DaedalMap Flood Events
Server Details
Global flood events and extent 1985-present from the Dartmouth Flood Observatory and GFD.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4/5 across 3 of 3 tools scored.
Each tool serves a distinct purpose: listing available packs, retrieving pack metadata, and running queries. No overlap or ambiguity.
All tools use consistent verb_noun snake_case naming (get_catalog, get_pack, query_dataset), following a predictable pattern.
With 3 tools, the server is minimal but sufficient for its core workflow of discovery, metadata, and query. Slightly under typical range but justified by focused scope.
The tool surface covers the essential operations for a read-only data query service. Minor gaps exist (e.g., no listing of datasets within a pack), but the primary use case is addressed.
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, making safety clear. Description adds useful context that the list is 'live agent-ready' and from DaedalMap, which goes beyond 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?
Two short sentences with minimal redundancy. 'Free discovery' is slightly redundant with the second sentence, but overall concise and 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?
For a simple list retrieval with no parameters and no output schema, the description adequately states what is returned and from where. Some missing details on data pack format, but acceptable given tool simplicity.
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 description doesn't need to add parameter details. Baseline of 4 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 clearly states it returns a list of data packs, with specific verb 'Returns' and resource 'list of live agent-ready data packs'. However, it does not explicitly differentiate from siblings like get_pack or query_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?
Only implies usage via 'Free discovery' but provides no explicit guidance on when to use this tool vs alternatives like get_pack or query_dataset. Missing context for proper selection.
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 declare readOnlyHint=true, and the description does not contradict this. It adds behavioral context like 'Free discovery' and specifies the data returned, 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?
Two sentences, no filler. Key purpose ('Free discovery') is first, then details, then usage guidance. Every sentence adds value.
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 output schema, the description explains what is returned (metadata, coverage, freshness, guidance, examples) and why to use it. It could mention linking to query_dataset but is adequate for a simple 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% with a clear description of pack_id including examples. The description adds no additional parameter semantics beyond stating it identifies the pack.
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 'Returns detailed metadata, coverage, freshness, preferred canonical tool guidance, and first-query examples for one pack.' It distinguishes itself from siblings (get_catalog lists packs, query_dataset queries data) by focusing on single-pack discovery.
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 instructs 'Call this before querying a new pack' and explains benefits: 'see time shape, coverage limits, and the paste-ready first query.' Does not mention when not to use or alternatives, but the context is sufficient.
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: 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?
The description adds value beyond the readOnlyHint annotation by disclosing that some packs are free and others require payment (up to $402 USDC). This is a key behavioral trait not captured in annotations. The mention of the same contract as POST /api/v1/query/dataset is consistent with read-only operations. 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?
The description is extremely concise: two sentences that front-load the core purpose and immediately list supported packs. Every word is functional, with no redundancy or filler. Ideal for quick scanning by an AI agent.
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 the complexity (8 parameters, nested objects, no output schema), the description only covers high-level access patterns and pricing. It does not explain the return format, how to structure queries (filters, metrics), or what 'same contract' implies for the API. Given the absence of an output schema, more context on expected results would be beneficial.
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 100% schema coverage, all parameters have descriptions, so the description's role is reduced. The description does not add new parameter-specific details beyond listing pack_id examples, which partially overlap with schema descriptions. It meets the baseline 3 but does not significantly augment parameter understanding.
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: 'Generic structured query for direct source_id or pack_id access'. It also lists specific pack types, making it distinct from sibling tools like get_catalog (for browsing packs) and get_pack (for pack details). The verb 'query' and resource 'dataset' are specific and well-defined.
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 free vs paid packs, implying cost considerations, but lacks explicit guidance on when to use this tool versus alternatives. It does not state prerequisites, exclusions, or conditions that would help an agent decide between query_dataset and get_catalog/get_pack. The guidance is implied but not directive.
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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