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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description adds value by specifying the exact information returned (name, version, data sources, license, author), which enriches the behavioral disclosure.

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, clear sentence followed by a parenthetical note. It is front-loaded with purpose and efficient with words, leaving 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 no parameters and no output schema, the description is complete: it lists the specific information returned (name, version, data sources, license, author) and indicates constant availability.

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

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

There are no parameters, so schema coverage is 100%. The description has no need to elaborate on parameters, and the baseline for zero-parameter tools is 4.

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 shows server information including name, version, data sources, license, and author. It distinguishes itself from sibling tools like dallas_nws_alerts which focus on specific data 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?

The phrase 'Always available' indicates no restrictions on when to use this tool. While it doesn't explicitly state when not to use it, the context of being an 'about' tool makes usage intuitive.

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 and idempotent. Description adds 'authoritative source' context. No contradictions; behavioral traits are sufficiently covered.

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, zero waste. Information is front-loaded and efficiently presented.

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 7 optional parameters, no output schema, and no nested objects, description covers tool's purpose and filters well. Missing pagination info but not critical for a search tool.

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

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

Schema coverage is 100% with descriptions. Description lists filter options but does not add extra meaning beyond schema. Baseline score 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 uses specific verb 'Search' and resource 'City of Dallas 311 service requests' with explicit categories. Clearly distinguishes from sibling tools (about, weather alerts, schools).

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?

States when to use (searching 311 requests) and lists filter options. Does not explicitly mention when not to use, but context with siblings implies scope. Adequate for selection.

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

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

Annotations already indicate read-only, open-world, idempotent, non-destructive. The description adds detailed return fields (severity, urgency, headline, description, expiration) and authoritative source, fully disclosing behavior.

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

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

Two concise sentences with front-loaded purpose and essential details. 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?

Despite no output schema, the description specifies return fields, making it complete for a simple read operation. Covers purpose, parameters, defaults, and data source.

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?

All parameters have schema descriptions, and the description adds context on default behavior (central Dallas) and geocoding skipping when using lat/lng, enhancing understanding beyond 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 retrieves active NWS alerts for a Dallas location, lists alert types, and describes returned fields. It distinguishes itself from sibling tools by being weather-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?

The description explains how to use parameters (lat/lng or address) and notes the default to central Dallas. It provides clear usage context without needing explicit 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?

The description fully aligns with annotations (readOnlyHint, idempotentHint, etc.) and adds valuable context: authoritative sources (TEA 2022-2023), fuzzy search behavior, and the limitation regarding attendance zones. It discloses the read-only nature and data recency, exceeding annotation coverage.

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 well-structured with a clear first sentence stating core purpose, followed by search options, returned fields, examples, source citation, and a limitation note. It is informative without excess; however, some sentences could be slightly shorter.

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 7 optional parameters, full schema coverage, no output schema, the description adequately covers expected returns (ratings, sub-scores, enrollment, demographics, etc.), sources, and data freshness. It sets proper expectations for what the tool does and does not do, making it reasonably complete for a lookup tool.

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

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

Schema coverage is 100%, but the description adds meaning beyond parameter descriptions by providing specific examples (e.g., 'Dallas ISD', 'Booker T Washington HSPVA'), clarifying that searches are 'fuzzy contains', and explaining the 'rating' parameter as '2022-2023 overall rating'. This adds practical guidance.

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 ('Look up'), resource ('Texas public schools and their TEA accountability ratings'), and scope ('Search by campus name, district, county, or city'). It lists what is returned and distinguishes itself from siblings by focusing on schools and ratings, while sibling tools cover about, alerts, and 311 services.

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 context for when to use the tool (looking up Texas public schools and ratings) and explicitly states what it does NOT do (address mapping to attendance zones). While it does not mention alternatives, sibling tools are unrelated, so explicit when-not guidance is less critical.

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