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

Discloses the returned fields (service_name, service_version, spec_version) and the purpose of each. No annotations exist, but the description fully covers behavior and side effects (none).

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?

Succinct with a clear structure: first line states purpose, second explains usage context, third lists return fields. Every sentence adds value, no redundancy.

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?

Completely describes the tool's function, usage, and output. With no parameters and an output schema (implied), no additional information is needed.

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?

No parameters exist, and schema coverage is 100%, so baseline is 3. The description adds value by detailing the return fields and their significance, justifying a 4.

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?

Explicitly states it retrieves version information for the qrz-mcp service and the upstream QRZ API. Clearly distinguishes from sibling tools (data lookup, logbook operations) by focusing on version alignment.

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?

Provides explicit guidance: use to confirm fleet alignment and detect drift across MCP deployments. Implicitly indicates not for data retrieval, differentiating from sibling 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?

With no annotations, the description discloses key behaviors: returns .adi file content, transparently paginates, and is rate-limited. This informs the agent about how the tool operates and potential constraints. Lacks mention of side effects or auth requirements, but these are covered by the required persona parameter.

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 sentences: first states action and output format, second explains usage, third discloses pagination and rate limits. Every sentence adds value, no repetition. Front-loaded with the core 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?

The description covers output format, pagination, and rate limiting. It does not address error conditions or the role of the 'persona' parameter, but the output schema exists and required parameter is clear. For a relatively straightforward download tool, this is mostly 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 100%, so the input schema already documents parameters. The tool description adds no extra parameter meaning beyond what is in the schema. For example, 'band' and 'mode' are explained in schema, and description does not clarify default behavior or interaction between filters.

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 downloads the complete QRZ logbook as raw ADIF text, using specific verbs and resource. It distinguishes from siblings by emphasizing 'complete' and 'raw ADIF', though no explicit comparison is given.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like qrz_logbook_fetch or qrz_logbook_status. The description does not mention use cases, prerequisites, or exclusions, leaving the agent to infer from the name 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?

No annotations are provided, so the description bears full responsibility. It only states the purpose without disclosing behavioral traits such as error handling, result format, or whether the operation is safe (e.g., read-only).

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, front-loaded sentence with no wasted words, efficiently conveying the tool's core function.

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 and presence of an output schema, the description is minimally adequate but lacks context on how it fits with sibling tools, error cases, or result interpretation.

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% with clear parameter descriptions. The tool description adds no additional meaning beyond what the schema already provides, so 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?

Description uses specific verb 'Resolve' and resource 'DXCC entity', clearly stating the tool's function. It distinguishes from sibling tools like qrz_lookup and others by focusing on DXCC entity resolution.

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 DXCC entity lookup but provides no explicit guidance on when to use this tool versus alternatives like qrz_lookup, nor any conditions or exclusions.

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?

No annotations are provided, so the description must disclose behavioral traits. It mentions pagination behavior ('Transparently paginates to collect up to `limit` records'), which is helpful. However, it does not disclose read-only nature, authentication requirements beyond requiring 'persona', rate limits, or error handling. For a query tool, more transparency about side effects and constraints would be beneficial.

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, front-loaded with purpose and immediately followed by a key behavioral detail (pagination). Every word adds value; no fluff or repetition. It is a model of conciseness.

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 9 parameters (1 required) and an output schema. The description covers the core purpose and pagination behavior, but lacks explanation of the required 'persona' parameter (what is a persona?), does not mention output format or fields, and provides no examples or use-case context. For a complex filtering tool, the description leaves gaps in completeness.

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 parameters are already documented in the schema. The description adds context about the 'limit' parameter by explaining pagination behavior ('Transparently paginates...'). For other parameters, the description adds no additional meaning beyond the schema. Baseline 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 queries QSOs from a QRZ logbook with optional filters. The verb 'Query' and resource 'QSOs from a QRZ logbook' are specific. It distinguishes itself from siblings like qrz_lookup (individual call lookup) and qrz_download (ADIF download) by focusing on logbook QSO retrieval.

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 mentions transparent pagination up to a limit, which gives some usage context. However, it does not explicitly state when to use this tool versus alternatives (e.g., qrz_lookup for single callsign queries, qrz_download for full log downloads). No when-not-to-use guidance or alternative suggestions are 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?

No annotations are provided, so the description must disclose behavioral traits. It only indicates a read operation ('Get') but omits details like authentication, rate limits, or potential errors. The output schema exists but is not mentioned in the description.

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, compact sentence that front-loads the core action and outputs. Every word serves a purpose with no redundancy.

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 tool with one parameter and an output schema, the description covers the essential functionality. It implicitly requires a configured persona (via schema) but does not elaborate on setup. The output schema compensates for missing return value details.

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%, and the schema describes the 'persona' parameter sufficiently. The description does not add additional meaning beyond the schema, so it meets the baseline for a covered 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 clearly states the tool retrieves QRZ logbook statistics, listing specific data types (QSO count, DXCC total, date range). This distinguishes it from siblings like qrz_logbook_fetch (which likely fetches individual entries) and qrz_dxcc (DXCC info).

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 aggregate statistics but does not explicitly state when to choose this over alternatives (e.g., qrz_logbook_fetch for raw entries). No context on prerequisites or exclusions 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?

The description lists the fields returned and implies a read operation, but it does not explicitly state that the tool is read-only or non-destructive. Without annotations, the description should confirm idempotency. The subscription note hints at partial behavior, but it's unclear what happens with a missing subscription.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences: one for the core function and one for the subscription requirement. No superfluous content. The key information is front-loaded.

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

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

The description adequately covers the tool's purpose and the subscription dependency. The presence of an output schema reduces the need to explain return values. Missing minor details like case sensitivity or error handling, but overall sufficient for a lookup tool.

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% (both parameters have descriptions), so the baseline is 3. The description does not add deeper meaning to the parameters; it only restates what the schema provides.

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?

Description clearly states the tool looks up a callsign on QRZ.com and enumerates the returned data (name, grid, DXCC, etc.). The verb 'look up' and resource 'callsign' are specific, and the tool is distinct from siblings like qrz_download or qrz_dxcc.

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 mentions the prerequisite of a QRZ XML Subscription for full fields, which provides some usage context. However, it does not explicitly state when to use this tool versus alternatives (e.g., qrz_dxcc for DXCC info) or when not to use it.

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