DaedalMap CIA World Factbook

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

Annotations already declare readOnlyHint=true, so the agent knows this is a safe read operation. The description adds useful context about 'live agent-ready data packs' and 'Free discovery,' which clarifies the tool's scope and accessibility. However, it doesn't disclose behavioral traits like rate limits, authentication needs, or response format details beyond what annotations provide.

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 at just 9 words, front-loaded with the key action ('Returns the list...'). Every word earns its place by specifying the resource type, availability status ('live agent-ready'), and source ('on DaedalMap'). There's zero waste or 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?

Given the tool's simplicity (0 parameters, read-only, no output schema), the description provides adequate context about what it returns. It could be more complete by mentioning the return format (e.g., list structure) or any limitations, but for a basic discovery tool with good annotations, it's sufficiently informative without being verbose.

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 0 parameters and 100% schema description coverage, the schema fully documents the lack of inputs. The description appropriately doesn't add parameter information, as none are needed. This meets the baseline expectation for a parameterless tool, earning a 4 for not introducing unnecessary complexity.

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 purpose with 'Returns the list of live agent-ready data packs available on DaedalMap' - a specific verb ('Returns') and resource ('list of live agent-ready data packs'). It distinguishes from siblings by focusing on catalog discovery rather than specific data types like earthquakes or FX rates. However, it doesn't explicitly contrast with 'get_pack' which might retrieve individual packs.

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 context with 'Free discovery' and 'live agent-ready data packs,' suggesting this is for browsing available resources. However, it provides no explicit guidance on when to use this versus alternatives like 'query_dataset' for specific queries or 'get_pack' for individual pack details. The context is clear but lacks sibling differentiation.

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?

ReadOnlyHint annotation already declares safety. Description adds behavioral details: returns metadata, guidance, examples. 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?

Three concise sentences: what it returns, when to use, why. 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?

For a simple discovery tool with one parameter and read-only annotation, the description covers return content and usage. Could mention response format but not necessary.

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 enum values. Description clarifies it's for one pack, adding minimal value beyond 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 explicitly states it returns metadata, coverage, freshness, guidance, and examples for a single pack. It distinguishes from siblings by focusing on pack discovery before querying.

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 says 'Call this before querying a new pack' and explains the benefits (time shape, coverage limits, first query). It does not explicitly list alternatives but provides clear usage context.

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, so the description adds no contradiction. It mentions the API contract (POST /api/v1/query/dataset) and categorizes packs, but does not disclose additional behavioral traits like pagination or 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?

The description is two sentences: one defining the tool's purpose and API contract, and one listing pack categories. It is efficient and front-loaded, with no extraneous information.

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 complexity (8 parameters, nested objects, no output schema), the description is relatively brief. It references the API contract but lacks examples or guidance on the structure of filters, metrics, and output controls. Adequate but could be more informative for agent 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?

Schema coverage is 100% with parameter descriptions. The description adds value by categorizing pack_id values as free vs. paid (e.g., 'currency' is free, 'earthquakes' is paid), which is beyond the schema. This provides extra context for parameter selection.

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 is a 'generic structured query for direct source_id or pack_id access', which distinguishes it from sibling tools like get_catalog and get_pack that retrieve metadata. It specifies the verb (query) and the resource (dataset).

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 querying datasets by source_id or pack_id, and lists free vs. paid packs, hinting at cost considerations. However, it does not explicitly state when not to use this tool or provide alternatives to siblings.

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