search_papers by emphasizing a single paper, though it does not name the sibling explicitly in the description body.

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 slug parameter notes it comes from search_papers, implying the search-then-get workflow, but the description never states when this tool should or should not be chosen over search_papers or the other get_* siblings. Usage is left to inference.

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, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuinely new behavior beyond that: results are public-only data, and returned URLs must be preserved verbatim rather than rewritten.

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, front-loaded with purpose and followed by the one handling constraint; nothing is redundant or padding.

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 is present, so return values need no explanation, and the description covers purpose, key format, and output handling. Only edge cases such as a missing or malformed slug are left 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?

With a single parameter at 100% schema coverage, the schema already documents the 'slug' and its provenance ('returned by search_repositories'). The description adds only the format hint that slug is an owner/repository pair, which is marginal but consistent.

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 ('Get public details for one AI repository') and scopes it to a single-record lookup keyed by the owner/repository slug, which implicitly separates it from the many search_* siblings. It does not name search_repositories directly in the description body, so sibling differentiation is only implicit.

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 singular 'one AI repository by its owner/repository slug' implies lookup-by-known-slug usage rather than browsing, and 'Preserve returned URLs exactly' is output-handling guidance. There is no explicit when-to-use/when-not statement or named alternative, so usage remains inferred.

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 a safe read (readOnlyHint=true, destructiveHint=false, openWorldHint=false), and the description adds two things beyond them: the result is limited to 'public' data, and returned URLs must be preserved verbatim. That URL-preservation constraint is a genuine behavioral caveat not captured in any structured field.

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, front-loaded with the core action; the second sentence is a distinct, actionable constraint rather than filler. Slightly terse on usage context, but 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-value structure need not be explained, and annotations cover the safety profile. For a single-parameter read tool the definition is essentially complete; only an explicit pointer to search_robots for slug discovery is missing.

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 fully documented in the schema (including its provenance from search_robots), so the description adds nothing about parameter format or syntax. 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?

States a specific verb ('Get') and resource ('public details and specifications for one robot') scoped by a single slug, which cleanly distinguishes it from the sibling search_robots. It does not, however, explicitly name that sibling as the lookup path.

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 schema notes the slug comes from search_robots, and the description adds 'Preserve returned URLs exactly' as a post-call handling rule. There is no explicit when-to-use vs when-not-to-use statement or exclusion guidance.

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, destructiveHint=false, and openWorldHint=false. The description adds that results are public details and explicitly warns to preserve returned URLs exactly, which is useful behavioral guidance beyond the annotations. It does not cover auth or rate limits, but the read-only profile is well established.

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, front-loaded with the tool purpose. The URL-preservation instruction is terse and actionable rather than padding.

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 an output schema present, the description need not explain return values. Annotations cover safety, the schema covers the single parameter, and the description covers purpose, sourcing, and a key output-handling caveat. It is nearly complete, though it could note any auth or access constraints.

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 the slug parameter is already fully documented as the task slug returned by search_tasks. The description confirms the tool is keyed by slug but adds no syntax or format detail beyond the schema. Baseline 3 is appropriate when the schema carries parameter semantics.

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: get public details for one TAAFT task category by slug. It also distinguishes this lookup tool from the sibling search_tasks by tying the required slug to search results. An agent can identify exactly what this tool retrieves.

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?

It clearly implies usage after search_tasks by stating the slug comes from that search. There is no explicit when-not-to-use or alternative lookup tool guidance, but the context is sufficient for selection.

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 read-only and non-destructive behaviorcompress. The description adds meaningful beyond-structure value by specifying that two URL fields exist ('url' for the TAAFT page, 'website_url' for the external website) and instructing to preserve returned URLs exactly. This is a valuable behavioral disclosure not captured in the schema or 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 terse sentences with no filler. The first states the core action, the second gives concrete field-level guidance for using the response.

