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Pasal.id — Indonesian Law

Get Law Context

get_law_context
Read-onlyIdempotent

WHEN a law is known, get compact status, structure outline, or relationships before reading text. Budget: summary <= ~3KB, outline <= 15KB, relationship groups capped at 20 each.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lawYesCanonical law_id or citation string accepted by resolve_law, e.g. 16 or 'UU 27 tahun 2022'.
detailNoOne of summary, outline, relationships.summary

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

With readOnly, idempotent, and non-destructive annotations already covering the safety profile, the description adds concrete output-size budgets (summary <= ~3KB, outline <= 15KB, relationship groups capped at 20 each). Those limits help an agent manage context, though the description does not describe what the returned status or relationship groups contain.

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?

Two tightly written sentences, front-loaded with the when-condition and followed by the budget constraint. Every clause carries information without repetition or filler.

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

Completeness5/5

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

An output schema exists, so return-value structure need not be covered. The description supplies the trigger condition, the distinction from reading full text, the three detail modes, and concrete size limits; an agent has enough to invoke it correctly.

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

Parameters4/5

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

Schema coverage is 100%, so the schema already documents both parameters and the law format. The description goes further by attaching size expectations to each detail mode (summary, outline, relationships), giving the detail parameter practical semantic weight beyond the schema's list of allowed values.

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?

States a specific verb (get) and resource (law context), enumerating the three outputs: compact status, structure outline, or relationships. It also explicitly distinguishes from read_law by saying 'before reading text', so an agent can route without opening the sibling schema.

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?

The leading 'WHEN a law is known' gives a clear trigger condition, and 'before reading text' implies this is a precursor to read_law. It does not explicitly state what to do when the law is unknown (resolve_law) or name read_law as the alternative, leaving a small inference gap.

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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