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

Annotations show non-read-only, non-destructive, non-idempotent, open-world. Description adds crucial behavior: returns a deep-link, requires payment/verification on web, first booking unlocks free trial, link expiry ~30 min, and need to echo traveler counts. No contradiction 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?

Very thorough but lengthy; however, the complexity of seven intent types with different data shapes justifies the length. Front-loaded with purpose and key instructions. Could be more structured, but still effective.

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?

Complete coverage for a 3-param tool with nested objects and no output schema. Explains all parameters, user reply requirements, link expiry, and behavioral context. Leaves no ambiguity about how to construct offer_data for any intent type.

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 100%, but description adds significant value: detailed structure of offer_data for each intent type, including examples. Explains optional expires_minutes with defaults and cap. Provides guidance on required fields like passengers/adults/rooms.

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 creates a deep-link booking intent on autonomad.ai, with specific verb 'Create' and resource 'booking intent'. Distinguishes from siblings by instructing to always use this instead of booking directly through MCP.

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 details when to call: two triggers (PICK intents after user chooses an offer; BROWSE intent immediately after search). Provides intent type guide and warns against generating multiple intents for a single trip. Includes user-facing reply requirements.

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

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

Annotations declare read-only and idempotent. Description adds specifics on returned fields (version, mode, tools list) and usage intent, complementing annotations well.

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

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

Two efficient sentences, no filler, front-loaded with output 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?

Given no output schema, description fully describes return values. Annotations cover safety. Sibling tools are distinct. Completeness for a simple introspection 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?

No parameters exist; schema coverage is 100%. Description adds no param info, but baseline of 4 applies for 0-parameter tools.

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 server version, mode, API base, and list of tools. It distinguishes itself from siblings as a meta introspection tool.

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

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

Provides explicit context for use: call at session start to confirm compatibility or branch on capabilities. Lacks explicit 'when not to use' but 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?

Annotations already declare readOnly, idempotent, and non-destructive. Description adds that results include photos, ratings, durations, and pricing—valuable context beyond the structured fields.

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

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

Two sentences with no filler. First sentence states purpose and scope; second sentence tells when to use. Information-dense and 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?

With rich annotations covering safety and no required output schema, the description covers all essential aspects: purpose, scope, filters, typical use cases, and result contents. No gaps.

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

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

Schema coverage is 100%, so the schema already documents all four parameters. The description summarizes filters and provides example categories (e.g., 'food tours', 'walking tours'), adding marginal value but not new 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 specifies a precise verb ('Search') and resource ('tours, experiences, attractions... via Viator with 200K+ activities'). It clearly distinguishes from sibling tools like search_dining or search_flights by focusing on activities and experiences.

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 'Use this when the user wants to plan day activities... fill a trip itinerary' and lists filterable dimensions. Lacks explicit when-not-to-use instructions, but sibling context makes that clear.

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description reinforces this by stating 'search' and 'reservation availability', implying no mutation. It adds context about partnership status and release timeline, which helps set expectations. No contradiction 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 three sentences: first defines the action and filters, second states use cases, third provides status. It is front-loaded with key information, no unnecessary words, and easy to parse.

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 purpose, usage guidelines, and behavioral context well. However, it does not describe the return format (e.g., list of restaurants with availability details), which would be helpful since there is no output schema. Minor gap given the tool's complexity.

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

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

Schema coverage is 100% with descriptions for all 7 parameters. The description lists the parameters in a sentence but does not add new semantics or usage tips beyond the schema. It provides a natural language summary but does not enhance understanding of parameter relationships or 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 searches for restaurants and dining options with reservation availability, specifying multiple filtering dimensions (city, date, time, cuisine, etc.). This distinguishes it from sibling search tools like search_hotels or search_events, which target different domains.

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 when to use: 'when the user wants to find a restaurant, book dinner, plan a meal, get reservations, or pick a place to eat on a trip.' Also provides context on current limitations ('surfaces availability today') and future plans ('full reservation flow in the next release'), guiding the agent on expected behavior.

