DaedalMap UN Sustainable Development Goals
Server Details
UN Sustainable Development Goals indicators across all 17 goals, from the UN SDG Global Database.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- xyver/daedal-map
- GitHub Stars
- 0
- Server Listing
- daedal-map
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Tool Definition Quality
Average 4/5 across 3 of 3 tools scored. Lowest: 3.4/5.
Each tool has a clearly distinct purpose: get_catalog lists available data packs, get_pack retrieves metadata for a specific pack, and query_dataset executes a query against a dataset. There is no overlap in functionality.
Tools follow a verb_noun pattern, but there is a minor inconsistency: two use 'get_' and one uses 'query_'. While understandable, a more uniform verb choice would improve predictability.
Three tools is a minimal but reasonable set for a data catalog server focused on discovery and query. It feels slightly under-scoped for a system with multiple data packs, but it covers the essential operations without excess.
The tools cover the basic workflow of discovering packs and querying datasets. However, there are notable gaps such as filtering or searching packs, listing available datasets within a pack, or any update/delete operations. This limits the agent's ability to handle more nuanced tasks.
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 provide readOnlyHint=true, indicating a safe read operation. The description adds value by specifying 'Free discovery' and 'live agent-ready data packs,' which gives context about cost and readiness. It doesn't contradict annotations, and while it could mention more behavioral traits like response format, it compensates well given the annotations.
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, efficient sentence that front-loads key information ('Free discovery') and states the core action and resource. There is no wasted text, making it easy for an agent to parse quickly and understand the tool's essence.
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 is complete enough for an agent to use it correctly. It covers purpose and context, though it could benefit from slight elaboration on output or usage scenarios to reach a perfect score, but it's adequate for the 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?
With 0 parameters and 100% schema coverage, the baseline is high. The description adds no parameter details, which is fine since there are none. It effectively communicates that no inputs are needed, aligning with the empty schema, so it meets expectations without redundancy.
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,' specifying the verb 'returns' and resource 'list of data packs.' It distinguishes from siblings like get_earthquake_events by focusing on catalog discovery rather than specific data types, though it could be more explicit about the distinction.
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 discovery of available data packs, which suggests it's for initial exploration or listing resources. However, it lacks explicit guidance on when to use this versus alternatives like get_pack (for specific packs) or query_dataset (for querying data), leaving some ambiguity for the agent.
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?
Annotations indicate readOnlyHint=true; description adds context about what is returned (metadata, coverage, freshness, etc.) and implies no side effects. 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?
Two concise sentences, front-loaded with 'Free discovery.' Every sentence adds value – purpose and usage guidance. No fluff.
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 tool without output schema, the description lists what the response contains (metadata, coverage, freshness, etc.), which is sufficient context for an agent.
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 covers the single parameter fully with examples. Description adds no extra parameter meaning beyond what schema provides, meeting baseline for 100% schema coverage.
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 metadata, coverage, freshness, tool guidance, and examples for one pack. It distinguishes from siblings like get_catalog (list all packs) and query_dataset (query).
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 advises calling this before querying a new pack to inspect time shape, coverage limits, and get a paste-ready first query. Provides clear when-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
query_datasetQuery DatasetBRead-onlyInspect
Generic structured query for direct source_id or pack_id access using the same contract as POST /api/v1/query/dataset. Free packs: currency, floods, un_sdg, volcanoes. Paid packs: earthquakes, hurricanes, tornadoes, tsunamis, 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, so the read-only nature is established. The description adds value by mentioning paid packs requiring USDC, which is behavioral context not in annotations. However, no details on response structure or limits beyond schema.
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: first defines purpose and contract, second lists packs. Efficient and front-loaded. No redundancy, but could include a brief usage note.
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?
Despite high schema coverage, the description lacks guidance on required vs optional parameters, mutual exclusivity of source_id/pack_id, pagination, or how to construct filters/metrics. No output schema leaves behavior ambiguous.
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 all parameters described. The description adds meaning by categorizing packs into free and paid, which is not in the schema's pack_id description. This helps understand parameter constraints.
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's a 'Generic structured query' for direct source_id or pack_id access, referencing the API contract. It lists free and paid packs, distinguishing from siblings get_catalog and get_pack which are for metadata, not 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?
The description implies usage via 'direct source_id or pack_id access' and lists pack types, but does not explicitly guide when to use this tool versus alternatives or mention any exclusions or prerequisites.
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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