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 single-parameter read-only tool with a 100%-described schema, this is well covered. The instruction to preserve URLs and distinguish the two URL fields partially compensates for the missing output schema, though it doesn't enumerate other response fields or error 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?

The input schema already fully documents the sole parameter 'slug' with the note that it is returned by search_tools, so schema coverage is 100%. The description adds no additional semantic meaning beyond repeating 'by slug'. Baseline of 3 applies since the schema carries the descriptive load.

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 states a specific verb ('Get'), a specific resource ('one TAAFT AI tool'), and the key identifier ('by slug'). The singular phrasing clearly differentiates it from the sibling search_tools, and the mention of 'public details' sets expectations for the response.

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 this is for retrieving a single tool's details by slug, with the schema noting the slug comes from search_toolsörgcu. It clearly establishes context as the follow-up to a search but does not explicitly say 'use search_tools to find the slug first' or exclude other use cases. No explicit exclusions, but the context is clear 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?

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered by structured data. The description adds only the catalog scope ('TAAFT catalog') and that results are companies building AI products; it says nothing about result volume, ranking, or matching behavior. With annotations carrying the safety burden, this is adequate but thin.

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. Every word (verb, catalog, resource, domain scope) earns its place.

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?

Because an output schema exists, return values need not be explained, and the read-only nature is covered by annotations. However, for a search tool with an undocumented 'limit' parameter, the description should say something about result paging or caps; that gap leaves it only minimally complete.

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 only 50%: the 'query' parameter is documented in the schema, but 'limit' (default 20, range 1-50) carries no description anywhere. The description adds no parameter meaning at all, so it fails to compensate for the uncovered parameter.

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) plus a specific resource (companies in the TAAFT catalog) and narrows scope to 'AI products', which separates it from siblings like search_tools or search_models. It stops short of explicitly naming which sibling to prefer, but the resource is unambiguous.

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 gives no when-to-use guidance: it never contrasts this with get_company (single-record lookup) or the many other search_* siblings, nor does it state any prerequisite or context for choosing it. An agent must infer usage from the name alone.

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, destructiveHint=false, and notably openWorldHint=false, so the safety profile is covered. The description adds nothing beyond that: no mention of result shape, pagination, or what 'activity' data is returned. Nothing contradicts the annotations, but the description contributes no behavioral context of its own.

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 short sentence that is front-loaded with the verb, so there is no waste or padding. It loses a point only because the brevity comes at the cost of the clarity noted elsewhere.

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. However, for a search tool with an undocumented limit parameter, no usage routing among 27 siblings, and a vague scope ('AI companies and activity'), the definition leaves an agent without enough to invoke it confidently.

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 only 50%: 'query' is documented in the schema, but 'limit' (default 20, max 50) has no description anywhere. The description mentions no parameters at all, so it does not compensate for the coverage gap or explain how country-name matching works (partial, exact, aliases).

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 verb and resource ('search TAAFT country pages for AI companies and activity'), but the object is muddled — it is unclear whether this returns companies, aggregate activity stats, or country pages themselves. It does not distinguish itself from sibling search_companies or get_country.

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?

No when-to-use guidance, no exclusions, and no routing to alternatives. With 27 siblings including search_companies and get_country, the agent has no signal on why it would pick this tool over those.

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=false and destructiveHint=false, so safety is covered. The description adds nothing further: no note on default result count, pagination, or what an empty/no-match response looks like, so it contributes no behavioral context beyond the structured fields.

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 tight sentence with the verb and scope front-loaded; nothing is wasted. It is arguably under-specified rather than over-long, but the structure itself is clean.

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, but for a search tool with a limit parameter left undocumented and no usage guidance, the description is too thin to let an agent call it correctly on first try.

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 only 50% — query is documented in the schema, but limit (default 20, max 50) is described nowhere. The phrase 'by name' loosely confirms the query semantics but the description does not compensate for the undocumented limit parameter.