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

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

Annotations already indicate readOnlyHint, destructiveHint, idempotentHint, and openWorldHint, covering safety and idempotency. The description adds that it searches a combined catalog from Ticketmaster and SeatGeek and supports filtering, which supplements annotations without contradicting them.

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: first defines scope and source, second gives usage guidance. Every sentence adds value, no redundancy 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 tool's 5 parameters (2 required), no output schema, and sibling tools covering other travel needs, the description fully equips an agent to understand purpose, parameters, and when to invoke it.

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

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

Schema description coverage is 100%, and the description essentially re-lists parameters (city, date range, category, keyword) with examples. It adds marginal value by providing example values for category and keyword, but does not significantly enhance what the schema already provides.

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 live events (concerts, sports, theater, etc.) in a city, explicitly listing event types and data sources (Ticketmaster + SeatGeek). This distinguishes it from sibling tools like search_activities or search_dining.

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 second sentence explicitly advises using this tool 'when the user wants tickets to a concert, a sports game, a Broadway show, or any live event during their trip.' It provides clear context for use but does not explicitly mention when not to use it or name alternatives.

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

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

Annotations already indicate readOnly and idempotent. Description adds context: real-time pricing from 800+ airlines (Duffel), schedules, stops. No contradiction 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?

Two sentences with maximum information density. First sentence lists core parameters, second adds source and data richness. 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?

Describes return content (flights, pricing, schedules, stops). No output schema exists, but the description gives a reasonable picture of what the agent will receive. Could mention pagination or limits.

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

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

Schema coverage is 100%, so the schema fully documents parameters. The description only summarizes key parameters without adding new semantic meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it searches airline flights/airfares between two cities with specific parameters. It distinguishes from sibling tools (e.g., search_hotels, search_transport) by focusing on flights.

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 says 'Use this when the user wants to book a flight, fly somewhere, find airfare, or compare airlines.' Lacks negative guidance, but given sibling diversity, it's clear enough.

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

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

Annotations declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint false. Description adds that it returns matching properties with rates, photos, and availability across 2M+ properties (LiteAPI), disclosing the data source and result contents. 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?

Three well-organized sentences: first states purpose and filters, second describes returns, third gives usage guidance. Every sentence adds value, no fluff. Front-loaded with key information.

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

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

For a search tool with 9 parameters, high schema coverage, no output schema, the description adequately explains return content (rates, photos, availability) and data source. It covers all necessary context 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?

Input schema covers 89% of parameters with descriptions. Description lists filters, echoing schema, and provides examples for amenities (e.g., 'wifi, gym, pool'). While not adding deep semantics, it groups and clarifies. Schema coverage is high, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool searches hotels, lodging, accommodations, resorts, etc. It lists specific filters (city, country, dates, room type, price, star, amenities) and indicates returns include rates, photos, availability. This differentiates it from sibling tools like search_flights.

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?

Explicit guidance: 'Use this when the user wants to book a hotel, find a place to stay, compare lodging options, or pick a resort.' This provides clear context, though no explicit when-not-to-use statements (but implications from sibling names are clear).

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

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

Annotations already indicate readOnlyHint=true and idempotentHint=true. The description adds valuable context: returns options timed to a flight arrival, door-to-door travel, and current coverage details. 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?

Three sentences, no fluff. First sentence defines what it searches, second adds timing and coverage details, third gives usage guidance. Well-structured and 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?

Given 8 parameters, 1 required, and no output schema, the description covers the main use case and limitations. It explains timing and coverage but does not detail return format or edge cases. Still, it provides sufficient context for selecting the 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?

Input schema covers 100% of parameters with descriptions. The description does not repeat parameter specifics but provides overall context. It adds moderate value by explaining the tool's purpose, but parameter details are already well-documented in 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 ground transportation, car rentals, and rideshare options. It distinguishes itself from sibling tools like search_flights or search_hotels by focusing specifically on ground transport.

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 when to use: when the user wants a rental car, airport transfer, or rideshare. It also mentions availability constraints (live across 15+ US metro areas, rideshare in progress). However, it does not explicitly state when not to use or list alternatives.

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