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

The annotations already declare readOnlyHint=true and destructiveHint=false, indicating a safe read operation. The description adds 'Always available' as a behavioral trait beyond the annotations, and specifies the fields returned, which is useful 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 that front-loads the action ('Show information') and immediately lists the key contents. The parenthetical URL and 'Always available' add useful context 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?

Given the tool's simplicity (no parameters, no output schema), the description fully explains what the tool does, what information it returns, and that it is always accessible. No additional details are needed for an agent to invoke it 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?

The tool has zero parameters, and the description correctly makes no mention of any. According to the rubric, a 0-parameter tool receives a baseline score of 4, as there are no parameter semantics to clarify.

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 begins with 'Show information about this MCP server,' a specific verb and resource. It lists the exact information provided (name, version, data sources, license, author) and is clearly distinct from the sibling tools about NWS alerts and TEA 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?

The phrase 'Always available' provides clear context that the tool can be called without prerequisites or special conditions. There are no explicit alternatives or when-not-to-use instructions, but the tool's purpose is so straightforward that no exclusions are necessary.

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 mark the tool as read-only, idempotent, and non-destructive. The description adds useful behavioral context beyond annotations by specifying the return fields (severity, urgency, headline, description, expiration time) and the default-central-Houston behavior. No contradictions with annotations; no hidden destructive or stateful behavior is implied.

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, front-loaded with the core purpose, and every sentence adds specific value: alert types, default location, return fields, and authoritative source. No filler or redundancy.

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

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

With three optional parameters, no output schema, and strong annotations, the description adequately explains what the tool does, what it returns, and when the default applies. It could mention edge cases like lat/lng outside Houston or geocoding failures, but overall it is complete enough for an agent to select 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?

The input schema provides 100% coverage for all three parameters, so the baseline is 3. The description reinforces the default behavior already stated in the schema ('If omitted, defaults to central Houston') but does not add significant new meaning beyond what the schema 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 the tool retrieves active National Weather Service alerts for a specific Houston location, listing alert types and the return data fields. This distinguishes it from siblings like 'about' and 'houston_tea_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?

The description provides clear context: it is for a specific Houston location, defaults to central Houston when no address is supplied, and relies on the National Weather Service as the authoritative source. It does not explicitly name alternatives or exclusion scenarios, but none appear necessary given the sibling tools.

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

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

Annotations already declare read-only, idempotent, non-destructive. The description adds useful context: authoritative sources (TEA, AskTED), data vintage (2022-2023), the specific return fields, and the limitation about attendance zones. This goes beyond 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 appropriately sized, front-loaded with purpose, then search criteria, return fields, examples, sources, and limitation. 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?

Despite no output schema, the description explains exactly what data is returned (ratings, sub-scores, enrollment, etc.), sources, and limitations. With 7 optional parameters and zero required, it gives sufficient context for an agent to select and invoke 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, including enums and defaults. The description only restates search fields and examples, not adding significant meaning beyond schema. 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?

The description states a specific verb and resource: 'Look up Texas public schools and their TEA accountability ratings.' It clearly distinguishes from siblings by focusing on school data rather than app info or weather alerts.

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

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

The description gives explicit search criteria (campus, district, county, or city), example districts, and explicitly states a when-not-to-use ('does NOT map an address to its assigned schools'). However, it does not name an alternative tool, so it falls short of a 5.

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