Namaste America

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

No annotations are provided, so the description carries full burden. It discloses write behavior, moderation (immediate publish vs. hold), and return format. It does not mention potential rate limits or detailed auth requirements, but provides good context beyond the schema.

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 efficient sentences: purpose with constraint, moderation behavior, and return format. No unnecessary words, front-loaded key info.

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 relatively simple (4 params, 2 required) with an output schema listed. The description covers the core behavior and return values, but omission of optional parameter semantics (city, vertical) is a minor 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 0%, so the description must compensate. It explains 'member_email' (must be authenticated) and 'question', but omits any explanation for the optional 'city' and 'vertical' parameters, leaving their purpose unclear.

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 identifies the tool as posting a question to the Namaste America community on behalf of a signed-in member. It distinguishes itself from sibling tools (mostly read/search operations) by being a write operation with a specific verb and resource.

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 states when to use (authenticated member asking a question) but does not explicitly state when not to use or mention alternatives. However, given that sibling tools are mostly for searching/reading, the use case is well 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?

No annotations are provided, so the description carries the transparency burden. It discloses the return format, but does not mention any side effects, permissions required, or whether the action is idempotent. For a mutation tool, this is insufficient.

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, front-loaded with the action and purpose, and includes all essential information without excess.

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 low complexity (2 required params, simple return), the description covers purpose, key parameter constraints, and return format. It could mention whether following a city already followed is handled gracefully, but overall it is nearly 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 0%, so the description must compensate. It provides an example for 'city' ('Plano, TX') and clarifies that 'member_email' must be the authenticated member's email. This adds meaningful context beyond the raw 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 'Follow', the resource 'city', and the purpose 'so the member is notified of new events there'. It distinguishes from sibling tools like 'save_place' or 'list_follows' by specifying the action on a city.

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 precondition: 'member_email must be the authenticated member's email.' It does not explicitly list alternatives, but the purpose is straightforward and no sibling tool directly overlaps.

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?

With no annotations, the description must disclose behavior. It mentions 'full canonical record plus version history' but does not clarify what constitutes a canonical record, nor does it address side effects, authentication, or other operational details.

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 succinct, using only 13 words to convey purpose and outputs. Every phrase is meaningful, though 'apparel/jewelry' might be slightly redundant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the high number of sibling tools and the lack of schema descriptions, the description is insufficient. It does not clarify the uniqueness of this tool or how it relates to similar ones like get_indian_apparel. The presence of an output schema does not mitigate the need for better context.

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 has one parameter (apparel_id) with no description. The description does not explain what the parameter represents or how to obtain it. At 0% schema coverage, the description should compensate but fails to do so.

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 it retrieves a 'full canonical record' plus version history for one apparel/jewelry store. The verb 'get' and resource are unambiguous. However, it does not differentiate from sibling 'get_indian_apparel' or other get_*_details tools, which could be similar.

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 is provided on when to use this tool vs alternatives. There is no mention of prerequisites, exclusions, or when to choose other tools like search_apparel_by_text.

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?

With no annotations, the description bears full burden. It discloses the return format (question with answers list or error) and ordering behavior. For a read-only retrieval tool, this is adequate and adds context beyond basic schema.

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 wasted words. Front-loaded with the main purpose. Every sentence adds value.

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 tool with one parameter, no annotations, and an implied output schema, the description covers the return format and error case, making it complete for an agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% with only a title 'Slug'. The description compensates by explaining that slug comes from search_community_questions, adding meaningful context for how to obtain the slug value.

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 it returns a community question with its published answers, specifies the ordering (Dost's AI answer first, then community answers by upvotes), and mentions the slug source, distinguishing it from siblings like ask_community_question.

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 provides clear context for when to use (to get answers for a community question) and notes that slug comes from search_community_questions, suggesting a prerequisite. It does not explicitly state when not to use or list alternatives, but the context is sufficient.

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?

With no annotations, the description should disclose behavioral traits like safety or side effects. It only mentions the output contents, not permissions, error behavior, or impact. This leaves the agent guessing about usage constraints.

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 efficiently conveys the core purpose and additional detail (version history). It is front-loaded and avoids unnecessary 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?

For a simple tool with one parameter and an output schema, the description is adequate but not thorough. It omits any mention of usage context, such as when community_id is valid, but the output schema covers return values.

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 0%, so the description must explain parameter meaning. It implies community_id identifies the organization but does not explicitly confirm its type or role, leaving ambiguity.

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 it returns the full canonical record and version history for a community organization, using a specific verb and resource. However, it does not explicitly differentiate from sibling tools like get_event_details, which also return detailed records.

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 is provided on when to use this tool versus alternatives. The description only states what it does, without indicating when it is appropriate or when to use 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?

No annotations exist, so the description carries full burden. It discloses that the tool returns 'full canonical record' and 'version history', indicating a read operation with historical data. However, it omits any mention of auth requirements, rate limits, or side effects. The description adds some context but could be more explicit about the operation's 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 a single sentence that efficiently communicates the tool's purpose and key feature (version history). No unnecessary words or redundancy. Ideal conciseness.

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 an output schema (handling return structure), the description appropriately focuses on the core behavior. It covers the main purpose and a notable feature (version history). One might expect mention of required permissions or the tool's scope (e.g., single entity only), but it is largely complete for a simple retrieval 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 0% and the description does not elaborate on the single parameter (education_id). The parameter name is self-explanatory, but the description should ideally clarify what constitutes a valid ID (e.g., numeric identifier from a listing). Without this, the agent may not understand how to obtain the ID.

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 specific verb 'get' and resource 'education/tutoring listing', clearly distinguishing it from search siblings (e.g., search_education_by_text) and other category-specific detail tools. It adds 'canonical record' and 'version history' for precision.

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?

Implies use when a specific education_id is known and full details (including version history) are needed, but no explicit when-not or alternatives are provided. Given the many sibling tools, guidance on when to use get_education_details versus search or other get_*_details would be beneficial.

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?

With no annotations, the description carries the full burden. It discloses that the tool returns a 'full canonical record' and 'version history', implying a read operation. While it doesn't explicitly state side effects, the behavior is reasonably clear for a get tool.

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, concise sentence with no wasted words. It is front-loaded with the core purpose and additional detail (version history) efficiently.

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?

Despite having an output schema, the description lacks usage context and parameter explanation. For a simple one-parameter tool it is minimally adequate, but leaves gaps in guidance and parameter clarity.

