Vigi-Sky

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

Annotations declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, which align with the safe, read-only nature implied by 'Live Kp/aurora odds'. The description adds that it uses specific data sources and thresholds, which is helpful behavioral context but does not explicitly detail any additional behavioral traits beyond what annotations already cover.

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 that packs source, output type, and key details (thresholds) with no redundant words. It earns its place without any fluff.

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 there is an output schema and annotations cover safety and idempotency, the description adequately completes the picture by specifying data source and France-specific thresholds. However, it could hint at the output shape (e.g., odds, KP index) to further aid an agent, though the output schema likely fills that 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?

Schema description coverage is 75%, so the schema already documents three of four parameters fairly well (lat, lng, lon). The description does not elaborate on parameter meaning, leaving the schema to carry most of the burden. For the required 'lat' parameter, the description adds no extra semantics beyond what the schema provides. 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 the tool as providing 'Live Kp/aurora odds' from a specific source (Vigi-Sky / NOAA) and includes mention of threshold values for France. It is distinct from siblings like 'solar' or 'first_skies', but does not explicitly differentiate itself from them.

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 guidance on when to use this tool versus other astronomy or observation tools. No alternatives or context-based suggestions are provided, leaving the agent to infer usage solely from the name and description.

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, idempotentHint=true, destructiveHint=false, openWorldHint=false, so the safety profile is fully specified. The description adds value by naming 'public MCP' and 'local vigisky-sentinel', indicating scope (public vs local) and transport (stdio/127.0.0.1). This is beyond what annotations provide, earning a 4.

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 of 17 words. It is front-loaded with 'Map of this MCP', immediately conveying purpose. Every phrase adds context: public vs local, tool count (23), transport method. 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, rich annotations, and an output schema (not shown but exists), the description completes the picture by specifying scope and transport. For a discovery/listing tool, this is fully complete.

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?

There are zero parameters, and schema description coverage is 100%, so the schema fully documents the tool. The description does not need to add parameter meaning. Baseline 4 is appropriate given zero params and complete schema coverage; the description earns a 5 because no additional parameter info is needed.

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 says 'Map of this public MCP + the shipped local vigisky-sentinel (23 typed tools, stdio/127.0.0.1)', which clearly indicates it provides an overview or listing of tools. The verb 'Map' implies discovery or cataloging, and it distinguishes itself from 19 sibling tools by not being a domain-specific function.

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 this tool is for exploring available tools, particularly the public MCP and a local set. It doesn't explicitly say when not to use it, but with zero parameters and a read-only idempotent nature, usage context is obvious. It provides a specific number (23 typed tools) and location (stdio/127.0.0.1), which helps in deciding relevance.

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, idempotentHint=true, and destructiveHint=false, informing the agent of safe, non-destructive behavior. The description adds that the tool returns a URL (implying a read operation), which is consistent. However, it does not disclose edge cases like no matching URL, ambiguity handling, or response format. It minimally supplements 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 a single sentence that directly states the tool's purpose with no extraneous words. It is front-loaded and efficient, earning its place without waste.

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?

Despite an output schema existing and simple parameters, the description lacks key information: parameter semantics, usage boundaries, and behavioral details (e.g., what constitutes 'best' URL). It does not guide the agent on how to prepare the query or interpret results beyond the schema. The description is insufficient for complete autonomous use.

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 0% description coverage, meaning the parameter names 'query' and 'lang' carry no documentation. The description fails to clarify that 'query' is the user question and 'lang' is an optional language specifier. With no parameter explanations, the agent cannot determine how to properly populate these fields, causing potential misuse.

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 'Map' and clearly identifies the resource: a user question to a Vigi-Sky or GEIPAN URL. This distinguishes the tool from sibling tools like 'nearby_cases' or 'object_lookup', which serve different functions. The purpose is unambiguous and directly stated.

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 no guidance on when to use this tool versus alternative tools such as 'nearby_cases' or 'iss_passes'. It does not mention any exclusions or contextual clues that would help an agent decide between similar tools. The agent is left to infer usage solely from the tool name and siblings.

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, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds content about Vigi-Sky's doctrine but does not disclose any behavioral traits beyond annotations—e.g., how the optional 'lang' parameter affects output, whether the response is a single string or structured data, or any limits. The description adds minimal value for behavioral understanding.

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 one line and not overly verbose, but it sacrifices clarity for brevity. The list of topics is crammed without structure. A bulleted or more explanatory format would improve scannability. As a single sentence, it is concise but not effectively front-loaded or organized.

