ny_lawsList the New York law corpora — Penal Law is PEN, Labor Law is LAB, Vehicle and Traffic is VAT, and so on — optionally filtered by subject. Use when you know the subject but not the law id, before calling ny_law_section.
| Name | Required | Description | Default |
|---|---|---|---|
| search | No | Optional filter on the law name, e.g. "penal", "labor", "insurance". |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful context about the tool being a precursor to ny_law_section and the filtering capability, which goes beyond the structured metadata. No contradictions with 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?
The description is two sentences with no filler. The core action and examples are front-loaded, and the usage guidance and sibling reference are concise. Every word contributes to understanding.
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 optional parameter and no output schema, the description covers the purpose, usage condition, and relationship to the sibling tool. The annotations handle the safety profile, so nothing essential is missing for an agent to call this correctly.
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 already provides full documentation for the single optional parameter (search) with examples like 'penal', 'labor', and 'insurance'. The description mentions 'filtered by subject' which aligns with the schema but doesn't add new meaning beyond what the schema already conveys. Since schema coverage is 100%, a 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 verb and resource ('List the New York law corpora') and provides concrete examples of law abbreviations (PEN, LAB, VAT), which helps distinguish it from the sibling ny_law_section. The purpose is unambiguous and not a tautology.
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 explicitly tells the agent when to use this tool ('when you know the subject but not the law id') and names the alternative (ny_law_section) and the order of operations ('before calling ny_law_section'). This is precise and leaves no ambiguity.
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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