Geojson
geojsonRead-onlyIdempotent
Current alerts as GeoJSON.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| event_type | No | ||
| alert_level | No |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Gdacs
TDQS
C2.6/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds minimal context ('current alerts') but does not disclose pagination, filtering behavior, data freshness, or response structure nuances beyond what the output schema provides.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only five words, which is concise but under-specified. It is more of a fragment than a complete sentence and omits essential usage context, making it insufficient rather than efficiently concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having optional parameters, an output schema, and good annotations, the description fails to explain the meaning of 'current alerts', how the filters work, or when this tool is appropriate. The minimal context leaves critical gaps for an agent to decide when to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the tool description does not mention the parameters 'event_type' or 'alert_level'. The agent receives no information about valid values, defaults, or how these parameters filter the alerts, making it impossible to use them correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Current alerts as GeoJSON' clearly indicates the tool returns current alerts in GeoJSON format, differentiating it from similar tools like 'recent_alerts' or 'events' by format. However, it lacks an explicit verb such as 'Get' or 'List', making it a noun phrase rather than a direct command.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'recent_alerts' or 'events'. There is no mention of scenarios, exclusions, or criteria for preferring GeoJSON output.
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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TDQS
A3.5/5.0
Disambiguation4/5
Most tools have clear, distinct purposes, but the three ask_pipeworx variants (especially ask_pipeworx_beta, identical to ask_pipeworx) and the six Polymarket tools overlap conceptually and could cause misselection. Detailed descriptions largely compensate, but the boundaries between some meta-tools (e.g., ask_pipeworx vs deep_research vs bet_research) require careful reading.
Naming Consistency3/5
All names are snake_case, but conventions are mixed: verb-first (ask_pipeworx, compare_entities, discover_tools), noun-first compounds (entity_profile, polymarket_arbitrage), and single-word nouns (event, events, rss). The pattern is predictable for common actions but inconsistent across the set, making it harder to guess names for related tasks.
Tool Count2/5
At 35 tools, the count is heavy and the server named 'Gdacs' includes many unrelated tools (Polymarket, npm scanning, AI visibility), indicating scope creep. Several tools could be consolidated (e.g., the ask_pipeworx family and multiple pattern-market scanners), and the breadth dilutes the disaster-alerting focus implied by the server name.
Completeness4/5
The surface covers core workflows: data querying (ask/research/validate), entity profiling, prediction-market analysis (arbitrage/edges/fill risk), and subscription management (create/list/cancel). Minor gaps exist, such as no direct fetch tool for a specific Pipeworx pack and limited GDACS event management (only read operations), but these are workable with the provided meta-tools.