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?

Despite having an output schema (which could describe return values), the description fails to explain what the tool actually returns or how to use it. The optional 'lang' parameter is not addressed. The description gives only cryptic hints about content (e.g., 'never UFO detected', 'Hatch vs live corpus'), leaving the agent uncertain about the tool's complete behavior and output structure.

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 a single parameter 'lang' with 0% description coverage and no enums. The description does not mention the parameter or explain its role (e.g., language selection). Schema coverage is low, so the description should compensate, but it provides no semantic information about any parameter.

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 lists topics ('never UFO detected', 'Hatch vs live corpus', 'book ISBN', 'founder') but does not state a clear verb and resource. It is unclear whether the tool returns a text, performs a query, or provides a reference. The phrase 'Vigi-Sky identity and method' hints at documentation retrieval, but the purpose remains vague and does not distinguish it from sibling tools like 'hatch_stats' or 'hypothesis_rank'.

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 guidance on when to use this tool over alternatives. Sibling tools include 'hatch_search', 'hatch_stats', 'hypothesis_rank', etc., but the description offers no context for choosing 'doctrine'. No when-to-use, when-not-to-use, or prerequisite information is 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 declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is already clear. The description adds value by disclosing that queries are 'honest' regarding horizon (lat=44 constraint) and includes cultural sensitivity guidance ('Never "the Indians"'). These go beyond 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 two sentences long and front-loads the purpose. The first sentence is dense but clear; the second provides quick examples. Slightly more context could be added without verbosity, but it's 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 tool's complexity (8 params, cultural sensitivity), the description covers key usage patterns and behavioral nuance well. There is an output schema, so return format details are handled. The description doesn't explain how queries combine parameters or how the horizon honesty constraint works, but it's sufficient for most uses.

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 low at 38%, but the description provides concrete examples of how to use common parameters (q, nation, western, theme, lat). It adds meaning beyond the schema for some parameters, but doesn't cover all 8 parameters (e.g., lang, lng/lon aliases are not mentioned). Baseline adjusted for low coverage, but still only partial compensation.

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 queries 'Ciel des peuples' and lists what it returns (nations, asterisms with RA/Dec, sources, etc.). It's a specific verb-resource combination, but doesn't explicitly distinguish it from siblings like 'object_lookup' or 'asterisms', which is a minor gap.

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 examples of query parameters (e.g., 'nation=dine', 'q=pléiades') which imply usage, but doesn't explicitly state when to use this tool versus alternatives like 'object_lookup' or 'tonight_sky'. No when-not-to-use guidance is given.

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 provide strong behavioral hints: readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds value by noting the geocoding is approximate, which is important behavioral context. No contradictions with 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 very concise at 8 words, front-loading the key verb 'Filter' and resource 'Hatch cases'. The single sentence efficiently conveys the core purpose. Could benefit from slightly more structure or examples.

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 tool has 6 parameters (moderate complexity), 0% schema coverage, but does have an output schema and rich annotations, the description is minimally adequate. It doesn't explain the output format, error cases, the radius_km boundary meaning (20000 km is half the Earth), or the ambiguous lon/lng field.

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 0%, so the description must compensate fully. It explains the purpose of the coordinates (point near which to filter), the country parameter, and the text parameter. However, it doesn't explain the unique 'lon' vs 'lng' choice, the semantics of 'radius_km', or the text search behavior. High reliance on parameter names 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 clearly states the tool filters Hatch cases by proximity to a point, constrained by country and text. The phrase 'Approximate geocode' provides useful accuracy expectations. However, it doesn't differentiate from the sibling tool 'nearby_cases' which may have similar geographic filtering.

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 guidance on when to use this tool versus alternatives like 'nearby_cases', 'hatch_stats', or other search tools. It doesn't mention prerequisites, required coordinate format preferences (lon vs lng), or when text filtering is appropriate.

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 it as read-only, idempotent, and non-destructive. The description adds value by clarifying the data is archived and not live as of 2026, which is critical for an agent to interpret date relevance. No contradiction with 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 exceptionally concise at two sentences, front-loading the key idea of stats and archive status. Every word adds value with no filler.

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 no parameters, comprehensive annotations, and an existing output schema, the description covers the essential 'what' and 'temporal scope'. It could optionally detail the nature of 'wiki lessons' but is sufficient for a read-only tool with schema support.

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?

There are zero parameters, so the description carries no burden for parameter documentation. Baseline 4 is appropriate as no further semantics are needed.

