Senlay Physical Context

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

With no annotations, the description carries the full burden and does substantial work: it discloses uncertainty ('It may be wrong'), states that unavailable evidence is named rather than inferred, names the human as final authority, and explicitly disclaims lightning detection while clarifying that wind, model precipitation and thunderstorm indications are included. This is exactly the kind of beyond-schema disclosure that matters. It stops short of stating latency, cost, or whether the call is purely read-only, which keeps it off a 5.

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 purpose is front-loaded, but the middle sentence is a run-on that chains a scope exclusion with return contents ('the outcome includes wind and model precipitation and thunderstorm indications and is not lightning detection'), which is harder to parse than it needs to be. The caveat sentence is dense but earns its place; the return-contents list could be tightened.

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 5-parameter, 100%-covered schema with no output schema, the description compensates by describing the shape of the result (thresholds, exceeded conditions, divergence, unknowns, uncertainty) and by flagging the time constraint's implication of current-only assessment. The one remaining gap is the absence of any routing signal relative to get_forecast_trust, which overlaps with the 'historical forecast reliability' claim.

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 lat/lng ranges, the ISO 8601 time pattern, the current-conditions-only constraint, and the domain/field alias agreement rule are all already documented. The description adds only that the assessment is 'at a coordinate' for 'an activity', which is marginal. Baseline 3 applies when the schema does the heavy lifting.

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 the resource (an activity at a coordinate) and enumerates what the response contains (thresholds, exceeded conditions, source divergence, unknowns, uncertainty), so an agent can tell it produces an operability assessment rather than a raw forecast. It also draws a scope boundary against the drone rain/thunderstorm model. However, the framing verb 'decision support' is abstract rather than a concrete action, and no sibling tool (notably get_forecast_trust, which sounds closely related) is named for contrast.

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?

There is no statement of when to call this versus get_forecast_trust, list_domains, or sense_location, and no prerequisites beyond the 'current conditions only' note that lives in the schema, not the description. The only routing information given is a negative scope boundary about a separate drone/thunderstorm model, which is not a sibling tool. The agent must infer that this is the general-purpose assessment endpoint.

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 the full burden and does substantial work: it declares that every value retains provenance, distance, age, measured/predicted status and confidence, that source divergence is surfaced, and that missing required evidence is named rather than estimated. That last clause is a meaningful behavioral promise an agent can rely on. It stops short of stating latency, cost, or any auth/permission requirements.

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 purpose is front-loaded, which is good, but the drone passage is redundant: 'separate model-derived precipitation and thunderstorm context is provided' is restated by 'the outcome includes wind and model precipitation and thunderstorm indications.' Trimming that duplication would tighten the definition noticeably.

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 the description must convey the return shape, and it only does so at the level of properties (provenance, age, confidence, divergence) without any structure or example. For a five-parameter tool with fuzzy, provenance-rich output, an agent still cannot predict what it will receive or how divergence is represented.

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%, including ranges, the ISO 8601 format, the current-conditions-only restriction on time, and the field/domain aliasing rule, so the schema does the heavy lifting and baseline 3 applies. The description adds context about what the domain value changes for drones but does not explain lat/lng precision expectations, time semantics, or the effect of each domain value.

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 first sentence names a specific verb and resource: return physical-world evidence plus historical forecast reliability for a coordinate. That is materially more specific than the bare name, though the abstract phrasing 'physical-world evidence' forces the agent to infer concrete content. It does not name or contrast with siblings like get_forecast_trust or check_operability, which read as closely related.

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 only implied: supply a coordinate, optionally a domain, with a drone-specific branch called out for precipitation/thunderstorm context. There is no explicit statement of when to prefer this over get_forecast_trust or check_operability, and no prerequisites. The 'not lightning detection' clause is a scope limit on the output rather than routing guidance.

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