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Get one sector’s AI-law cross-section

get_sector_detail
Read-onlyIdempotent

One sector’s cross-section: the free awareness OVERVIEW (name, inherent risk, enforcement bodies, federal penalty structure) PLUS the derived per-law obligations + penalties for that sector. The overview is open to every tier; the derived obligations/penalties are the salable interpreted layer (Pro+ for obligations) — under-tier callers get a one-item preview + upsell (meta.preview), never a blank wall. Every derived record is grounded in a real law + its primary source (no LLM). Use list_sectors for valid slugs. NOT legal advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sectorYesA sector slug (see list_sectors), e.g. healthcare, finance, hr-recruiting.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate safe read operation. Description adds context about tiered access, preview vs. full data, and grounding in real laws. No contradiction found.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Concise yet informative; every sentence adds value. Could be slightly improved by structuring the upsell part more compactly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no output schema, the description explains return structure (overview fields, derived obligations/penalties, preview for under-tier). Sufficient for a single-parameter tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and already explains the 'sector' parameter well (slug from list_sectors). Description merely repeats this guidance, adding marginal value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool returns a sector's cross-section including free overview and derived obligations/penalties. It uses specific language and distinguishes from sibling tools like list_sectors.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly instructs to use list_sectors for valid slugs, describes tier-based access and upsell behavior, and clarifies what different tiers receive.

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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