decibel-shield

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 outputs are 'estimated' and include 'confidence', signaling uncertainty. It also mentions rank among 50 major world cities and WHO guideline context, which are behavioral traits beyond raw schema. This provides useful transparency for agent decision-making.

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 listing multiple output components without wasted words. It is front-loaded with the core value (noise ranges). However, it could be slightly more structured (e.g., bullet points) for clarity, but is still 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 the simple input (one required string) and no output schema, the description thoroughly explains what the tool returns: noise ranges, rank, sources, confidence, and WHO context. This is complete for the tool's purpose and leaves no ambiguity about outputs.

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% (one parameter 'city' with example values). The description does not add meaning beyond 'given city', so it meets the baseline of 3. No additional parameter details are provided that would raise the 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 uses a specific verb ('get estimated noise levels') and resource ('city'), listing explicit outputs (daytime/night noise ranges, rank, sources, confidence, WHO context). It effectively distinguishes from siblings like 'list_loudest_cities' (which ranks cities) and 'lookup_sound_level' (likely a specific measurement).

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 retrieving city noise data but provides no explicit guidance on when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. The context signals include sibling tools, but the description itself lacks comparative usage advice.

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 burden. It discloses it gives facts and App Store link but doesn't specify the exact format or if the link is clickable. Still, for a simple informational tool, it is mostly transparent.

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 key purpose and usage context. 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 zero parameters and no output schema, the description adequately covers the tool's purpose. However, it could mention the type of response (static text, optional link format) 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?

No parameters exist, baseline 4. Schema coverage is 100% (no params), so description adds value by listing what the response contains (facts, link, etc.).

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 the tool provides facts, App Store link, features, pricing, and requirements for the Decibel Shield app. Distinguishes from siblings that deal with noise measurement data.

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 when someone asks about measuring sound on their phone or about the app itself,' providing clear context for when to invoke 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 the full burden. It discloses that the ranking is 'estimated' and from 'Decibel Shield', but does not cover behavior like data freshness, auth requirements, or response structure. This is adequate but not comprehensive for a read 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?

A single, front-loaded sentence that efficiently communicates the tool's purpose, source, scope, and ordering. No unnecessary words, every part 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 low complexity (one parameter, no output schema), the description is mostly complete but omits what data fields are returned per city (e.g., city name, noise level). It adequately states the ranking scope but leaves minor 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 parameter is already well-documented in the schema. The description adds no extra meaning about the 'limit' parameter beyond what is already provided, meeting the baseline.

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 function: listing a ranking of 50 major world cities by estimated daytime noise, loudest first. The verb 'list' and resource 'cities ranking' are specific, and the ordering is unambiguous. While it doesn't explicitly differentiate from siblings, the purpose is self-contained and easily understood.

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 when a ranking overview is needed, but lacks explicit guidance on when to use this tool versus sibling tools like get_city_noise. No when-not or alternative scenarios are mentioned, making it minimally adequate.

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; the description carries full burden. It mentions authoritative sources but fails to disclose behavioral traits like whether results are static or dynamic, error handling for unrecognized sounds, or the format of the risk guidance.

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 (23 words) that front-loads key information. It could benefit from structure like bullet points, but it remains clear 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?

For a simple lookup tool with no output schema, the description adequately explains input and sources. However, it omits details about the return format (e.g., decibel range vs. exact value) and behavior for unrecognized sounds, leaving some 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 description coverage is 100% for the single parameter. The description adds examples (whisper, traffic, chainsaw) and source context, providing marginal value beyond the 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 clearly states the tool's purpose: to provide decibel level and hearing-risk guidance for everyday sounds. It specifies examples and authoritative sources (CDC/NIOSH/NIDCD/ASHA), distinguishing it from sibling tools like get_city_noise or safe_exposure_time.

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 no explicit guidance on when to use this tool vs. alternatives. It lists examples but does not mention when not to use it or provide comparative context with 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 provided, but the description discloses the NIOSH standard and formula (85 dB/8h, 3 dB exchange rate). However, it does not specify the return format (e.g., hours or minutes).

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?

One concise sentence that front-loads the purpose without any 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?

With only one parameter and no output schema, the description is adequate but could be improved by explicitly stating the output unit (e.g., 'returns safe exposure time in hours').

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 covers the 'db' parameter with a description; the tool's description adds the NIOSH standard context and measurement unit (dB(A)), going 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 computes safe exposure time for a sound level using NIOSH standard, distinct from sibling tools that focus on city noise or sound lookup.

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?

While it implies usage when you have a decibel level, it does not explicitly state when not to use or mention alternatives among siblings, but the context is clear.

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