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 0% for the parameter, and the description does not mention or explain the required 'event_id' parameter. Although the parameter name is self-explanatory, the description adds no semantic value beyond what the name implies.

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 returns 'full canonical record for one event, plus its version history', specifying the verb (get) and resource (event details), and distinguishes from sibling 'get_*_details' tools by mentioning both the entity and additional version-history content.

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 is provided on when to use this tool over alternatives such as search_events_by_text or other get_*_details tools. The description lacks any contextual hints about usage scenarios.

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?

No annotations are provided, so the description carries the full burden. It discloses that dates are best-effort due to lunar calendars and advises users to confirm with local religious institutions. It also mentions the return format (name, date, days_until, emoji, greeting) and a top-level note.

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 front-loaded with the purpose, followed by behavior and a warning. It is reasonably concise with three sentences plus a caveat. Every sentence adds value, though the warning could be shortened slightly.

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's simplicity (2 parameters, no required params, output schema exists), the description adequately covers parameter behavior, return format, and an important caveat about date accuracy. It feels complete for an agent to understand and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate. It explains the behavior of both parameters: limit defaults to 6, query defaults to empty, and describes how query affects results. It adds meaning beyond the schema by linking parameters to tool behavior.

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 it returns upcoming Indian/South-Asian festival dates for planning in the USA. It distinguishes behavior with and without a query parameter. However, it does not explicitly differentiate from sibling tools like get_indian_events, which may overlap in 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?

The description explains when to use the tool with no query (returns next limit festivals) and with a query (returns single soonest matching). It provides context for both use cases but does not mention when not to use it or suggest alternatives among 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?

No annotations provided; description does not disclose read-only nature, permissions, error behavior, or what 'canonical record' entails beyond version history. Lacks critical behavioral details.

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?

Single sentence, front-loaded with key information. Efficient but could expand minimally to improve clarity.

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 output schema present, return values are covered. However, missing parameter documentation and usage context make it barely adequate for a simple 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 0% and description adds no meaning to 'finance_id' parameter. Agent must guess its purpose and format.

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 specific verb 'get' and resource 'finance/tax listing' plus 'version history', clearly distinguishing from search tools that list multiple results.

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 vs alternatives like search_finance_by_text or other get_details tools. Context implies single-record retrieval but not 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?

With no annotations, the description must disclose behavioral traits. It mentions returning a 'full canonical record' and 'version history,' indicating it is a read operation. However, it lacks details on authorization, data freshness, or side effects.

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 that is efficient. However, it uses jargon ('canonical record') and could be slightly more informative without losing conciseness.

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 simplicity of the tool (one parameter, output schema exists), the description is still incomplete. It does not explain what 'canonical record' entails or provide usage hints. Schema descriptions are absent, so the description should compensate but does not.

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 0%, yet the description does not explain the meaning or usage of the 'grocery_id' parameter. The parameter name is self-explanatory but the description fails to add any value 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 it retrieves the full canonical record and version history for a grocery store, using a specific verb and resource. It distinguishes from siblings like get_restaurant_details by specifying 'grocery store'.

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 is provided on when to use this tool vs alternatives such as search_groceries_by_text or other get_*_details tools. The agent receives no context for appropriate invocation.

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?

Without annotations, the description discloses return format (sponsor record or error object), data source (DOL LCA), and the fact that it aggregates data. This is good transparency for a read-only tool.

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 front-loaded with purpose. No unnecessary words; the ellipsis efficiently summarizes additional return fields.

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?

Adequately covers return structure, error handling, and data source. With a simple parameter and existing output schema, no further details are needed.

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 0% schema coverage, the description adds crucial context by specifying the id comes from search_h1b_sponsors, which is beyond the schema. The single parameter's meaning is clarified.

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?

Clearly states it returns full details for one H-1B sponsor, referencing the id from a sibling search tool. The verb 'get' and resource 'sponsor details' are explicit, and the distinction from other get_* tools is evident.

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?

Implies using search_h1b_sponsors first to obtain the id, providing clear context. Does not explicitly state when not to use, but the context is sufficient for correct invocation.

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?

No annotations are provided, so the description bears the full burden. It omits important behaviors such as pagination (limit/offset), default radius, conflict handling when both location types are provided, and the safety/read-only nature of the operation.

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 wasted words. The purpose is front-loaded, and usage follows concisely. The parentheses for tag examples add value without clutter.

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 description covers the main parameter groups but misses pagination (limit/offset) and does not explain default behavior (e.g., radius default 15). An output schema exists, reducing the need for return value description, but gaps remain.

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 0% schema description coverage, the description adds meaning to lat/lng, radius_miles, city, state, tag, and open_now, including example tags. However, it fails to document limit and offset, which are in the schema but lack explanation.

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 finds Indian apparel and jewelry stores, listing specific examples like sarees and lehengas. It distinguishes from siblings like 'get_apparel_details' (for details) and 'search_apparel_by_text' (text search).

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 explains the two location modes (lat/lng vs city/state) and the optional filters (tag, open_now), providing clear context for parameter usage. However, it does not mention alternatives or when not to use this 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?

No annotations are provided, so the description carries the full burden for behavioral disclosure. The description only says 'Find', implying a read operation, but does not explicitly state read-only behavior, required permissions, data freshness, pagination behavior, or any other safety or rate-limiting context. This is insufficient for a tool with 9 parameters.

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: the first states the tool's purpose with examples, the second provides usage instructions. Every word adds value, no fluff. It is front-loaded with the core function.

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?

Despite having an output schema and many parameters, the description omits critical usage details like pagination (limit, offset) and spatial filtering (radius_miles, open_now). It also does not mention the output format, though the schema might cover that. For a tool with 9 parameters, the description is incomplete.

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 description adds meaning for 5 out of 9 parameters (lat, lng, city, state, tag) by explaining their purpose and giving examples for tags (e.g., 'telugu', 'gujarati', 'association'). However, it does not mention limit, offset, radius_miles, or open_now, which are significant for search behavior. With 0% schema description coverage, the description should have covered all parameters, but it only partially compensates.

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 finds Indian community organizations and cultural associations, providing specific examples like regional samaj/sangam, cultural centers, Indo-American associations. The verb 'Find' and resource 'community organizations' are specific, and the tool is easily distinguished from sibling tools focused on temples, restaurants, etc.

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 explains how to use the tool: provide a lat/lng point or city/state, and filter by tag. It implies this tool is for community organizations, not for other categories like temples or restaurants. However, it does not explicitly state when not to use it or mention alternative tools for different types of Indian places.

