DaedalMap CIA World Factbook

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

Description adds context beyond the readOnlyHint annotation by describing the tool as 'Free discovery' and specifying the source (DaedalMap), though it does not disclose additional behavioral details.

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?

Single sentence efficiently conveys purpose and scope with zero 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 no parameters and no output schema, description fully covers the tool's behavior: returns a list of available data packs.

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; description adds no parameter info, but baseline for zero-param tools is 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?

Description clearly states the tool returns the list of live agent-ready data packs available on DaedalMap, distinguishing it from siblings like get_pack (retrieving a specific pack) and query_dataset (querying within a pack).

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 when-to-use or alternatives, but context implies it's a discovery tool to be used before accessing specific packs or datasets.

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, and the description adds behavioral context (free discovery, returns specific information). No contradictions. The description does not disclose any negative behaviors, but none are expected for a read-only metadata tool.

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

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

Two sentences with no wasted words. Front-loaded with 'Free discovery.' followed by a clear list of return contents and usage advice. 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?

Given the simple one-parameter, read-only nature, the description fully covers purpose, usage guidance, and return content. No output schema exists, but the description lists what is returned, making it complete for an agent to understand and invoke correctly.

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

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

Schema coverage is 100% with a detailed parameter description including examples. The description adds minimal extra meaning beyond the schema (e.g., 'one pack'), so 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 returns detailed metadata, coverage, freshness, guidance, and first-query examples for a specific pack. It distinguishes itself from siblings (get_catalog lists all packs, query_dataset queries data).

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?

Explicitly says 'Call this before querying a new pack' and describes what information it provides. Siblings are implied but not explicitly contrasted; however, context from sibling names combined with description is clear.

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 readOnlyHint annotation already signals safety, and the description adds behavioral detail without contradicting it. It transparently enumerates what the help response includes: refusals, access limits, provenance fields, recommended next calls, and the interaction contract. It does not mention its own operational limits, but the read-only nature lowers the burden.

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 dense but efficiently structured: first sentence defines the core purpose, second lists the returned contents, third gives a direct usage pointer. It is not overly long for the rich information it conveys, though the second sentence is a long list that could arguably be split for readability.

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 one-parameter, read-only help tool with no output schema, the description is thorough. It spells out the output categories, the prerequisite tools/list discovery step, and the recommended invocation timing. The agent gets enough context to understand what the tool returns and how to call it successfully.

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 provides 100% coverage for tool_name, including the instruction 'Exact tool name from tools/list.' The description reinforces this by saying to discover names via tools/list, but it adds no new parameter syntax or format details. With full schema coverage, 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 states a specific verb+resource: 'get tool help' / 'guidance for one tool visible on this MCP facade.' It clearly differentiates from siblings like get_catalog and query_dataset by focusing on meta-guidance rather than data retrieval. The list of returned content (when to use, refusals, example, limits) makes the function unmistakable.

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 explicit usage context: 'Use tools/list to discover names, then call this before an unfamiliar tool.' This is a clear when-to-use directive. It doesn't explicitly mention when-not-to-use or compare with sibling tools, but the workflow is unambiguous and actionable.

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?

Beyond the readOnlyHint annotation, the description adds valuable behavioral context by distinguishing free vs. paid packs and mentioning the x402 Base USDC cost. It also references a specific API contract, which gives agents a pointer for expected behavior, though it does not disclose response format or pagination.

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

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

The description is a single, well-structured sentence with a front-loaded purpose followed by organized free/paid pack lists. It is dense but not verbose, and every piece of information (packs, cost, contract) is useful.

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 8 optional parameters, no output schema, and no enums, the description should provide more guidance on how to construct a query and what to expect in return. It only covers high-level purpose and pack lists, leaving out default limit behavior, response shape, and how filters/metrics interact, making it incomplete for a tool of this 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 coverage is 100%, so all parameters have descriptions. The tool description adds value by listing valid pack IDs and their free/paid status, complementing the schema's pack_id examples, but it does not enrich the meaning of sort, filters, metrics, or other parameters beyond what the schema already 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?

The description clearly states the tool's function as a 'Generic structured query for direct source_id or pack_id access' and references a specific API contract. It distinguishes itself from siblings by focusing on data access rather than catalog browsing, though it does not explicitly contrast with get_catalog/get_pack.

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 by listing free and paid packs and noting direct source_id or pack_id access, but it does not provide explicit when-to-use/when-not-to-use guidance relative to sibling tools like get_catalog or get_pack. The context is clear enough for a basic query scenario.

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