nola_datasetsSearch the New Orleans open-data catalogue (data.nola.gov) for datasets by keyword. Returns dataset names, descriptions, and Socrata resource ids to use with nola_query.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max datasets (1-100, default 20). | |
| query | No | Keyword(s). | |
| offset | No | Offset for paging. | |
| _apiKey | No | Optional — your own Socrata app token for higher rate limits. Omit to use the keyless endpoint. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. Description adds context about the specific data source (data.nola.gov) and output fields, but does not disclose pagination behavior, rate limits, or authorization details beyond what 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with the core action. Every phrase adds value: target catalogue, action, return values, and linkage to related tool. 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 search tool with full annotations and schema, the description covers the essential purpose and output usage. Could benefit from a brief note on pagination (limit/offset) or that results are paginated, but not critical.
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?
Input schema covers all 4 parameters with full descriptions (100% coverage). Description adds no new semantic information about parameters, only reiterating 'by keyword' which aligns with the query param. Meets baseline for high 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?
Description clearly states it searches the New Orleans open-data catalogue by keyword, specifying the resource and action. It also mentions the return type (names, descriptions, resource ids) and ties to sibling nola_query, distinguishing its output.
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?
No guidance on when to use this tool versus siblings like nola_recent. Does not specify prerequisites or when not to use. Only implies usage chain with nola_query, insufficient for tool selection.
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.
Several tool boundaries blur: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all serve overlapping query/research entry points, and ask_pipeworx_beta is currently identical to ask_pipeworx by the server's own description. entity_profile, recent_changes, and compare_entities also cover overlapping company-investigation territory, forcing agents to parse long descriptions to avoid mis-selection.
Names are uniformly snake_case and mostly follow a predictable verb-object or domain-prefix pattern (ask_pipeworx_*, polymarket_*, nola_*, subscribe/unsubscribe). Minor deviations like nola_datasets, polymarket_edges, and ai_visibility_check are noun-first rather than verb-first, but the overall convention is still readable and coherent.
34 tools is well above the 15-25 heavy range and includes multiple near-duplicate query modes, four closely related Polymarket analysis tools, and memory/subscription utilities layered on top of the core data-access surface. While the server appears to be a broad data platform, the count is bloated for an agent to navigate efficiently.
The tool surface is remarkably broad: discovery, single-answer lookup, grounded verification, deep research, entity resolution, entity profiles, comparisons, claim validation, NOLA querying, prediction-market analytics, memory, subscriptions, and feedback are all covered with few obvious dead ends. The main gap is that the NOLA-specific surface is thin relative to the server name, though nola_query plus nola_datasets provides a flexible escape hatch.