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?

No annotations are provided, so the description must carry the full burden. It explains that the tool returns results based on location and tag, but does not disclose pagination (limit, offset), the open_now filter, or the default radius of 25 miles. More detail on the response format would improve 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?

The description is two sentences long, with the first sentence immediately stating the purpose. Every word adds value, and the structure is efficient 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?

Given the 9 parameters, no annotations, and the presence of an output schema, the description covers the core usage (location and tag) but omits description of limit, offset, and open_now. The output schema may compensate for return values, but the input guidance could be more thorough.

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 0%, so the description must add meaning. It explains that lat+lng and radius_miles form a point, and city/state are alternatives, and tag filters by category. However, it omits limit, offset, and open_now, which are part of the schema. The guidance is helpful but incomplete.

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 finds Indian-American education & tutoring resources, listing specific types like heritage/language schools, Bal Vihar, and coaching. This distinguishes it from sibling tools like get_education_details (which likely retrieves a single entity) and other category 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 tells when to use the tool (e.g., by location or city/state) and how to filter by tag. It does not explicitly state when not to use it or mention alternatives, but the context is clear enough for selecting this over get_education_details.

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?

With no annotations, the description carries full burden and covers key behaviors: default upcoming ordering, include_past for history, offset pagination with has_more, and output fields. Lacks details on error handling or rate limits but is sufficient for safe usage.

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 concise (around 100 words) and front-loads the purpose. Although not bullet-pointed, it efficiently conveys parameter groupings and behavior constraints without 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 complexity (10 parameters, no annotations) and existence of an output schema, the description covers most usage aspects: default ordering, pagination, output fields, and filter examples. Minor gaps include not clarifying that lat/lng are required together and omitting 'limit' explanation.

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 0%, but the description adds meaning for 9 of 10 parameters (missing 'limit'), grouping them logically and providing examples for enums. It explains the location vs. filter distinction and default behavior.

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 finds upcoming Indian-American community events using specific verbs and resource. It distinguishes itself from siblings like search_events_by_text and get_event_details by focusing on location, category, and tag filters.

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 usage context through parameter options (location vs. city/state, filters) but does not explicitly state when to use this tool over other event-related tools (e.g., search_events_by_text for text search, get_event_details for 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?

No annotations are present, so the description must disclose behavior. It fails to mention that the tool returns a list, is paginated (limit/offset), or if it's read-only. This lack of transparency hurts.

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 very concise, with a clear purpose statement followed by brief usage instructions in two lines. Every sentence adds value.

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 9 parameters and no annotations, the description should cover all behavioral aspects. It does not explain pagination, the open_now filter, or result format (though output schema exists). Significant gaps remain.

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 0%. The description explains lat, lng, radius_miles, city, state, and tag, but omits limit, offset, and open_now. These are crucial for controlling results and filtering, leaving significant gaps.

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 finds Indian-American CPAs, tax preparers, and financial advisors. It distinguishes from siblings like search_finance_by_text (text search) and get_finance_details (details).

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 explains how to use parameters: provide lat/lng with optional radius_miles, or city/state, and filter by tag. It does not explicitly mention when to use this tool over siblings, but the guidance 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?

No annotations are provided, so the description carries the burden. It explains the output fields (description, store type, tags, hours, region, open_now) and documents the open_now filter, but does not mention pagination limits, rate limits, or behavior when no results are found.

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 three sentences, concise and front-loaded. The first sentence states the purpose, the second explains parameters, and the third describes output. No unnecessary 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 tool has 10 parameters (none required) and an output schema, the description covers key use cases: location vs city/state input, common filters, and output fields. It lacks sorting or combinability of inputs, but overall it's sufficient for an agent to use 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 0%, so the description must explain parameters. It effectively explains the lat/lng pairs, optional radius_miles, alternative city/state input, and gives examples for region_tag and tag. It clarifies that records include certain fields. However, it omits explanation of limit and offset parameters.

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 finds Indian grocery stores and includes specific details about input options (location or city/state) and filters (region_tag, tag, open_now). It distinguishes itself from sibling tools like get_grocery_details which returns details for a single store.

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 specifies when to provide a point vs city/state and mentions optional filters, but does not explicitly contrast with alternative search tools (e.g., search_groceries_by_text) or state when not to use this 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?

With no annotations, the description carries full responsibility for behavioral disclosure. It does not mention authentication, rate limits, side effects, pagination, or the format of results (just 'Find'). The schema includes parameters like 'open_now', 'limit', and 'offset' that are not mentioned, leaving the agent unaware of these capabilities or constraints.

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 exceptionally concise: two sentences that immediately state purpose and key usage. Every sentence is necessary and front-loaded with the most critical information. 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?

Considering the tool has 9 parameters, no required ones, an output schema, and many siblings, the description is insufficiently complete. It does not explain pagination ('limit', 'offset'), the 'open_now' filter, or what the output contains. For a listing tool, this forces the agent to guess or rely on conventions from sibling tools.

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 0%, so the description must add meaning. It explains that 'lat' and 'lng' define a geographic point, 'radius_miles' is optional, and 'city'/'state' are alternatives, with 'tag' for filtering. These explanations add value beyond schema names. However, it ignores 'limit', 'offset', and 'open_now', leaving 4 of 9 parameters unexplained.

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: 'Find Indian-American immigration attorneys & law firms.' It specifies the types of resources (attorneys, law firms) and the domain (Indian-American immigration), making it easy for an agent to understand what the tool retrieves. The name and description together distinguish it from siblings like 'get_legal_details' (likely a detail retrieval) and 'search_legal_by_text' (text search).

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 explicit guidance on how to use the tool: 'Provide a point (lat+lng, optional radius_miles) or city/state. Filter by tag (e.g. 'immigration').' This tells the agent the two primary modes of querying (location or city/state) and optional filtering. However, it does not specify when to use this tool versus alternatives like 'search_legal_by_text', nor does it mention prerequisites or limitations.

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?

With no annotations, the description carries full transparency burden. It discloses the data source (TMDB) and a key limitation (no per-theater showtimes, ticket_url is a search link). This is informative, though it could note any update frequency 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?

The description is concise and well-structured: a short first sentence for purpose, then a paragraph with details. Every sentence adds value, with no repetition or fluff.