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 identifies the resource ('Hatch UDB stats (decades, countries) + wiki lessons') and implies retrieval/access. It distinguishes from sibling 'hatch_search' by specifying it's static archive data, and notes the temporal scope ('Archive, not live 2026'). The verb is implicit rather than explicit, but the purpose is clear enough.

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 explicit guidance on when to use this tool instead of siblings like 'hatch_search' or others. The description hints at historical data but does not state contexts where stats are preferred over search, nor when the tool should be avoided.

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 indicate readOnlyHint, idempotentHint, and no destructive behavior. The description adds context with 'No origin claim,' which is a behavioral trait beyond the annotations. However, it does not elaborate on the ranking process, limits, or any side effects, so the added value is minimal.

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 extremely concise with two sentences, delivering the core purpose and a key constraint without any wasted words. It is front-loaded and easy to parse.

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 enums, annotations covering safety, and an output schema assumed to describe return values), the description is minimally sufficient. However, it lacks details on the ranking algorithm, number of hypotheses, or input constraints, so it could be more complete.

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 0% for the single 'description' parameter. The tool description clarifies that the input is a 'free-text sighting,' which adds meaning beyond the bare schema type. This is adequate but not extensive, as it does not specify format, length, or example content.

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 it ranks natural hypotheses from a free-text sighting, which is a specific verb+resource. It distinguishes from siblings like 'identify' or 'object_lookup' by focusing on ranking hypotheses rather than identification. However, the phrase 'cheap natural hypotheses' is somewhat jargon and could be clearer.

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 does not provide explicit guidance on when to use this tool versus alternatives. It only mentions 'No origin claim,' which hints at a scope but does not clarify when to prefer this over siblings like 'identify' or 'nearby_cases.' No when-not or alternative tools are mentioned.

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, destructiveHint=false, idempotentHint=true, and openWorldHint=true, so the agent knows the tool is safe, idempotent, and has an open-world result. The description adds value with the three possible verdicts and the explicit 'Never UFO detected' caveat, which clarifies limitations beyond annotations. No contradictions.

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 and front-loads the key action. It is concise and avoids fluff, though the 'Never UFO detected' sentence could be integrated into the first or placed as a separate note. Every sentence serves a purpose.

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 tool has 7 parameters (57% schema coverage), an output schema, and no nested objects, the description covers the essential behavior (matching, verdicts) and edge case (no UFO). It does not detail the output format, but the output schema is present, so that is acceptable. It could mention what the tool does with the 'lon'/'lng' alias more explicitly, but overall it is complete for its complexity.

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 57%, and the description does not detail individual parameters. However, the description's high-level explanation of the tool's purpose (matching azimuth/elevation/time to satellites) provides enough semantic context for the required parameters (az, el, lat, time). The 'lon' and 'lng' alias is documented in the schema. The description could have added more detail on the 'lang' or optional parameters, but the core meaning is clear.

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 specific verbs ('Match') and resources ('timed azimuth/elevation to known bright satellites'), and distinguishes from siblings—none of the sibling tools (e.g., object_lookup, iss_passes) suggest the same satellite identification function. The three possible verdicts are enumerated, which clarifies the output scope.

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 clearly states the tool's function (matching observations to satellites) and implies its use case (when an agent has a timed observation), but it does not explicitly exclude alternatives or state when not to use it. The verdict list and 'Never UFO detected' provide some usage boundaries, but no sibling comparisons are made.

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, idempotentHint, and destructiveHint, covering safety and idempotency. The description adds that it uses the SGP4 algorithm and explains the night_only filter's effect. This adds some behavioral context beyond annotations but does not cover rate limits, authentication, or what 'bright' means. Value is modest.

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 (17 words) frontload the core purpose. No redundant or filler content. Every clause adds value. Ideal length for quick scanning.

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 7 parameters, output schema present, and annotations available, the description adequately covers the basic purpose and a key parameter. However, it lacks usage context (e.g., typical scenario, how results relate to output schema) and does not help an agent choose between this and sibling tools like starlink_trains. It is minimally complete for a simple tool but has notable 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 only 43% (3 of 7 parameters described in schema: lat, lng, lon). The description explains the night_only parameter's effect, adding meaning for one more parameter. However, lang, limit, and include_tle remain undocumented in both schema and description. The compensation is partial.

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 it provides 'upcoming bright satellite/ISS passes' and mentions the SGP4 algorithm. The verb 'upcoming' plus resource 'satellite/ISS passes' is specific. However, it does not explicitly differentiate from sibling tools like 'starlink_trains' or 'object_lookup', though the topic is distinct enough.

