ag_data_record_link

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

With no annotations, the description carries the transparency burden and does well: it discloses determinism, fixture verification, guest access, rate limiting, the need for an API key for member budget, and that a Guild-signed provenance envelope is returned.

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 and organized, but it repeats 'Deterministic' and the return/provenance information multiple times, adding redundancy without much new information.

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?

The description includes the algorithm, matching behavior, output shape, provenance envelope, determinism, rate limiting, and auth expectations. It is sufficient for a tool of this complexity, though it omits explicit edge-case behavior such as no-match results.

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?

The inline JSON schema supplies types and constraints, and the prose explains key fields and threshold as a similarity cutoff, but individual payload parameters are not described in detail, leaving some semantics to inference.

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 a specific action ('Fuzzy-match records across two lists by a key field') and distinguishes this from related tools by focusing on two-list record linkage rather than deduplication or other operations.

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?

Use cases are implied through phrases like 'Entity-resolution lite' and the explicit two-list matching behavior, but no alternatives are named and there is no direct when-to-use vs. when-not-to-use guidance.

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