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 (AI devices) plus the scope 'by name' and the catalog it searches. It is clearly distinguishable from search_tools or search_models, though it offers no explicit contrast with the sibling get_device.

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 guidance on when to search versus when to fetch a known device via get_device, and no mention of result limits or how to narrow broad queries. The sentence describes the action but not the conditions that select it.

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, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds the catalog scope ('TAAFT catalog') and query target ('by name'), but gives no behavioral details such as pagination, rate limits, or result ordering.

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 efficient sentence with the key scope and purpose front-loaded. Every word earns its place and there is no repetition or 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 search tool with an output schema, the description is minimally adequate: it names the catalog and the search key. However, it omits usage guidance against siblings and does not cover the undocumented limit parameter, leaving some practical context missing.

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 50%, with the required query parameter described in the schema and limit left undocumented. The description adds little beyond the schema for query and says nothing about limit semantics, so it does not 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?

The description states a specific verb and resource: search the TAAFT catalog for AI events. It is clear enough to distinguish this from get_event by the use of 'search' and 'by name', though it does not explicitly name sibling tools or contrast with get_event.

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 guidance on when to use this tool versus get_event or other search_* siblings. The only implied usage is looking up events by name, which is not sufficient for an agent choosing among many similar tools.

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, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds nothing beyond the purpose statement – no mention of result ordering, pagination, or what an empty result means.

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 filler; the verb and resource come first. It is concise, though the brevity comes at the cost of the missing detail noted elsewhere rather than being tightly informative.

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 an output schema present, return values need not be explained, but the description still omits the 'limit' parameter and any routing against 27 sibling tools. For a two-parameter search tool this leaves real gaps for an agent choosing among the search_* family.

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 only 50%: the 'query' parameter is documented as a company name, but 'limit' (default 20, max 50) is undocumented in both schema and description. The description adds no meaning beyond the schema for either parameter.

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 clear verb ('Search') and resource ('fundraising rounds') scoped to the TAAFT catalog of AI companies. An agent can tell what it returns, but the description offers no differentiation from siblings like search_companies or search_investors.

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?

No when-to-use guidance, no exclusions, and no mention of alternatives such as get_fundraise (single record) or search_investors (related entity). The agent must infer that this is for company-name-driven exploration of funding rounds.

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 declare readOnlyHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is covered structurally. The description adds only the fact that results come from the TAAFT catalog (consistent with the closed-world hint); it says nothing about result count behavior, pagination, or how the limit interacts with the search, so with annotations carrying the load a 3 is appropriate.

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 tight sentence with the resource and catalog front-loaded and zero filler. It is efficient, though its brevity is part of why so much guidance is missing.

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 tool is a simple two-parameter search. Still, with one parameter undocumented and no usage routing against the many sibling tools, the definition is only minimally complete.

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 only 50%: 'query' is documented in the schema but 'limit' (default 20, max 50, min 1) has no description anywhere. The description paraphrases the query concept but never mentions the limit parameter, 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?

The description gives a clear verb+resource ('Search ... for investors') and names the catalog (TAAFT), so an agent knows exactly what is being searched. It does not, however, differentiate itself from siblings like get_investor or search_companies, leaving the search-vs-get choice ambiguous.

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 when-to-use guidance, no prerequisites, and no mention of the alternative 'get_investor' sibling sitting right next to it. The agent must infer that this is the discovery path and get_investor is the lookup path entirely on its own.

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 a safe read-only, non-destructive, closed-world operation. The description adds the data source (TAAFT MCP directory) and the output-handling instruction to preserve URLs exactly, but it does not disclose richer behavior such as ranking, pagination, or rate limits.

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?

Three short sentences, front-loaded with the core purpose and usage context, followed by a critical output-fidelity instruction. Every sentence earns its place with no 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?