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 existence of an output schema, the description appropriately lists the returned fields (title, language, etc.) and explains the ticket_url limitation. It lacks mention of pagination or ordering, but is otherwise complete for a listing tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must add meaning. It clarifies the 'language' parameter with an example, but does not explicitly describe the 'limit' parameter beyond its default. Some value is added, but more detail on 'limit' would help.

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 it lists Indian-language movies currently playing in US theaters, specifies the languages included, and distinguishes itself from the sibling tool 'get_movie_details' by focusing on current listings rather than individual movie details.

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 explains the optional language filter and the data each movie includes, providing clear context. However, it does not explicitly mention when to use alternatives like 'get_movie_details', leaving it implied 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?

Without annotations, the description carries full burden. It discloses that results are matched via Indian-name signal from public data and includes a confidence_score, indicating potential accuracy concerns. No contradictions.

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 concise: first sentence states purpose, second sentence details parameters and behavior. No wasted words, front-loaded with key info.

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 11 parameters (0 required), no annotations, and an output schema, the description covers major parameters and behavioral context. Lacks mention of pagination (limit/offset) but this is partially mitigated by output schema. Overall well-rounded.

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 0%, so description must compensate. It explains the role of lat, lng, radius_miles, city, state, profession_type, speciality, tag, and open_now. It does not cover limit, offset, or confidence_score (likely output), but adds significant value beyond the raw 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 tool finds Indian-American healthcare professionals, specifying the action ('find') and resource types (doctors, dentists, clinics, pharmacies). It distinguishes from sibling tools like search_professionals_by_text by emphasizing structured location and filter parameters.

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 clear usage patterns: provide a point (lat+lng+radius_miles) or city/state, and filter by profession_type, speciality, tag, or open_now. It does not explicitly mention when not to use or compare to alternatives like search_professionals_by_text, but the guidance is sufficient for basic usage.

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?

No annotations provided, so description must fully disclose behavioral traits. It describes two search modes and a filter, but omits crucial details: pagination behavior (limit, offset), the meaning of 'open_now' for real estate, handling of conflicting parameters (both location and city/state), and whether results are sorted or ranked. Incomplete disclosure for a tool with 9 parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with purpose. Could list the modes more explicitly (e.g., bullet points), but overall concise and readable. 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 9 parameters, 0% schema description coverage, and an output schema (contents unknown), the description is insufficient. It does not explain pagination, return format, default radius, or behavior with missing required parameter combinations. For a complex search tool, more detail is needed to ensure correct invocation.

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 0% description coverage for parameters. Description clarifies lat, lng, radius_miles, city, state, and tag, but omits limit, offset, and open_now. open_now is particularly confusing for real estate and requires explanation. The description partially compensates for the missing schema descriptions but does not cover all parameters.

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 'Find' and resource 'Indian-American realtors & real-estate agencies', and distinguishes two search modes (location-based or city/state) plus optional tag filter. This differentiates it from sibling tools like search_realestate_by_text (text search) and get_realestate_details (details on a specific entity).

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?

Description provides explicit usage instructions: 'Provide a point (lat+lng, optional radius_miles) or city/state. Filter by tag.' However, it does not state when to use this tool over alternatives, nor does it mention when not to use it (e.g., unsupported locations). No explicit guidance on parameter combinations or conflicts.

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?

With no annotations provided, the description bears full burden for behavioral disclosure. It describes the read-only nature (find restaurants), filtering, pagination, and output fields (description, tags, confidence_score, etc.). Missing details like authorization or rate limits, but the scope is clear and non-misleading.

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 paragraph but well-organized with clear, sequential sentences. It avoids fluff and conveys all necessary information efficiently. Minor improvement could be grouping parameter categories into bullet points for easier scanning, but it's already concise and 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?

Given the tool's complexity (12 parameters, 0 required) and the presence of an output schema, the description covers location modes, filters, pagination, and output fields adequately. It implies mutual exclusivity between point and city/state but does not explicitly state constraints like 'do not mix both modes.' Slightly more explicit guidance would make it 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 0%, yet the description thoroughly explains all key parameters: location modes (lat/lng/radius vs city/state), filters (region_tag with examples, dietary_tags, tag, open_now, featured_only), and pagination (offset, limit, has_more). It adds meaning that the bare schema lacks.

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 starts with 'Find Indian restaurants by location and/or filters,' clearly stating the tool's purpose with specific verb and resource. It distinguishes itself from sibling tools like 'search_restaurants_by_text' by emphasizing structured filters and location modes rather than free-text search.

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 explains when to provide a point (lat/lng with optional radius) or city/state, and covers pagination with offset. However, it does not explicitly state when NOT to use this tool (e.g., when to use search_restaurants_by_text or get_restaurant_details), which would improve differentiation further.

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?

No annotations are provided, so the description carries the full burden. It implies a read-only query by stating 'Find' and describing the output, but does not explicitly declare it as non-destructive or mention any authentication/rate limits. The output fields are listed, but behavioral traits like idempotency or error conditions are omitted.

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 short sentences and a sentence listing output fields, all front-loaded and free of fluff. Every sentence adds value without 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 9 parameters, no required fields, and an output schema that likely documents return structure, the description covers the essential search modes and filters. It lacks pagination details and coordinate precision, but overall is sufficient 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 0%, so the description must compensate. It explains lat/lng, radius_miles, city, state, tag, and open_now, but leaves limit and offset undocumented. While the main parameters are covered, the missing ones are important for pagination, and coordinate format is not clarified.

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 'Find Indian beauty salons' with specific service examples (threading, henna/mehndi, hair, bridal), making the resource and purpose unambiguous. It also distinguishes from sibling tools like search_salons_by_text and get_salon_details by focusing on direct filtering rather than text search or details 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?

The description explains how to use the tool: provide a point (lat/lng + radius_miles) or city/state, and filter by tag or open_now. However, it does not explicitly state when to prefer this over alternatives like search_salons_by_text or get_salon_details, nor when not to use 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?

With no annotations, the description must disclose behavior fully. It mentions filtering capabilities but omits details like pagination (limit, offset), ordering, rate limits, or what the response contains. The output schema exists but is not described, leaving behavioral gaps.

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 concise: two sentences that front-load purpose and examples. Every sentence adds value without 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 9 parameters, no annotations, and an output schema that is not described, the description provides enough to start using the tool but lacks details on pagination, sorting, and response structure. It is minimally complete for a simple finder but not fully sufficient for complex interactions.

