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

With no annotations provided, the description carries the full disclosure burden. It usefully reveals the 200-camera limit and points to an alternative for complete counts. However, it does not mention output shape, pagination behavior, error conditions, or any access requirements, leaving notable behavioral gaps.

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 deliver the essential information with no filler. The primary purpose is stated first, and the critical operational caveat (200-camera limit) plus the alternative tool are provided in the second sentence, which is ideal for an agent scanning descriptions.

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 moderately simple list tool, the description covers the main operational caveat (result cap) and directs the agent to the correct sibling for full counts. It lacks an output schema and has no annotations, but the core information needed to scope and call the tool correctly is present.

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%, so the schema already explains state, route, and live_only. The description adds a route example and restates the two-letter state requirement, but it does not meaningfully expand on parameter semantics 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 states a specific verb ('List'), a clear resource ('traffic cameras'), and a precise scope ('for a US state (two-letter code)'), with an optional route filter. It also names state_uptime as a distinct tool for full fleet counts, helping separate it from a sibling at a glance.

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 explicitly tells the agent when to avoid this tool: if full fleet counts are needed, use state_uptime instead. It does not explicitly contrast with cameras_for_entity or camera_status, but the state-scoped purpose is clear enough to infer most usage boundaries.

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 must carry the transparency burden alone; it does clearly indicate a read-only operation and discloses that the result includes the matching livetrafficcam.com page URL. However, it does not explain behavior for unknown slugs, pagination, or any further response conventions, so it only reaches adequate transparency.

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 conveys purpose, scope, slug format, and one important output detail. It contains no filler and does not restate the parameter name.

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 one-parameter list tool with no output schema or annotations, the description covers the input contract and at least one key output element (the page URL). It could be more complete about other returned camera fields or error/empty behavior, but nothing essential for invoking it correctly is missing.

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 already fully documents entity_slug, so the baseline is 3, but the description adds meaning by specifying that the slug represents a pass, corridor, bridge, or tunnel and by providing two realistic examples (donner-pass, snoqualmie-pass) beyond the schema's single example.

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 opens with a specific verb ('List') and a precise resource ('traffic cameras for a named pass, corridor, bridge, or tunnel'), scoped by slug with concrete examples. This makes it distinct from siblings like cameras_by_state, which target states rather than entity slugs.

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 phrasing 'for a named pass, corridor, bridge, or tunnel by its slug' clearly communicates when to use this tool: when you have an entity slug. It does not explicitly name alternatives or when-not conditions, but the use case is strongly implied and unambiguous.

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 provided, the description carries the behavioral burden. It communicates that this is a read-style status lookup and enumerates what the result contains. It does not discuss rate limits, auth, or side effects, but 'Live status of one camera' strongly implies a non-mutating query.

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 compact sentences. The first establishes the tool's output, and the second explains how to address a specific camera. There is no filler or repetition of schema details.

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?

There is no output schema, so describing the return contents in prose is important and is done well. The main gap is not explicitly stating whether exactly one of name, slug, or camera_id is required, but the overall description is sufficient for a straightforward status lookup.

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%, giving the baseline 3. The description adds real value by explaining that the camera can be identified by id, slug, OR name fragment, and that these are scoped within a state. This clarifies the relationship between state and the optional identifier parameters beyond the schema alone.

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 names a specific verb ('Live status'), a clear resource ('one camera'), and the key output fields (verified-live state, last live time, source URL, attribution). This distinguishes it from siblings like cameras_by_state (listing) and state_uptime (state-level status).

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 clearly implies this is for fetching status of a single camera using id, slug, or name fragment within a state. However, it does not explicitly say when to prefer this over cameras_by_state or state_uptime, nor does it state that one of the identifiers should be supplied.

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 communicates that this is a list operation and adds that counts originate from the measured camera uptime report, which provides useful provenance. However, the 'liveness summary' is not defined, and with no annotations providing safety or behavior hints, some behavioral context is left unstated.

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 two concise sentences: the first states the action and result, the second adds data provenance. There is no redundant wording or filler, and the key information is front-loaded.

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 zero-parameter list operation, the description covers the scope, the per-state grouping, and the two output categories: camera counts and liveness summary. It could define 'liveness summary' more precisely, but overall it is sufficient for an agent to 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 tool has zero parameters and the input schema is empty with 100% description coverage, so there are no parameter semantics for the description to clarify. This matches the baseline for a no-parameter tool.

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 a specific verb ('List') and resource ('US states covered by livetrafficcam.com'), and it specifies the output contents: camera counts and a liveness summary per state. It does not explicitly differentiate itself from sibling tools like state_uptime or cameras_by_state, but its scope is reasonably distinct.

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?

No guidance is given about when to prefer this tool over the sibling tools. There is no mention of alternatives, conditions, or exclusion criteria, so an agent must infer usage from the name and description alone.

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 itself carries the disclosure burden. It states the output content (live/stale/dead counts, 14-day check success rate), notes the temporal scope ('right now'), and adds a practical behavioral instruction to cite the report URL. It does not mention rate limits or data freshness, but the tool appears to be a straightforward read-only report.

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 two sentences with no wasted words. "no waste" and front-loads the core function before the citation requirement.

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?

The description adequately explains what the tool returns (live/stale/dead counts and success rate) and the report URL citation rule. Since there is no output schema, this is necessary and sufficient for a simple query tool. It does not cover invalid state handling, but that 's a minor gap.

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 has full description coverage for the single 'state' parameter, including format and example. The description adds no new parameter semantics beyond confirming 'one state,' which is appropriate given the schema is already complete.

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 a specific action and resource: measuring camera uptime for a single state, including live/stale/dead counts and a 14-day success rate. It does not explicitly name sibling tools, but the resource scope ('one state') and aggregate report nature distinguish it from camera-level or listing 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 implies usage context: it is for aggregated uptime reporting per state, not for individual camera status or camera lists. However, it does not explicitly state when to prefer this tool over its siblings or provide exclusions such as 'use camera_status for a single camera.'

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