list_organizationsList the publishing organizations on HDX (CKAN organization_list) — UN agencies and NGOs such as OCHA, UNHCR, WFP, IDMC, ACAPS. Use an org "name" as fq="organization:" in search_datasets.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max organizations, 1-1000 (default 100). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description adds context beyond annotations by specifying the tool returns UN agencies and NGOs and is CKAN's organization_list, which helps set expectations.
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 with no unnecessary words. The first sentence sets the purpose, and the second adds a practical usage hint. Front-loaded and efficient.
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 tool with one parameter and no output schema, the description is complete. It explains what the tool does, provides examples, and ties to a sibling workflow. Annotations are rich, so no further context needed.
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?
The schema description coverage is 100%, so the input schema fully describes the limit parameter. The description adds no additional parameter details, so baseline score of 3 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?
The description clearly states the tool lists publishing organizations on HDX, specifying it's CKAN's organization_list and giving concrete examples of organizations. This distinguishes it from sibling tools like search_datasets.
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 guidance on using the output (org name) in search_datasets, hinting at a common workflow. However, it does not explicitly state when to use this tool versus alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools have overlapping purposes (e.g., three variants of ask_pipeworx, several polymarket tools, and multiple discovery/entity tools). Despite detailed descriptions, the similiar functionalities create confusion for an agent selecting among them.
Tool names are consistently in snake_case but the verb/noun pattern is mixed: some start with verbs (ask_, list_, remember_), others with nouns (entity_profile, polymarket_edges). This inconsistency reduces predictability.
35 tools is high for a single server, especially when the scope spans two disparate domains (HDX humanitarian data and Pipeworx data platform). Many tools could be logically split into separate, more focused servers.
The tool set covers a wide range of functionality (data retrieval, comparison, monitoring, memory) but has notable gaps: no direct data download tool for HDX resources, no account management, and no exploration of Pipeworx packs beyond discover_tools.