get_lawRead a law by id. Short laws come whole. Long laws (100+ sections) return their front matter and a Contents list: then ask for one part, e.g. part: "section 86", "schedule 1", "regulation 3" or "part 2" (lists that part's sections).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Law id from search_laws, e.g. ukpga/1996/18 | |
| part | No | One section, regulation, article, schedule or part of a long law, e.g. "section 86" | |
| max_chars | No | Default 60000 |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already establish read-only and open-world behavior, while the description adds important non-obvious behavior: short laws are returned whole, but long laws return only front matter and a Contents list first. It still does not discuss truncation, errors, or rate limits, so it is strong but not complete.
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 front-loaded, concise, and well-structured: it states the core action, then explains the important short-law/long-law branching and follow-up part request with examples. Every sentence contributes useful operational detail.
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 three-parameter read tool with no output schema, the description covers the key return-shape nuance and the follow-up part workflow. It is nearly complete, though it could say more about max_chars behavior and what front matter includes.
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?
Schema coverage is 100%, so the baseline is 3, but the description adds real meaning to the part parameter by explaining that it is used after a long-law Contents response and by giving concrete part formats. It does not add meaning beyond the schema for max_chars.
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 gives a specific verb and resource: "Read a law by id," and it clarifies short-law versus long-law behavior. It does not explicitly name sibling tools like search_laws, so sibling differentiation is partly implicit rather than fully stated.
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?
It clearly explains when to supply a part: long laws return front matter and a Contents list, then the agent should request one section, schedule, regulation, or part. It gives useful examples but does not mention alternatives or when not to use this tool.
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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