With an output schema present, the description does not need to explain return values. It covers purpose, usage context, and URL preservation, though it omits sibling differentiation and limit-parameter guidance, leaving minor gaps for this simple search 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 50%: the query parameter is well described, but the limit parameter lacks a description. The tool description does not compensate by adding meaning for either parameter, so the schema carries most of the parameter semantics.

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: search and recommend MCP servers from the TAAFT MCP directory. It is clear and not tautological, but it does not distinguish itself from sibling tools like search_tools or search_entities.

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 clear context for when to use it: when the user asks for MCP recommendations or when an MCP server is relevant to their task. It does not state when not to use it or name alternatives among the sibling tools.

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=false, and destructiveHint=false, so the safety profile is covered. The description adds that the search is scoped to the TAAFT catalog and by model name, but does not disclose result limits or pagination 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?

The description is a single front-loaded sentence with no wasted words. It efficiently communicates the core action and scope.

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 search tool with an output schema, the description covers the basic search scope. However, it omits guidance on when to prefer this over get_model and does not explain the limit parameter, leaving some gaps for an agent.

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 50%: the query parameter is documented in the schema, but the limit parameter has no description. The description only repeats that search is by model name and adds no meaning beyond the schema for either parameter.

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 (search) and resource (AI models) within the TAAFT catalog and even names the search key (model name). It is clearly distinct from sibling search tools by resource type, though it does not explicitly contrast with get_model.

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 guidance, no prerequisites, and no mention of alternatives such as get_model. The intended use is only implied by 'search by model name.'

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 declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, covering the safety profile. The description adds that the search is over the TAAFT catalog and by name, but does not disclose pagination, result limits, or matching behavior. With annotations doing the heavy lifting, a 3 is appropriate.

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 extraneous words. It is appropriately sized for a simple search tool and gets straight to the point.

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 described, and annotations cover safety. However, the limit parameter lacks any description, and the description does not explain how many results are returned or how to control it, leaving a gap for a search 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 50%; only the query parameter is documented. The description's 'by name' restates the query parameter's meaning without adding new detail, and it entirely omits the limit parameter, which is undocumented in both schema and description.

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 ('Search') and resource ('AI organizations'), and scopes it to the TAAFT catalog and name-based matching. It does not explicitly differentiate from sibling tools like get_organization or search_companies, but the resource term is distinct enough for an agent to identify its purpose.

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?

No guidance on when to use this tool versus alternatives such as get_organization for a known organization or search_companies for companies. The description only states what it does, leaving usage entirely implied.

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 destructiveHint=false, so the safety profile is covered. The description adds a useful behavioral constraint — that matching is on title (not full text) and limited to the TAAFT catalog — but says nothing about result volume, ranking, or the limit cap's effect.

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: verb, corpus, resource, and matching dimension in one pass. Nothing to trim, nothing buried.

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-value explanation is not needed, and annotations cover safety. However, for a search tool the description omits sibling routing (get_paper vs. search_papers) and any note on the uncovered limit parameter, leaving a couple of practical 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 50%: 'query' is documented and 'limit' is not documented anywhere. The phrase 'by title' adds meaning to query beyond the schema (title-oriented matching rather than free-text), but the undescribed limit parameter (default 20, max 50) is left entirely to the agent to infer.

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 (papers) scoped to the TAAFT catalog, and adds the search dimension ('by title'). It is distinguishable from get_paper (fetch by id) implicitly, but it never names siblings or contrasts search vs. retrieval.

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 use this tool versus the sibling get_paper or the other search_* tools. Usage is only weakly implied by the tool name and the phrase 'by title'; no exclusions or alternatives are offered.

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, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds only that the search is scoped to a bounded catalog, which is consistent with the annotations but discloses nothing new about result limits, ordering, or pagination.

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 naming the verb, resource, and searchable fields with no filler. Nothing could be removed without losing 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?