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 0%, so the description must add meaning. It explains lat/lng/radius_miles, city, state, tag, and open_now with examples, covering most key parameters. However, limit and offset are not mentioned, and the description does not fully compensate for the missing schema descriptions.

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 finds Indian community services with specific examples (money transfer, immigration, etc.), making its purpose clear. It differentiates from siblings like get_indian_finance by covering a broader range, but doesn't explicitly contrast with similar broader 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 explains when to use the tool (by location or filter) but does not provide explicit guidance on when to avoid this tool and use a sibling like search_services_by_text or a specific get_indian_* tool. Usage is implied but not contrasted.

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?

No annotations are provided, so the description carries the full burden. It correctly implies a read operation (find) but does not disclose default limits (limit=25, offset=0, radius=15), pagination behavior, or any potential side effects. The description is adequate but lacks detailed behavioral context for a tool with 9 parameters and no 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?

The description is two sentences with no wasted words. The first sentence front-loads the purpose and scope, making it immediately clear what the tool does. 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?

Given the complexity (9 parameters, no required ones) and that an output schema exists, the description covers the most important usage aspects: location-based and tag-based filtering. It does not mention pagination parameters (limit, offset) or default radius, but the schema and output schema likely cover the rest. It is complete enough for most use cases.

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 0%, so the description must explain the parameters. It successfully does so: explains lat/lng as a point, radius_miles as optional, city/state as alternatives, tag with examples, and open_now as a boolean filter. It does not explain limit/offset, but those are common pagination parameters. Overall, it adds significant 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 the specific resource 'Indian yoga & cultural studios', listing examples like yoga, classical dance, music, language classes. This distinguishes it from siblings such as search_studios_by_text, which likely performs a text-based search.

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 clear usage patterns: 'Provide a point (lat+lng, optional radius_miles) or city/state. Filter by tag... or open_now.' This tells the agent when to use this tool (location-based or tag-filtered queries) but does not explicitly state when not to use it or mention alternatives like search_studios_by_text.

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?

No annotations provided, so description should fully disclose behavioral traits. Mentions filtering but does not describe pagination (limit/offset), data source, rate limits, or what happens on invalid input. Lack of annotation burden not carried by description.

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 focused sentences. First sentence states purpose, second sentence lists parameter usage. No redundant or filler content. 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?

Given 9 parameters and existence of output schema, description covers main functionality but misses pagination parameters (limit, offset) and does not explicitly state that at least one location input is required. Adequate but with 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 has 0% coverage, so description must compensate. It explains lat/lng as a point, radius_miles as optional, city/state as alternative, and tag/open_now as filters. Adds significant meaning, but omits limit, offset, and the relationship between location inputs (e.g., co-dependency of lat/lng).

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?

Clear verb 'Find' with specific resource 'Indian sweets shops (mithai) & bakeries'. Distinguishes from siblings like get_indian_restaurants or search_sweets_by_text by specifying location-based search.

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?

Gives two modes of location input (point or city/state) and lists filters, providing clear context. However, does not explicitly contrast with alternative sibling tools like search_sweets_by_text (text search) or get_sweets_details (specific shop details).

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 lists returned fields (description, deity, etc.) but does not address behavior when no location is provided, pagination, or 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 concise and front-loaded with the main purpose. It could be slightly more compact but is efficient overall.

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 11 parameters and output schema, the description covers key filters and return contents but misses pagination params and default behavior, making it somewhat incomplete.

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 description explains lat+lng as a point and mentions most filter parameters, adding meaning beyond the schema. It omits limit and offset but covers everything else.

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 finds Indian-American temples and lists filter options. It distinguishes from general search but does not explicitly differentiate from search_temples_by_text sibling.

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 explains how to use location or city/state filters, but lacks guidance on when to use this tool versus get_temple_details or search_temples_by_text.

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?

No annotations provided, so description carries full burden. It implies a read operation returning a full record and history, but does not disclose any side effects, authorization needs, 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?

Single sentence, front-loaded with key information. No filler. Slightly more context about what 'canonical record' entails could improve it, but it is adequately concise.

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 detail return values. It covers the scope (one listing) and mentions version history. Missing any notes on pagination or limitations, but overall sufficient for this simple tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter (legal_id) is not explained beyond the tool name. Schema coverage is 0%, but description adds that it identifies a single listing and that the response includes version history. Lacks guidance on how to obtain the ID or its format.

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 retrieves the 'full canonical record' and 'version history' for one immigration/legal listing. It distinguishes from sibling tools like search_legal_by_text or list tools by focusing on a single authoritative record.

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 explicit guidance on when to use this tool versus the many sibling get_*_details tools or search tools. The description does not mention prerequisites or alternatives.

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

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

With no annotations, the description discloses return types (record or error) and data source (TMDB). It lacks explicit read-only hints but adequately covers expected outcomes.

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 brief and front-loaded with the core purpose. The second sentence adds necessary detail without excessive length.

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 detail retrieval with an output schema, the description covers the ID source, return types, and data attribution. It is sufficient for the agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description links the parameter to a specific source (ID from another tool), adding context. It does not describe format or constraints 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?

The description clearly states it provides 'Full details for one Indian movie' and specifies the source of the ID, distinguishing it from sibling tools like get_indian_movies_in_theaters.

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 explicitly mentions the prerequisite ID from get_indian_movies_in_theaters, offering clear context for use. However, it does not specify when not to use or provide alternatives.

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

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

No annotations are provided, but the description explains that it returns current non-expired posts and includes the output shape. This provides reasonable transparency for a read-only, filtered query.

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 concise with three efficient sentences: purpose, return shape, and usage example. It is well-structured and front-loaded with the 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?

Given the optional parameters and provided output schema, the description is complete. It covers the tool's behavior, filtering capability, and return format, enabling confident agent usage.

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 0%, but the description mentions optional filters by city/state/vertical, partially compensating. However, it does not explain the 'limit' parameter or provide additional syntax guidance beyond the schema defaults.

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 retrieves current, non-expired offers and announcements from Indian-American business owners, with optional filters. It specifies the resource ('offers') and distinguishes from siblings by targeting promotional content.

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 includes a concrete example ('any deals near me this week') and implies use for offers only. It does not explicitly state when to avoid this tool, 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?

No annotations are provided, so the description must fully disclose behavior. It mentions 'Full canonical record' and 'version history', which adds context, but does not specify whether the tool is read-only, has rate limits, or any other behavioral traits.

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 concisely conveys the tool's purpose. It is front-loaded but could be slightly more structured (e.g., listing return fields).