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 guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., requiring a date/time), nor does it state when night_only should be set to true in a broader recommendation. Sibling tools exist but no comparisons are made.

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 provide readOnlyHint, idempotentHint, and destructiveHint=false, so the description does not need extensive behavioral disclosure. The mention of 'via Vigi-Sky' slightly adds context about data provenance, but no further traits are revealed. This is adequate given the annotation coverage.

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-front-loaded sentence. It is concise and immediately communicates the purpose. However, it could be slightly more informative without adding length, such as hinting at the output type.

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 tool with solid annotations and an output schema, the description is essentially complete. It answers the core 'what does it do?' question. The existence of an output schema reduces the need to describe return values explicitly.

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?

There are zero parameters, so schema coverage is 100% by default. The baseline for 0 parameters is 4. The description does not need to explain parameters; 'via Vigi-Sky' is a peripheral detail about the tool's backend.

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 returns NASA's Astronomy Picture of the Day, specifying the source and service ('via Vigi-Sky'). It is the only APOD-related tool among 19 siblings, so there is no confusion with alternatives.

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 no guidance on when to use this tool versus other astronomy tools like 'aurora', 'solar', or 'object_lookup'. Without any context on use cases or exclusions, the agent must infer entirely from the name and siblings.

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 provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds important context beyond annotations: archive nature (UDB), date range (1900–2002), and approximate geocoding precision. This is valuable behavior disclosure that annotations alone do not convey.

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 extremely concise: two sentences with no wasted words. Every sentence is front-loaded with the core action and adds a critical qualifier (date range, geocoding precision, distinction from live reports).

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 tool has 5 parameters, moderate schema coverage, and an output schema (so return values need no description), the description is adequately complete. It covers what the tool does, data scope, precision, and clarifies it's not live data. The only minor gap is not mentioning that lat is required and lon/lng are aliases, but the schema covers that.

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 60%, and the description does not repeat parameter details. The description provides high-level context (historical archive, approximate geocode) that helps interpret parameters like radius_km and lang. For the 40% of undocumented parameters, the tool's overall purpose compensates somewhat. A minor point: the description doesn't explicitly guide on the lon/lng alias choice.

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 explicitly states the tool finds historical Hatch UDB cases near a point, with specific date range (1900–2002) and approximate geocode. It clearly distinguishes itself from live Vigi-Sky reports and by context from siblings like hatch_search and hatch_stats.

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 clearly indicates the tool is for historical archive data (1900–2002) and not live reports, which helps the agent choose between this and live-report tools. However, it does not explicitly state when not to use it or name sibling alternatives, though the context signals show many related 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?

Annotations already provide readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the tool's safety is clear. The description adds the note '(astronomy, not UAP)' which clarifies the scope (avoids confusion with UFO/UAP domains). This adds value beyond 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?

A single sentence with a parenthetical clarification—extremely concise and front-loaded with purpose. Every word is earned; no fluff.

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 0 parameters, a clear description, and an output schema present, the tool definition is fairly complete. The description doesn't detail return values, but the output schema covers that. Could mention the data source or reliability briefly, but overall sufficient.

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 0 parameters and schema description coverage is 100%, so no additional parameter meaning is needed. The description does not need to compensate, earning a baseline of 4 due to schema coverage, but since there are no parameters, a 3 is adequate as there is nothing to add.

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 lists near-Earth objects for today, which is specific and distinct from sibling tools like 'iss_passes' or 'nasa_apod'. However, it doesn't differentiate from tools like 'object_lookup' or 'first_skies' which could overlap in purpose.

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 today's NEO data, but there are no explicit guidelines on when to use this vs alternatives like 'object_lookup' (which may cover historical or broader objects). No when-not-to-use or prerequisite info.

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, destructiveHint=false, and idempotentHint=true, covering the safety profile. The description adds that the tool is 'currently empty', which is a behavioral state beyond the annotations. It does not contradict any annotation. However, it does not disclose other traits like return format or pagination, which would be useful given the output schema exists.

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 that is front-loaded with the purpose and ends with a candid note about emptiness. Every word serves a purpose, with no redundancy. It is highly concise for a zero-parameter tool.

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 tool's simplicity (no parameters, annotations covering safety, output schema exists), the description is reasonably complete. It states the resource and current state. However, it could be improved by briefly describing what the reports contain when not empty, to better inform the agent about expected data.

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?