An output schema exists, so return values need not be explained, and the annotations cover safety. The only real omission is any mention of the limit parameter or result-count behavior, a minor gap for a simple two-parameter search 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 50%: query is documented in the schema, limit is not. The description's 'by name or company' merely restates the query schema description and does nothing to explain the undocumented limit parameter, 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 (Search) and resource (AI code repositories in the TAAFT catalog), plus the searchable dimensions (name or company). It is clearly distinguishable from the get_* siblings, though it does not explicitly differentiate itself from the other 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?

Usage is implied by the phrase 'by name or company,' which tells the agent what inputs are useful, but there is no explicit guidance on when to choose this over search_tools/search_models or over get_repository for direct lookup.

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, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered without the description. The description adds only the matching-key detail ('by name'), with nothing about match semantics (exact vs substring) or result limits.

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 tight sentence with the resource and matching key front-loaded. No filler, though it is perhaps too terse to do more than the minimum.

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?

The tool is simple and has an output schema, so return values need no explanation. Still missing anything about match behavior, result ordering, or how the limit/default of 20 affects output, which matters for a search 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 coverage is 50%: 'query' is documented in the schema and the description adds little beyond restating it as a name search. 'limit' is neither described in the schema nor explained in the description, though its type/default/max/min constraints constrain misuse. Baseline 3 fits when the schema carries the parameter semantics.

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 ('Search the TAAFT catalog for robots') plus the matching key ('by name'), which is clear. However, it does not distinguish this tool from the many parallel siblings (search_tools, search_companies) or from get_robot, so an agent must infer the search-vs-fetch distinction.

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?

No when-to-use or when-not-to-use guidance is given, and no alternative such as get_robot (direct lookup) or search_tools (other entity) is named. Only the implicit hint that matching is by robot name.

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, destructiveHint=false, and openWorldHint=false, so the safety profile is covered structurally. The description adds no behavioral context beyond that — no note on result ordering, pagination, or scope limits to complement 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?

A single compact sentence with the resource front-loaded and no filler. It is efficient, though that efficiency comes partly from omitting needed guidance.

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 explaining return values is unnecessary, and this is a simple two-parameter read tool. Still, it omits guidance on the limit parameter and on when to prefer it over the singular get_task sibling, leaving a modest 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?

Schema description coverage is only 50%: 'query' is documented in the schema but 'limit' (default 20, max 50) is not, and the description mentions no parameters at all. It neither adds syntax/format guidance nor compensates for the undocumented limit parameter.

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 (TAAFT task categories) plus the domain of what is searched (capabilities/jobs users want AI tools to perform). It distinguishes itself implicitly from the singular sibling get_task, but never names a 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?

No when-to-use guidance is given. The agent is not told when to search tasks versus calling get_task for a known ID, nor how this relates to search_tools in the sibling list. Usage is only implied by the verb 'search'.

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 cover read-only and non-destructive behavior, so the bar is lower. The description adds useful behavior beyond the schema: it distinguishes 'url' (for TAAFT pages) from 'website_url' (for external websites) and instructs the agent to preserve returned URLs exactly. This is meaningful operational guidance.

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 concise sentences with no filler. The first sentence states the core operation, and the second provides an important, actionable detail about URL fields. Information is front-loaded and efficient.

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 search tool with an output schema and helpful annotations, the description covers the essential search context and URL handling. It does not describe result limits or sorting details, but nothing critical is missing for invoking the search 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 low (only 'query' is described), and the description does not explain 'sort', 'type', or 'limit' beyond what the enums already self-document. The URL guidance concerns response fields, not input parameters, so it does not compensate for the schema's low descriptive coverage.

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 ('Search') and names the target resource ('TAAFT directory for AI tools that match a query'). This clearly distinguishes it from the sibling 'get_tool' by focusing on search-by-query rather than retrieval of a specific item.

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 makes the tool's context clear: use it to search the directory for AI tools based on a query. It does not explicitly say when not to use it or when to prefer get_tool, but the 'Search' framing plus the sibling name provide enough directional clarity without further exclusion instructions.

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