telecom-truth

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, covering safety and determinism. The description adds meaningful context beyond annotations by promising 'honest numbers with their grain and vintage stated,' which informs the user about data quality and temporal provenance—a useful behavioral trait not captured in structured 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 concise and front-loaded, presenting the core purpose and expected outputs in a single, information-dense sentence. The second sentence gives necessary input instructions. Every clause adds value, with no filler or redundant repetition.

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 absence of an output schema, the description adequately outlines the return content (providers count, fiber share, technologies) and mentions metadata ('grain and vintage'). It is sufficient for a simple two-parameter read-only intelligence tool, though it could benefit from a more explicit statement about the output format or units.

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 both 'city' and 'state', so the baseline is 3. The description reinforces the parameter format ('Give city and two-letter state') but adds little beyond the schema, except for clarifying the US-only scope, which is already implied by the word 'US' in the description. No new semantic depth is provided for the parameters.

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 specifies the tool's function: it provides city-level coverage intelligence including number of providers, fiber availability share, and dominant technologies. It distinguishes itself from sibling tools by focusing on aggregate city statistics rather than individual availability checks or provider profiles.

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 by stating the required inputs ('Give city and two-letter state') and the scope ('for a US city'), but it does not explicitly contrast with sibling tools or state when to choose this over alternatives. No exclusions or alternative recommendations are provided.

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 establish read-only and idempotent behavior. The description adds valuable context about return content (fiber-first ordering, FCC filing vintage, live page link) and data provenance (cross-verified evidence ledger), enhancing transparency beyond the 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, front-loaded with the core purpose, then efficiently packing input methods, output details, and data source. 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?

For a lookup tool with no output schema, the description covers what the tool does, inputs, outputs, and data quality. It is suitably complete given the tool's straightforward nature.

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 all 4 parameters with descriptions, providing a baseline of 3. The description adds semantic value by framing lat/lng and address as alternatives and noting location_id comes from a previous call, clarifying how to choose among them.

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: 'Authoritative internet availability for one US location' and details what it returns (every provider, technology, speeds). It distinguishes itself from siblings like area_intelligence and provider_profile by focusing on location-specific availability.

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 input options ('street address, lat/lng, or an FCC location_id') and indicates reuse from previous calls. Clear context for when to use, but no explicit exclusions or 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 declare read-only and idempotent hints, so the description doesn't need to discuss safety. It adds useful behavioral context by enumerating the data included (providers, locations, tech mix, vintages) and confirming there is no geographic filtering below national level.

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 deliver the full value: the first enumerates the data dimensions, the second states the intended use case. No fluff or repetition.

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 no output schema, the description carries the burden of explaining return values, and it lists the main categories (providers, locations, tech mix, vintages). The phrase 'filing vintages held' is slightly technical, but sufficient for an overview tool with no 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?

The tool has zero parameters, so the schema provides no input guidance. Baseline is 4; the description appropriately focuses on output content rather than inputs, leaving no parameter semantics gap.

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 what the tool provides: US telecom market data at national scale, including providers, locations, technology mix, and filing vintages. It distinguishes itself from local/area-focused siblings by emphasizing 'national scale' and 'market context,' though it lacks an explicit verb like 'get' or 'list.'

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?

It gives clear context for when to use it: for questions about the US broadband industry, the fiber transition, or market size. It does not explicitly name alternatives or say when not to use it, but the national vs. local distinction implies the boundary.

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 and idempotentHint=true, so the description builds on that by detailing what data is returned (fiber density, competition, speeds, etc.). It adds the 'herd-mentality' framing, giving context beyond a bare read operation. It does not describe return format or pagination, but with readOnlyHint covering the safety profile, this is sufficient.

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, each earning its place: first defines what the tool returns, second explains the conceptual context, third gives input instructions. It is front-loaded with the core purpose and avoids redundancy, making it an efficient and well-structured description.

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 absence of an output schema, the description does a good job listing the key output dimensions (FCC locations, providers, fiber density, speeds) and explains why this data matters (herd-mentality). It could be more explicit about response structure or edge cases, but for a read-only lookup tool, it conveys the essential information.

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% (lat, lng, hex_id each described). The description adds meaningful context by specifying 'any US coordinate', the hex resolution (~0.46 km cells), and that hex_id is a direct alternative to lat/lng. This reinforces and extends the schema descriptions, justifying a score above 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: 'Res-8 hex intelligence (~0.46 km cells) for any US coordinate' with specific data dimensions (FCC locations, providers by technology, fiber density, competition, underserved status, speeds). It distinguishes from siblings by emphasizing the neighborhood scale and 'build-predictability grain', making it unique among area-level tools.

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 implicitly indicates when to use this tool: when you need 'herd-mentality context' or 'build-predictability'. It also specifies input expected ('Give lat+lng, or an H3 res-8 hex_id directly'). It does not explicitly name alternatives or exclusions, but the context of neighborhood-level detail vs. area intelligence is 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 cover read-only and idempotent behavior. The description adds significant context: handling brand variants, listing exact output fields, and noting that the answer pack is only available 'when precomputed'. This exceeds annotation coverage and gives the agent actionable expectations.

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 the core purpose, then output details, followed by explicit usage guidance. Every sentence contributes, with no redundant content.

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 tool with one parameter and no output schema, the description fully covers input semantics, output elements, usage context, and limitations (precomputed answer pack). It is complete for effective tool invocation.

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 schema describes 'name' as 'Provider name or brand as a user said it,' which is already clear. The description adds concrete examples (ATT, Google Fiber) and implies normalization, reinforcing the parameter's flexibility. This is marginal but useful added value over 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's function: returning a canonical profile of a US internet provider by name, with specific outputs (FCC numbers, technologies, etc.). It also distinguishes itself from sibling tools by emphasizing disambiguation and canonical identity, making its purpose unmistakable.

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 a clear use case: 'Use it to disambiguate providers before making claims about them.' However, it does not explicitly name alternatives or state when not to use it, preventing a 5.

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