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's low complexity (one required parameter) and the presence of an output schema, the description is minimally adequate. However, it lacks details on the structure of the output (e.g., what 'version history' entails) and does not fully compensate for missing parameter descriptions.

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 0%, meaning the schema has no parameter descriptions. The tool description does not mention the 'professional_id' parameter at all, so it adds no meaning beyond the schema for the user.

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 returns a full canonical record for a professional/practice along with version history. It effectively differentiates from sibling tools that return similar 'details' for other categories.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool over alternatives. The context of needing a single record is implied, but no when-not-to-use or prerequisite information is provided.

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?

No annotations are provided, so the description must disclose behavioral traits. It only mentions the output includes a full record and version history, but lacks information on side effects, authentication needs, rate limits, or whether the operation is read-only.

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, well-structured sentence that conveys the core function without any unnecessary words or details.

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?

While an output schema exists and reduces the need for return value details, the description lacks usage context such as how to obtain the realestate_id or when this tool is appropriate compared to similar listings tools.

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 0% schema description coverage, the description should compensate but does not elaborate on the 'realestate_id' parameter, leaving it to the parameter name alone to convey meaning.

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 retrieves the full canonical record and version history for one real-estate listing, which is distinct from sibling 'search_realestate_by_text' and other category-specific 'get_*_details' 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 this is for obtaining detailed information for a single listing, but does not explicitly state when to use it over alternatives like 'get_indian_realestate' or search tools, nor provides conditions for use.

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?

No annotations, but the description indicates a read operation with no side effects. It's clear enough for a simple fetch, though lacks details on authorization 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?

Single sentence, no fluff, perfectly concise for describing a straightforward tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the low complexity (one param, output schema exists), the description covers the main purpose and output, but 'canonical record' and 'version history' could be slightly vague without output schema details.

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 0%, and the description only vaguely implies the parameter ('one restaurant') without explaining what restaurant_id is or how to obtain it. This does not adequately compensate for the missing schema documentation.

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 action ('Fetch') and resource ('full canonical record for one restaurant') and specifies additional content ('version history'), distinguishing it from sibling get_*_details 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?

Implies usage for fetching a single restaurant by ID, but no explicit guidance on when to use this vs alternatives like search_restaurants_by_text, or any exclusions.

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?

With no annotations provided, the description carries the full burden. It discloses that reviews are returned newest first, include owner replies, and lists the exact return fields. It does not mention any side effects but none are expected. No contradictions with 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?

The description is concise (three sentences) and well-structured, starting with the core purpose, then adding clarifying details about the community rating and return format. Every sentence adds value without 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 3 parameters (2 required) and an output schema is indicated, the description provides a complete picture: it explains the return format, differentiates from sibling tools, and covers key behavioral aspects. For a retrieval tool, this is sufficient.

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 0%, so the description should compensate. However, it does not explain the 'vertical' parameter (what verticals are accepted), 'listing_id' (how to obtain it), or 'limit' (range or default behavior). The description only mentions the return structure, leaving parameter semantics poorly defined.

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 retrieves published community reviews for a listing, sorted newest first, and includes the community rating. It distinguishes the community rating from web-harvested ratings from get_/search_ tools, which aids differentiation among sibling 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 mentions the community rating is separate from web-harvested ratings, providing context for when to use this tool versus others like get_restaurant_details. However, it does not explicitly state when to use this tool or when alternatives are better, leaving some ambiguity.

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?

With no annotations, the description carries the full burden. It adds context about 'version history' but does not specify side effects (none expected), permissions, or any limitations. The output schema is present but not referenced.

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 one sentence (10 words) and directly states the tool's function. It is front-loaded but could be slightly more informative without being verbose.

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's simplicity (one required parameter, output schema exists), the description is minimally adequate. It covers the core purpose but lacks usage guidance, error handling, or any behavioral context beyond the basic record retrieval.

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 0%, so the description should compensate. However, it offers no additional meaning for the 'salon_id' parameter beyond what the schema provides (type, required). No format or range hints.

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 it returns the 'Full canonical record for one salon, plus its version history,' specifying the verb (get) and the resource (salon details). It distinguishes from sibling tools like search_salons_by_text but does not explicitly name alternatives.

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 siblings, no prerequisites, and no mention of when not to use it. The context of fetching a specific salon by ID is implicit but not elaborated.

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?

No annotations exist, so the description bears full responsibility for behavioral disclosure. It mentions returning 'full canonical record' and 'version history' but does not address destructive potential, authentication needs, rate limits, or error handling (e.g., what happens if service_id is invalid).

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 extremely concise, consisting of one sentence that covers the key aspects. It is front-loaded with the primary purpose. However, it could be slightly more structured (e.g., listing what 'full canonical record' includes).

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 low complexity (1 required parameter, output schema exists), the description is minimally adequate. It vaguely describes the output without specifics; while the output schema can fill details, the description lacks context on version history and what 'full canonical record' entails. Not severely lacking but has room for improvement.

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 0% for the single parameter service_id, and the description does not elaborate on its meaning or source (e.g., from search results). The description fails to compensate for the missing schema documentation.

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 returns the full canonical record and version history for one service business. It distinguishes from sibling get_*_details tools by specifying the 'service business' category, but could be more explicit about what constitutes the 'canonical record'.

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 is provided on when to use this tool versus alternative get_*_details tools for other categories (e.g., apparel, community). There is no mention of prerequisites or context for choosing this 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?

With no annotations provided, the description carries the burden of behavioral disclosure. It adds 'plus its version history' beyond the obvious record retrieval, which is useful context, but it doesn't mention auth requirements, rate limits, or whether the tool is read-only. Still, it is adequate for a simple lookup.

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, front-loaded with the key purpose, and contains no superfluous words. It earns its place with direct 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 tool has an output schema (true) and is a simple retrieval by ID, the description is nearly complete. It mentions the core data and version history. It could optionally note what 'full canonical record' includes, but it's not essential.

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 0% (no description for studio_id in schema), and the tool description does not explain the parameter's meaning, valid values, or format. The user cannot learn anything about the parameter beyond its type and required status.

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 'get' and the resource 'studio', and specifies it returns the 'full canonical record' plus 'version history'. This distinguishes it from search tools and other get_*_details tools by resource type.

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 use when you need a single studio's complete data and history, but it does not explicitly state when to use it versus alternatives like search_studios_by_text or other get_*_details tools. No exclusions or prerequisites are mentioned.

