Voidly Atlas (hosted)

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful behavioral context beyond that: a caveat that the response update time does not reflect when each underlying measurement was observed, which is important for interpreting results. It stops short of describing return structure or any rate/coverage limits.

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 terse sentences, front-loaded with the core action, with the interpretive caveat second. No filler or restatement of the name or title.

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 single-parameter read tool with no output schema, the description is nearly complete: it identifies the resource, notes its public nature, and closes a key data-interpretation gap. It does not sketch what fields the profile returns, but nothing essential to invoking it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with a single required parameter (country_code) already documented with its format and pattern. The description adds no syntax, format, or constraint detail beyond the schema, so the baseline of 3 applies.

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: 'Read one public country profile.' This clearly distinguishes it as single-country retrieval against the aggregate/incident-oriented siblings (incident_stats, measurement_summary), though it never names those siblings explicitly. Purpose is clear but not differentiated by direct reference.

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 explicit when-to-use or when-not-to-use guidance, and no alternative tool is named. The phrase 'one public country profile' weakly implies single-record retrieval versus the aggregate siblings, but the agent must infer that routing decision without help.

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

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

Annotations already establish this as a safe, read-only, open-world read, so the safety profile is covered. The description adds real behavioral context beyond that: the record is public (no auth implied) and the source labels are attribution rather than independent corroboration, which is a meaningful data-reliability caveat. It still omits not-found/error behavior and rate limits.

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 tight sentences: the first front-loads the action, scope, and return contents; the second delivers a non-obvious interpretive warning. Nothing is redundant or padded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description compensates by listing the fields the record contains, and the annotations cover the safety profile. It is nearly complete for a simple single-record lookup, missing only failure/error behavior for an unknown or malformed ID.

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 is a single required parameter at 100% schema coverage, and the schema itself supplies the accepted formats (IR-2026-0253 or hex hash) plus a validation pattern. The description only restates 'published ID' and adds no format or edge-case detail beyond the schema, so the baseline of 3 applies.

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?

States a specific verb and resource ('Read one public Voidly incident record by published ID') and enumerates the returned content (status, incident dates, source labels, measurement count). This clearly separates it from siblings like voidly_incident_stats and voidly_measurement_summary, which aggregate rather than fetch a single record.

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 by the 'by published ID' framing — call it when you already have a specific incident ID — but there is no explicit when-to-use or when-not-to-use guidance, and no sibling is named as an alternative. An agent must infer the selection rule from the description's scoping 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 cover the safety profile (readOnlyHint=true, destructiveHint=false, openWorldHint=true), so the bar is lower. The description adds a genuinely useful interpretive constraint (counts are not proof of an event, no freshness guarantee), but says nothing about return shape, granularity, or data cadence.

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 short sentences with no waste; the core action is front-loaded and the caveat follows as a qualifier. Every word 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?

With zero parameters, no nested objects, and no output schema, the description covers what an agent needs to call it correctly. It could be more complete by routing to the sibling tools for detail or freshness, but nothing essential is missing me.

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 takes zero parameters and the schema is empty, so there is nothing for parameter semantics to add or omit. Baseline 4 applies.

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?

States a specific verb and resource ("Read aggregate public incident counts") and the word "aggregate" implicitly contrasts with the detail-oriented sibling voidly_incident_detail. However, it never names an alternative, so the distinction must be inferred from sibling names rather than the description itself.

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 explicit when-to-use statement or named alternative, but the caveat that counts alone do not establish a censorship event or measurement freshness implicitly nudges the agent toward measurement_summary for freshness questions. 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 declare readOnlyHint=true, openWorldHint=true and destructiveHint=false, so the safety profile is covered. The description adds genuine behavioral context beyond them: returned definitions and dates bound the measured scope, and unmeasured domains yield no accessibility finding. It still says nothing about the shape or size of the aggregate result.

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 tight sentences with the core action front-loaded and no filler. The second sentence is denser and slightly telegraphic ('definitions and dates delimit the measured scope') but it earns its place by adding scope semantics.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description should carry more of the return-value burden for an aggregate report. It hints at scope-bounding and null-finding behavior for unmeasured domains, which helps, but leaves the actual contents, granularity and response shape unstated.

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 takes zero parameters (empty schema, 100% coverage), so there is nothing for the description to disambiguate; baseline 4 applies. No parameter-level claims are made or 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 states a specific verb ('Read') and resource ('aggregate public measurement summary and coverage'), which is clear. It distinguishes itself implicitly from siblings like voidly_incident_detail and voidly_incident_stats by being the aggregate summary, but never names or contrasts those alternatives explicitly.

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 through the word 'aggregate' and the sibling set (country/incident detail and stats), suggesting this is the high-level rollup. There is no explicit 'use this when...' or 'for per-incident breakdown use X instead' guidance, leaving the agent to infer the routing.

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