With zero parameters, the baseline is 4 per instructions. The input schema has 100% coverage (trivially, since no params). The description does not need to add parameter meaning, and it correctly avoids irrelevant details. No enhancement needed.

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 'Public Sentinel night reports' clearly identifies the resource as a collection of night reports from Sentinel, implying a read operation. It distinguishes from sibling tools like 'aurora' or 'tonight_sky' by specifying the data source. The honesty about being empty adds context. However, it lacks a verb like 'get' or 'list', which would make it slightly more explicit.

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 no guidance on when to use this tool versus alternatives. Given the sibling tools (e.g., 'observation_conditions', 'tonight_sky'), there is no differentiation or use case context. The 'currently empty' note is a factual state, not 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds 'No silent default', which is a useful behavioral trait beyond annotations (ensuring the agent must supply a query). However, it does not disclose other behaviors like error handling, rate limits, or output nature, though the return format is presumably covered by the output schema.

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 extremely concise: two sentences, no wasted words. The first sentence front-loads the purpose, and the second provides the key input requirement. It could be slightly more informative about the return format without sacrificing brevity, but overall it is well-structured for a simple tool.

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 tool's simplicity (one parameter, no nested objects) and the presence of an output schema (which covers return values per the guidelines), the description is minimally adequate. It explains the input requirement and gives examples. However, it lacks details on the output content (e.g., what a 'hint' includes) and error cases, which could affect an agent's ability to fully understand the tool's capabilities.

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 has 0% description coverage for the sole parameter 'q'. The description compensates by providing example values (M31, M42, M45) and stating it is required. This adds meaning beyond the bare schema, showing the expected format (Messier catalog designations). However, it does not explain whether other deep-sky object IDs (e.g., NGC) are accepted, leaving some ambiguity.

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 'Quick Messier/deep-sky hint' clearly states the tool's purpose: looking up quick information about Messier objects and deep-sky objects. It implies a verb (lookup/hint) and a specific resource category. However, it does not fully differentiate from sibling tools like 'identify' or 'nights_network', which might also involve object lookup, but the scope is narrowed to Messier/deep-sky.

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 input format guidance ('q is required (M31, M42, M45…)') but no explicit direction on when to use this tool versus alternatives. It lacks context about alternative tools for similar tasks, such as 'identify' for unknown objects or 'nights_network' for broader sky info. The agent receives no 'when-not-to-use' 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?

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds the context that the tool computes a score for night/moon/solar conditions, which is valuable but does not disclose return format, range, or any other behavioral traits. It does not contradict 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 two sentences with no wasted words. The first sentence front-loads the core purpose, and the second sentence provides a crucial negative clarification. Every sentence 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?

Despite having annotations, a high schema coverage, and an output schema, the description is very brief. It does not explain the score's range, interpretation, or any caveats about location or time. For a score-computing tool with many sibling tools, this leaves ambiguity.

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 75% with lat, lng, lon, and lang all described. The tool description adds no additional parameter-level meaning; it only provides overall context. Given the high schema coverage, a 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 clearly states the tool evaluates observing conditions (night, moon, solar) and explicitly distinguishes it from a UFO-appearance probability. This verb+resource framing is specific and differentiates from sibling tools like 'aurora', 'solar', and 'nights_network'.

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 a negative usage hint (NOT a UFO-appearance probability) but provides no explicit guidance on when to use this tool versus alternatives like 'aurora' or 'tonight_sky'. Usage is implied rather than directed.

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 provide readOnlyHint: true, openWorldHint: true, idempotentHint: true, and destructiveHint: false. The description adds that the data comes from 'Vigi-Sky APIs' (external dependency) and that it is 'Live' (real-time), which is useful context beyond annotations. However, it does not disclose rate limits, data freshness guarantees, or any specific behavior of the API calls.

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 12-word sentence that is front-loaded with the core purpose ('Live solar/CME context') and provides the source ('from Vigi-Sky APIs'). Every word earns its place; there is no redundancy or fluff.

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 an existing output schema (which presumably defines the return structure), the description is sufficient. It names the two main data categories (solar/CME context and Kp) and the source. It could be slightly more specific about what 'solar/CME context' includes (e.g., flares, CMEs), but the output schema likely covers that, so completeness is adequate.

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?

There are no parameters (input schema is empty), so per the guidelines baseline is 4. The description adds meaning by explaining what the tool returns (solar/CME context and Kp), which compensates for the lack of parameters. The schema coverage is trivially 100% as there are none.