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?

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It states the output is a 'full canonical record' and includes version history, but does not mention that the tool is read-only, idempotent, or any security/permission requirements. This is insufficient for safe invocation.

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, concise sentence with no fluff. It front-loads the key information ('Full canonical record') and avoids redundancy. However, it could be slightly more structured by separating the record from version history without adding length.

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 low complexity (1 parameter) and the presence of an output schema, the description adequately conveys the output nature but fails to explain the input parameter clearly. It is functional but not fully self-contained, missing usage context that would compensate for the missing schema descriptions.

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 has 0% description coverage for the single required parameter (sweets_id). The description adds no explicit explanation of this parameter; the phrase 'for one sweets shop / bakery' only indirectly implies the ID parameter's role. An explicit mapping would improve semantic clarity.

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 retrieves a full canonical record and version history for one sweets shop or bakery, which aligns with the tool name and specifies the resource type. It differentiates from sibling tools by category and specificity to a single record rather than search results.

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 is provided on when to use this tool versus alternatives. For example, it does not contrast with search_sweets_by_text for searching or other get_*_details tools for different categories. This omission forces the agent to rely on tool name alone for disambiguation.

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?

With no annotations, the description must disclose behavioral traits. It states the output includes 'version history' but omits details like read-only nature, authentication needs, rate limits, or data freshness. Basic purpose is clear but lacks depth.

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?

Single sentence frontloaded with key information. No waste, every word adds meaning.

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?

Adequate for a simple tool with one parameter and output schema, covering core functionality. However, missing usage guidelines and behavioral transparency prevent full 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?

Schema description coverage is 0%, so the description should compensate. It only implies 'one temple' without explaining the temple_id parameter format, examples, or validation. Minimal value added over 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?

Clearly states it retrieves the full canonical record and version history for a single temple, distinguishing it from sibling tools that likely list or search temples. The verb 'get' and resource 'temple details' are specific.

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?

Implies use when needing a complete record and history for one temple, but no explicit guidance on when not to use it or alternatives. While sibling tools focus on different entities, no direct comparison is provided.

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?

With no annotations, the description carries the full burden. It discloses that lunar festival/tithi dates are approximate and that date fields are ISO. It explains the aggregated nature of the return, though it does not detail auth or rate limits, which are assumed non-intensive. Overall sufficient for a read-only aggregation tool.

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 concise, front-loading the purpose in the first sentence and adding essential details without fluff. Every sentence adds value.

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 returns a complex aggregated feed and an output schema exists, the description adequately covers the return structure. It lacks detail on the 'culture/immigration nugget' and 'trending community questions,' but the schema likely fills that gap. Overall complete for the context.

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 0%, so the description must compensate. It explains the `languages` parameter format and indicates `city` and `languages` are optional, but it omits `state` entirely. This partial coverage justifies a mid-range score.

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 as a consolidated daily briefing about Indian America, listing specific components like festivals, events, movies, places, a cultural nugget, and community questions. It distinguishes itself from sibling tools that focus on individual topics.

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 positions the tool as 'Great for a daily briefing,' implying its use for a broad overview. It does not explicitly state when not to use it or name alternatives, but the purpose is clear enough for an agent to differentiate from more specific 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?

With no annotations provided, the description carries the full burden. It discloses the return format and the authentication constraint ('member_email must be authenticated member's email'). It lacks details like rate limits or permissions, but the read-only nature is clear.

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 extremely concise—two sentences that deliver the core purpose, a key constraint, and the return format. Every sentence earns its place without 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's simplicity (1 parameter, output schema exists), the description is complete. It explains the return format and the essential constraint on the parameter. No gaps are evident for this use case.

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 schema has only one parameter 'member_email' with no description. The tool description adds important context: it must be the authenticated member's email, which is critical for correct invocation. This significantly adds value 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 that the tool lists what a member follows, specifically cities and categories. It distinguishes the tool's action and resource, though it does not explicitly differentiate from sibling tools like 'follow_city' or 'list_saved_places'.

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 that the tool is used for listing follows and provides the constraint that 'member_email must be the authenticated member's email'. However, it does not explicitly state when to use this tool versus alternatives or provide exclusions.

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?

No annotations are provided, so the description must carry the behavioral burden. It discloses the return format and the authentication requirement, but omits details like pagination behavior, error conditions, or read-only 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 three sentences, each adding value: purpose, constraint, and return format. No wasted words; information is front-loaded.

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 list operation, the description covers purpose, parameter constraint, and output shape. It lacks details on error handling or ordering but is sufficient given the tool's simplicity and the presence of an output schema (not shown).

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 0% schema description coverage, the description must explain both parameters. It only adds context for member_email (must be authenticated) and does not explain the limit parameter beyond its schema default.

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 that the tool lists a member's saved places joined with live listing details. This distinguishes it from sibling tools like save_place and unsave_place, which perform mutations.

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 specifies that member_email must be the authenticated member's email, providing a clear usage constraint. However, it does not explicitly state when to use this tool versus alternatives like search or list_follows.

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?

No annotations provided, so description carries full burden. It discloses authentication requirement and return format. It is clearly a mutating operation, but does not mention idempotency or if it overwrites/upserts.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with purpose. Every sentence adds value: first defines action, second specifies parameter sources and return format. No fluff.

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?

Covers purpose, parameter sources, return format, and authentication. With no output schema in structured form, the description provides it informally. Could clarify what 'name' refers to (likely list name). Overall sufficient for action execution.

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 0% description coverage. Description adds significant context: explains origin of vertical and listing_id, and constraint on member_email. This compensates well for missing schema descriptions.

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?

Clearly states verb 'save' and resource 'listing to signed-in member's list'. Distinguishes from sibling 'unsave_place' and search tools via context about parameter sources.

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 states member_email must be authenticated, and vertical+listing_id come from get_/search_ tools. Implicitly guides when to use (after obtaining listing info) and prerequisite authentication. Could explicitly mention not to use if user is not signed in.

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?

Since no annotations are provided, the description carries the full burden. It discloses ranking criteria (exact name match, keyword/semantic similarity, proximity, freshness), vertical tagging, and optional constraints. This is good behavioral transparency, though it doesn't mention auth or rate limits (which may not apply).

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 reasonably concise and front-loaded: first sentence gives scope, then usage examples, then ranking details, then optional params. It could be slightly shorter, but each sentence adds value.

