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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, covering safety and idempotency. The description adds valuable context beyond this: 'Side effects: none (read-only local file access)' clarifies the scope, and 'Cost note: full schema is large' warns about payload size. It doesn't contradict annotations but provides practical 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?

The description is front-loaded with the core purpose, followed by parameter guidance and behavioral notes in a logical flow. Every sentence adds value: the first states the action, the second covers inputs and defaults, the third explains mode usage, and the fourth adds side effects and cost. 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 4 parameters with no schema descriptions and no output schema, the description does well to explain parameter usage, defaults, and behavioral traits. It covers when to use different modes and warnings about payload size. However, it doesn't detail the response format or error handling, leaving some gaps for a tool with multiple parameters.

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 compensates well by explaining parameter purposes: 'mode='summary'' vs. 'full', 'maxPaths=25' for limiting output, 'optional pathPrefix filter' for filtering, and the requirement of 'confirmLargePayload=true' for full mode. It adds meaning beyond the bare schema, though it doesn't detail all constraints like min/max values.

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 specific action ('inspect the BirdWeather OpenAPI contract') and resource ('used by this server'), distinguishing it from sibling tools like get_ebird_api and get_system_prompt. It goes beyond the title by specifying it's for reading the API schema, not just a generic 'read' operation.

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 when to use different modes: 'summary is preferred for planning' and 'Set mode='full' with confirmLargePayload=true for full schema.' It also mentions 'optional pathPrefix filter' for specific use cases, offering clear alternatives within the tool itself.

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

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

The description adds valuable behavioral context beyond annotations: it notes 'side effects: none (read-only local file access)' and 'Cost note: full schema is large; use summary first.' While annotations already indicate readOnlyHint=true and idempotentHint=true, the description provides practical implementation details about payload size and local access.

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 efficiently structured: it starts with the core purpose, lists required inputs, explains defaults and options, and ends with behavioral notes. Every sentence adds value without redundancy, making it 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?

Given the tool's moderate complexity (4 parameters, no output schema), the description is mostly complete: it covers purpose, usage, parameters, and behavioral traits. However, it lacks details on return values (since no output schema exists) and doesn't fully explain all parameter 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?

With 0% schema description coverage, the description compensates by explaining parameter semantics: it clarifies that mode has 'summary' and 'full' options, maxPaths defaults to 25, pathPrefix is optional, and confirmLargePayload is required for full mode. However, it doesn't fully explain all parameters (e.g., exact meaning of pathPrefix).

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 with specific verbs ('inspect', 'read') and identifies the resource ('eBird OpenAPI contract used by this server'). It distinguishes from sibling tools like get_birdweather_api by specifying the eBird API schema, not other APIs or system prompts.

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 usage guidance: 'use summary first' due to cost concerns, and specifies when to use mode='full' (with confirmLargePayload=true). It implicitly contrasts with siblings by focusing on eBird API inspection, though it doesn't explicitly 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?

The description adds valuable behavioral context beyond annotations: it notes 'Side effects: none (read-only local file access)' and 'Cost note: full mode can consume significant tokens.' While annotations cover read-only and idempotent aspects, the description provides practical warnings about token consumption and clarifies the access type, enhancing transparency without contradiction.

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

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

The description is highly concise and well-structured: it opens with the usage scenario, lists required inputs and defaults, explains parameter interactions, and adds behavioral notes. Each sentence serves a distinct purpose—no wasted words, and information is front-loaded for 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?

Given the tool's moderate complexity (3 parameters, no output schema), the description is nearly complete: it covers purpose, usage, parameters, and behavioral notes. However, it lacks details on the output format (e.g., what a 'summary' vs. 'full' prompt looks like), leaving a minor gap in contextual understanding.

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 fully compensates by explaining all parameters: it states 'Required inputs: none,' lists defaults for mode and previewLineCount, and details the interaction between mode='full' and confirmLargePayload. This adds essential meaning beyond the bare schema, covering semantics and usage conditions effectively.

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 explicitly states the tool's purpose: 'when you need operational instructions for BirdStats analysis behavior.' It specifies the verb 'read' (implied from title) and resource 'system prompt,' clearly distinguishing it from sibling tools like get_birdweather_api and get_ebird_api, which likely access different data 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?

The description provides explicit usage guidance: 'Use this tool when you need operational instructions for BirdStats analysis behavior.' It also details when to use specific modes (e.g., 'Set mode='full' with confirmLargePayload=true to return full prompt text'), offering clear alternatives within the tool itself.

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