Check municipal, state, and federal regulatory rules, required permits, compliance deadlines, and grant requirements.
| Name | Required | Description | Default |
|---|---|---|---|
| topic | No | Topic or keyword (e.g. 'Short-term rentals', 'AI disclosure', 'Commercial composting') | |
| jurisdiction | No | Location or jurisdiction (e.g., 'San Francisco', 'California', 'Federal') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It names categories the tool 'checks' but does not disclose output format, coverage limitations, data source, recency, or whether results are summaries or raw documents. This is a meaningful transparency gap for a compliance tool.
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 compact sentence with no filler or repetition. It front-loads the action and then efficiently enumerates the tool's coverage areas, making every part informative.
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?
The description and schema cover what the tool does and its two parameters, but there is no output schema and no guidance on what a returned compliance check looks like or how the optional parameters should be combined. For a simple two-parameter tool this is adequate but leaves notable gaps.
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 description coverage is 100%, so both parameters are already documented in the input schema. The description adds general context about the domain but no additional parameter-level meaning beyond what the schema provides, so the baseline 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 a specific action ('Check') and a defined resource ('municipal, state, and federal regulatory rules, required permits, compliance deadlines, and grant requirements'). It is distinguishable from zoning-focused siblings by emphasizing broad regulatory scope plus permits, deadlines, and grants, though it does not explicitly name or contrast those siblings.
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 gives no guidance on when to choose this tool over siblings like refinery_custom_municipal_zoning_compliance or refinery_custom_real_estate_zoning. It implies regulatory compliance questions are in scope but provides no exclusions, prerequisites, or alternative routing.
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 tools form near-overlapping pairs: b2b_pricing_matrix vs custom_b2b_saas_pricing_matrix, dev_breaking_changes vs custom_dev_sdk_breaking_changes, and municipal/real-estate zoning vs regulatory_compliance. While individual descriptions differ, an agent would often have to guess which variant applies.
Names share a refinery_ prefix and use snake_case, making them mostly predictable and readable. The custom_ qualifier is used inconsistently—custom schema vs custom URL—and refinery_refine_custom_url/semantic_search break the otherwise noun-object pattern, but these are minor deviations.
13 tools is reasonable for a data-refinery platform covering multiple vertical schemas. The redundancy between base and custom_ variants and overlapping compliance tools makes it slightly heavier than necessary, but not excessive.
The surface covers refining arbitrary URLs, semantic search, and many domain-specific extraction schemas. Missing are database/schema management, document-level retrieval/update/delete, and clear parity between base and custom variants, so agents may hit dead ends when managing or verifying refined data.