nyc-charter-laws-rules

get_section

Retrieve a specific NYC Charter, Administrative Code, or Rules section by citation. Pass corpus to disambiguate when citations match multiple documents.

Instructions

Retrieve a specific section by its citation (e.g. '§ 259', 'Section 259', '11-602.1', 'Chapter 11'). Input is normalized (with or without '§', any case). Pass 'corpus' to disambiguate when the same citation exists in multiple documents (e.g. charter 'Chapter 3' vs a rules chapter); if multiple sections still match, a disambiguation list is returned. For informational purposes only. Not legal advice. Verify against official sources at codelibrary.amlegal.com before relying on any result.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "citation": "<citation>"
    },
    "name": "get_section"
  }
}

Input Schema

Name	Required	Description	Default
`corpus`	No	Which document to look in (default: all three)
`citation`	Yes	Section citation or heading

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.4.4Nov 9, 2026

TDQS

A4.1/5.0

Behavior4/5

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

No annotations exist, so the description carries the full burden: it discloses the disambiguation-list return behavior and adds a 'for informational purposes / not legal advice' caveat. It stops short of describing pagination or what a successful match looks like.

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?

Core retrieval and disambiguation guidance is front-loaded and tight; the trailing legal disclaimer is boilerplate but short.

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?

For a two-parameter read tool with no annotations or output schema, the description covers normalization, ambiguity handling, and disambiguation responses. Return shape of a single match is left implicit.

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%, so both parameters are already documented, and description only restates normalization behavior for 'citation' and the disambiguation purpose of 'corpus'. Baseline 3 applies.

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 and resource ('Retrieve a specific section by its citation') and gives concrete citation examples, making it clearly distinct from siblings like search and list_titles.

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?

Explains normalization and the 'corpus' disambiguation use case with a concrete example (charter 'Chapter 3' vs a rules chapter). Doesn't explicitly contrast with 'search' for partial or fuzzy lookups, so not a full 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server