Senlay Physical Context

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

With no annotations provided, the description carries the behavioral disclosure burden. It does this well by stating that results may be wrong, unavailable evidence is named rather than inferred, and a human remains the final authority, while also exposing assessment uncertainty. This gives the agent valuable expectations about reliability and limits without contradicting structured metadata.

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 compact, front-loaded with the core purpose, and uses its sentences to convey purpose, outputs, and caveats. There is little waste, though the phrase 'including historical forecast reliability when established' is slightly vague and could be sharper.

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 that there is no output schema and no annotations, the description provides a useful inventory of return categories and explicitly discloses uncertainty and fallibility. It is sufficient for a competent agent to select and invoke the tool, though it would benefit from more detail on output structure and clearer sibling differentiation.

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 fully documents lat, lng, time, and domain. The description adds only a mild semantic link by framing the call as an activity at a coordinate but does not provide parameter-specific detail beyond the schema, so the baseline score of 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 identifies a decision-support purpose for an activity at a coordinate and names the main outputs: thresholds, exceeded conditions, source divergence, unknowns, and uncertainty. It is specific enough to separate it from generic lookups, though it does not explicitly contrast with siblings like get_forecast_trust.

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?

Usage is implied: an agent would call this when it needs operational decision support for a domain at a location. However, there is no explicit guidance about when not to use it, no mention of alternatives such as get_forecast_trust, and no prerequisite or exclusion criteria.

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 annotations already mark the tool read-only, idempotent, and open-world, but the description adds meaningful behavioral detail beyond those hints: it reports UNKNOWN until Core has enough eligible archived forecast-versus-instrument pairs, never corrects forecasts, and never predicts regime end. This explains the tool's safety profile and limitations clearly. There is no contradiction with 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?

The description is compact: it states the core function, the sentinel behavior, the exclusions, and the decision-support framing in only three sentences. Every sentence adds distinct information, and the most important purpose statement is front-loaded. There is no filler or redundant restatement of the tool 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 simple two-parameter read-only tool, the description covers most of what an agent needs: the result concept, the separate dimensions of wind speed and direction, the UNKNOWN sentinel condition, and the main limitations. However, there is no output schema, and the description does not specify the exact return shape, scale, or value type for reliability, which leaves a small gap for an agent trying to interpret the response.

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%, with lat and lng each described by range and meaning. The description only adds 'at a coordinate', which maps directly to the two parameters but does not add new semantic detail such as coordinate format, precision, or handling. With full schema coverage, the baseline of 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 opens with a specific verb ('Return') and a clearly defined resource ('historical forecast reliability at a coordinate'), and further narrows it by stating output is separated for wind speed and direction. This is distinguishable from the sibling tools on its face: check_operability, list_domains, and sense_location all have different implied purposes. The closing 'Decision support' clarifies the intended role without ambiguity.

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 useful context for when to rely on the tool ('Decision support') and explicitly states what it is not for: it 'never corrects a forecast or predicts when a regime will end.' This gives the agent guardrails against misuse. However, it does not name any alternative tool for those excluded use cases, so it stops short of full when-to-use-versus-alternative guidance.

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 and idempotent, so the description's job is lighter. It adds value by disclosing that the tool provides only a brief of evidence and threshold logic and that actual thresholds and assessments always come from Senlay Core, which manages expectations about the authority of the returned information.

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 well-structured sentence that front-loads the action and resource, then adds essential detail about what the listing includes and the important caveat about Senlay Core. No words are wasted.

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 zero-parameter, read-only listing tool, the description is complete: it states what is listed, what detail is provided, and the limitation of the information. There are no missing operational details that an agent would need 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 an empty schema, so there is no parameter burden to describe. The description appropriately focuses on the output content rather than inputs, matching the baseline expected 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 states a specific verb and resource: 'List the operational domains accepted by Senlay' and indicates the content included (evidence and threshold logic). This makes the tool's identity clear and distinguishable from siblings like check_operability and sense_location.

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 the tool is used to get an inventory of operational domains and their threshold logic, but it does not explicitly state when to prefer this over its siblings or when not to use it. The caveat about Senlay Core provides some context but no direct alternative guidance.

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 full behavioral burden and does well: it guarantees provenance, distance, age, measured/predicted status, confidence, and source divergence reporting, and states that unavailable required evidence is named rather than estimated. This is substantial transparency for a read-style retrieval 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?

Three dense sentences front-load the core purpose and then expand with high-value behavioral guarantees. No filler words; every sentence contributes.

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?

No output schema exists, so the description must communicate return semantics, and it does by enumerating the preserved attributes and the missing-evidence policy. It could be more complete by specifying response format or units, but the essential contract for a caller 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 coverage is 100%, so the baseline is 3. The description adds conceptual context by framing lat/lng as a 'coordinate' and mentioning historical reliability, which lightly relates to the time parameter, but it adds no parameter-level syntax 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 opens with a specific verb ('Return') and a precise object: current physical-world evidence and historical forecast reliability for a coordinate. This makes the core function clear. It does not explicitly distinguish itself from get_forecast_trust, but the evidence-focused wording separates it from list_domains and check_operability.

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 the tool is for obtaining coordinate-bound evidence and reliability data, but it never states when to prefer it over the sibling tools or when not to use it. No exclusions or alternative routing are provided, so the agent must infer usage from the purpose statement.

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