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 it provides 'Live solar/CME context plus current Kp', using a specific verb ('Live') and naming the specific resource (solar/CME context and Kp index). It distinguishes from siblings like 'aurora' (which likely focuses on aurora forecasts) and 'observation_conditions' (broader conditions) by focusing on solar activity and geomagnetic index.

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 explicit guidance on when to use this tool versus alternatives. Siblings include 'aurora' and 'observation_conditions', which might overlap, but the description does not provide any when-to-use or when-not-to-use advice. The agent is left to infer from the tool 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?

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, which clearly indicate a safe, read-only, potentially stateful operation. The description adds that it returns 'count + launch id', which is useful output context. However, it does not explain behavior over time (e.g., whether trains are ephemeral) or data freshness. Given the strong annotations, this is adequate.

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 that captures the essence of the tool. Every word is meaningful: 'recently launched' sets context, 'Starlink trains' identifies the resource, and 'count + launch id' specifies the data fields. 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 the simplicity of the tool (0 parameters, well-covered by annotations) and the presence of an output schema (which describes return format), the description is mostly complete for basic understanding. However, it does not clarify whether 'recently launched' refers to days or weeks, nor does it explain if the tool filters by the user's location. With sibling tools like 'first_skies' and 'nights_network', the agent might benefit from more context on how this relates to actual visibility.

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 0 parameters and schema description coverage is 100%, so the description does not need to add parameter details. It mentions the specific data returned (count and launch id), which adds value beyond the schema of empty properties. This is a clear and helpful addition.

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 the verb 'launched' and specifies the resource 'Starlink trains', indicating a listing of recent Starlink train sightings. It mentions two data points (count and launch id) which clarifies the output. It does not explicitly differentiate from sibling tools like 'aurora' or 'iss_passes', but the resource name is distinctive enough.

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 no guidance on when to use this tool versus alternatives such as 'nights_network' or 'iss_passes'. There is no mention of prerequisites, frequency of updates, or typical use cases. The context signals show 0 parameters, so the tool is simple, but the agent would benefit from knowing that this is for recently launched trains specifically.

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, openWorldHint, idempotentHint, and destructiveHint, making the tool's safe, read-only, and non-destructive nature clear. The description adds context about the specific data (API health, archive size, observation counts) without contradicting annotations, but does not reveal additional behavioral traits (e.g., caching behavior, authentication 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 description is extremely concise, using a single sentence with a list to convey all key outputs. Every word earns its place, and there is no redundancy or filler.

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 tool has no parameters and an output schema exists, the description is sufficiently complete for a status/health endpoint. It covers the key data categories returned. The only minor gap is not mentioning that the output schema fully describes the structure, but the context signal already notes it has an output schema.

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 zero parameters and schema description coverage is 100%, so the description does not need to explain parameters. The description adds meaning by listing the types of data returned, which is helpful beyond the empty 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 provides Vigi-Sky API health, Hatch archive size, and public observation counts. It references a specific resource (the Vigi-Sky API and related stats) and uses a clear verb ("health, ... size, ... counts"), though it does not explicitly distinguish it from sibling tools like 'capabilities'.

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 lists what data the tool returns, but provides no guidance on when to use this tool over alternatives, such as 'capabilities' or 'hatch_stats'. It implies usage for checking system status and counts, but lacks explicit when/when-not or alternative references.

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, openWorldHint, idempotentHint as true, and destructiveHint as false, making the safe, non-destructive nature clear. The only behavioral addition in the description is the default 'night_only=true' setting, which is useful but minor. No contradictions with 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 two sentences long, very concise, and front-loads the main outputs. However, the second sentence about night_only could be integrated more smoothly.

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 tool has a moderate parameter count (5) with an output schema, and annotations are fairly complete. The description covers core outputs but omits details on how to interpret Kp values, what 'next potentially visible satellite pass' means, and format of asterisms. With an output schema existing, return structure explanation is not needed, but usage context is still sparse.

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 already defines all five parameters with descriptions, achieving 60% coverage. The description only mentions 'night_only' explicitly (its default), adding no detail on lat, lng/lon aliasing, or lang. It does not compensate for the 40% of schema parameters lacking descriptions.

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 lists specific outputs: 'Kp + next potentially visible satellite pass + First Skies asterisms', clearly naming the key resources returned. It also mentions the default night_only parameter, adding useful scope. However, it does not differentiate from sibling tools like 'aurora', 'iss_passes', or 'first_skies', which may overlap.

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 no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, typical use cases, or when not to use it. With many sibling tools covering related astronomical topics, this is a significant gap.

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