DaedalMap CIA World Factbook
Server Details
CIA World Factbook country indicators: infrastructure, energy, demographics, economy, 2002-2026.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- xyver/daedal-map
- GitHub Stars
- 0
- Server Listing
- daedal-map
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 3.8/5 across 3 of 3 tools scored.
Each tool serves a distinct purpose: get_catalog lists available data packs, get_pack retrieves metadata for a specific pack, and query_dataset executes a query; no overlap.
Tools use a verb_noun pattern (get_catalog, get_pack, query_dataset). The use of 'get' for two tools and 'query' for the third is a minor inconsistency but the pattern remains clear.
With 3 tools, the server is lean but well-scoped for the domain of data discovery and query. It’s slightly minimal but each tool is necessary and well-defined.
The tool surface covers the full workflow: discover available packs, inspect a pack's metadata, and query a dataset. No obvious gaps for a read-only data access server.
Available Tools
3 toolsget_catalogGet CatalogARead-onlyInspect
Free discovery. Returns the list of live agent-ready data packs available on DaedalMap.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
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.
get_packGet PackARead-onlyInspect
Free discovery. Returns detailed metadata, coverage, freshness, preferred canonical tool guidance, and first-query examples for one pack. Call this before querying a new pack so you can see time shape, coverage limits, and the paste-ready first query.
| Name | Required | Description | Default |
|---|---|---|---|
| pack_id | Yes | Pack identifier such as 'currency', 'earthquakes', 'floods', 'hurricanes', 'tornadoes', 'tsunamis', 'un_sdg', 'volcanoes', 'world_factbook', or 'worldpop'. |
Tool Definition Quality
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.
query_datasetQuery DatasetARead-onlyInspect
Generic structured query for direct source_id or pack_id access using the same contract as POST /api/v1/query/dataset. Free packs: boundaries, currency, distributed_manufacturing, floods, geography, nri, owid_co2, reverse-geocoding, un_sdg, un_wpp, volcanoes, world_bank_wdi. Paid packs: earthquakes, hurricanes, tornadoes, tsunamis, wildfires, world_factbook, worldpop (x402 Base USDC).
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | Optional sort instructions for row-returning queries. | |
| limit | No | Maximum number of rows to return for the requested source or pack. | |
| output | No | Optional output controls such as response format hints. | |
| filters | No | Structured filters including time, region_ids, and compare clauses. | |
| metrics | No | Metric ids to return. Use event_count for aggregate counts when supported. | |
| pack_id | No | Pack identifier such as 'currency', 'earthquakes', 'floods', 'hurricanes', 'tornadoes', 'tsunamis', 'un_sdg', 'volcanoes', 'world_factbook', or 'worldpop'. | |
| source_id | No | Concrete source id such as 'earthquakes_events', 'volcanoes_events', 'hurricanes_events', or 'un_sdg/01'. | |
| request_id | No | Optional caller-supplied request id for tracing and idempotency. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds context about paid packs and the API contract ('same contract as POST /api/v1/query/dataset'), which provides useful behavioral insight beyond the annotation.
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 paragraph that starts with the primary purpose and then lists packs. It is relatively concise but could be more structured (e.g., bullet points for packs).
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 8 parameters with nested objects and no output schema, the description does not explain return values or query structure. The schema descriptions help, but additional context on usage patterns would improve 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 each parameter's purpose is already documented. The tool description does not add any additional meaning beyond what the schema provides, thus baseline score.
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', and lists specific free and paid packs, distinguishing it from sibling tools like 'get_catalog' (likely for listing packs) and 'get_pack' (for pack metadata).
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 explicit guidance on when to use this tool versus alternatives (get_catalog, get_pack). It does not mention prerequisites, context, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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