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smridhiwho

open-india-law-mcp

by smridhiwho

search_regulations

Search provisions inside a single regulator's instruments (SEBI, RBI, etc.). Specify the regulator body and optional query; use list_catalog for available regulator slugs to target your search.

Instructions

Search one regulator's instruments at the provision level, e.g. body="SEBI" or body="RBI". Same query semantics as search_legislation -- the regulator files share the same provision schema. Use list_catalog() to see which regulator slugs are currently published.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes
limitNo
queryNo
in_force_onlyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description carries the behavioral disclosure burden. It adds useful context about provision-level granularity and shared schema semantics, but it does not disclose pagination, result ordering, whether only published instruments are returned, or other runtime behavior.

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

Conciseness5/5

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

Three tight sentences front-load the tool's purpose and example, then point to the relevant sibling for schema semantics and list_catalog for valid inputs. Every sentence earns its place with no redundant phrasing.

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?

The core invocation path is covered: required body parameter, example values, where to find valid slugs, and the relationship to search_legislation. Gaps remain around the optional parameters and behavior, but the output schema and self-explanatory param names reduce the risk of incorrect calls.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for all four parameters. It gives an example for 'body' but does not explain 'query', 'limit', or 'in_force_only'; the reference to 'same query semantics as search_legislation' is helpful only if the agent already knows that tool's parameter details.

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 states a specific verb and resource: 'Search one regulator's instruments at the provision level.' It also distinguishes itself from sibling search tools by emphasizing 'regulator' and by explicitly linking its query semantics to search_legislation while still framing it as a distinct corpus.

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

Usage Guidelines4/5

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

It tells the agent when to use this tool—for regulator instruments—and points to list_catalog() to discover valid body slugs. It does not explicitly say when not to use it versus search_legislation or search_judgments, but the regulator/provision framing makes the intended domain clear.

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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