lu_dp_get_decision

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description implies a read operation (Get) but doesn't state whether this is non-destructive/read-only, whether it has permission requirements, what happens for invalid/malformed reference numbers, or what the response shape is. For a retrieval tool this is a notable gap.

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 a single, concise sentence with zero wasted words. Example formats are embedded inline for immediate usefulness. No redundant information or filler.

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?

This is a simple retrieval tool with a single well-documented parameter and output schema absent. The description sufficiently covers what the tool does and how to identify target decisions. It could note error behavior or return format, but for a basic single-param fetcher, the information provided is reasonably complete.

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%, with the single 'reference' parameter well-documented in the schema. The description adds value by providing example formats for the reference parameter beyond what the schema states, giving the agent concrete syntax patterns to use. However, it largely overlaps with schema content, so it doesn't exceed the baseline 3 by much.

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 clearly states the verb (Get), resource (CNPD decision), and specific identifying mechanism (reference number). It also provides concrete example formats ('CNPD-2021-001', 'CNPD-DEC-2023-001') that distinguish it from sibling tools like lu_dp_search_decisions (search vs. direct fetch).

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?

The description implicitly communicates when to use this tool — when you have a specific reference number and want a particular decision, as opposed to searching for decisions. It does not explicitly state 'use search_decisions for discovery, then this for retrieval', which would earn a 5, but the reference-based targeting is clear context.

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