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 complexity (cross-vertical, ranking, optional params), the description covers most essential aspects: scope, use cases, ranking, vertical tagging, constraints. Missing limit/offset details; however, the presence of an output schema reduces the need to describe return values. Overall adequate.

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 0%, so the description must add meaning. It explains query (required), lat/lng for proximity, city/state for constraints. However, it does not explain limit and offset parameters, which are important for pagination. Thus it partially compensates but leaves gaps.

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 searches across multiple Indian-American verticals, listing 10 verticals. It provides example broad queries and differentiates from per-vertical search tools (siblings like search_restaurants_by_text), establishing a distinct cross-vertical search 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?

The description explicitly says 'Use for broad queries' and gives examples, guiding the agent to use this tool when a query spans multiple categories. While it doesn't explicitly say 'not for single vertical', the sibling tools imply that alternative. The guidance 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?

No annotations are provided, and the description only mentions 'Free-text/semantic search' without disclosing behavioral traits such as read-only nature, authentication needs, rate limits, or response format. The description carries the full burden and provides minimal behavioral context.

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 concise sentence with no wasted words. However, it is too brief and could benefit from structuring to include key details like parameter usage or output expectations.

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 5 parameters and an output schema, the description is incomplete. It lacks details on filtering (city/state), pagination (limit/offset), and return format. The context from siblings increases the need 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?

Schema description coverage is 0%, so the description must compensate. However, it does not mention any parameters or their meanings. Parameter names (query, city, state, limit, offset) are self-explanatory to some extent, but the description adds no value 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 tool performs 'Free-text/semantic search over Indian apparel & jewelry stores', specifying the verb (search), resource (apparel & jewelry stores), and scope (Indian). This distinguishes it from sibling search tools targeting different categories.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for apparel/jewelry search but provides no explicit guidance on when to use this tool versus alternatives. With many similar sibling search tools, clearer differentiation would improve score.

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?

No annotations exist, so the description carries full burden. It does not disclose behavioral traits such as whether the search is read-only, any authentication needs, rate limits, or what happens with empty results. The description only states the high-level function.

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?

At one sentence and 10 words, the description is very concise. However, it sacrifices useful detail for brevity. A middle score reflects that while there is no wasted text, the lack of structure (e.g., no bullets or further context) limits its informativeness.

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 5 parameters, an output schema, and many siblings, the description is too sparse. It does not explain pagination (limit/offset) or filtering (city/state), which are critical for an agent to use the tool correctly. The output schema exists but the description still needs to cover behavioral context.

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 0%, and the description adds no meaning to any of the 5 parameters. There is no explanation of what 'query', 'city', 'state', 'limit', or 'offset' mean, their formats, or constraints. The agent must rely solely on parameter names.

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 it performs free-text/semantic search over Indian community organizations and associations, identifying the verb (search) and resource (community organizations). However, it does not explicitly differentiate from sibling search tools like search_restaurants_by_text or search_all, leaving some ambiguity.

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 is provided on when to use this tool versus the many sibling search tools. There is no mention of exclusions, prerequisites, or context that would help an agent decide between this and similar search 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?

No annotations are provided, so the description carries the full burden. It discloses that only published questions are returned, sorted by most-answered first, and includes the return structure. However, it does not mention authentication needs, rate limits, or any destructive actions, which is acceptable for a read-only search tool.

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 paragraph with front-loaded examples and purpose. It is efficient and includes only relevant details, though the last sentence about being a complement is somewhat extraneous.

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 no annotations and the presence of an output schema in the description, it explains the return format (`count`, `results` with fields). It adequately covers what the tool does and returns, though it could mention pagination or sorting details beyond 'most-answered first'.

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 0%, meaning the JSON schema provides no parameter descriptions. The description mentions 'matching the query' but does not explain the `limit` parameter (default 8) or the nature of the `query` field. It adds minimal 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 it searches community Q&A for Indians in the USA, with specific examples ('Telugu-speaking pediatrician in Plano?', 'best sweets for Diwali in Edison?'). It identifies the resource (community questions) and distinguishes from sibling `get_community_answers` by mentioning slugs.

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 usage context by noting it returns most-answered questions and serves as a complement to listings and knowledge base. However, it does not explicitly state when to use this tool versus alternatives like `search_knowledge` or other search 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?

With no annotations provided, the description must disclose behavioral traits. It only states the search type, but omits information about pagination, result ordering, return format, or any side effects. The presence of offset/limit parameters suggests pagination but is not described.

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 concise sentence, which is efficient for a simple tool, but it sacrifices detail. It is front-loaded with the core purpose but lacks structure to cover important aspects.

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 5 parameters and an output schema, the description is incomplete. It does not explain query semantics, how city/state filter, pagination behavior, or what the output contains (e.g., relevance scores). The tool's context in Indian-American education is clear, but operational details are 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 0% and the description does not explain any parameters. The names (query, city, state, limit, offset) are self-explanatory to some degree, but the description adds no value 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 it's for free-text/semantic search over Indian-American education and tutoring. The name and description together make the domain specific and distinguish it from sibling search tools like search_apparel_by_text and get_education_details.

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 usage for text-based queries in education, but provides no explicit guidance on when to use this tool versus alternatives like search_all or get_education_details. No exclusions or use cases are mentioned.

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?

No annotations are present, so the description carries the full burden. It discloses that the search is free-text/semantic, includes past events, and supports offset pagination. However, it omits behavioral traits such as authentication needs, rate limits, result sorting, or handling of empty queries, leaving gaps.

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 extremely concise—one sentence plus a code snippet. It front-loads the core purpose and every phrase adds value. No unnecessary words 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's complexity (5 parameters, one required, output schema exists, many siblings), the description is incomplete. It covers purpose and pagination but lacks parameter semantics, search behavior details (fuzzy vs exact), error handling, and permission requirements. The output schema partly mitigates return value omission, but other gaps remain.

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 0%, yet the description only minimally addresses one parameter (`offset` via '`offset` pages'). It fails to describe the required `query` parameter or optional filters (`city`, `state`, `limit`), which is insufficient for a 5-parameter tool with no schema descriptions.

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 (search) and resource (Indian-American events), includes scope (free-text/semantic, includes past events for history), and distinguishes from sibling tools like get_indian_events and other search_*_by_text tools by specifying the event type.

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 usage for free-text or semantic search over Indian-American events, including past ones, suggesting when to use this compared to get_indian_events. However, it does not provide explicit guidance on when not to use it or alternatives like search_all, and it lacks exclusions.

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