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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so credit is for extra context: the list is not exhaustive because vendors can opt out, and it is not a ranking or recommendation despite paid plans. This is genuinely useful framing not present in structured fields.

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?

Front-loaded with the core purpose, then caveats, then the usage rule. The middle clause about haggl.ai running sales agents and paid plans is slightly verbose but earns its place by motivating the 'not a ranking' caveat.

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?

With an output schema present and annotations covering safety, the description need not explain return values or pagination. It covers inclusion criteria, completeness limits, and usage, leaving only minor gaps such as pagination over a potentially large vendor list.

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 tool takes zero parameters, so there is nothing for the description to clarify beyond the schema; baseline 4 applies. No parameter-related claims are made or needed.

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?

States a specific verb+resource (list vendors) and sharply scopes it: vendors that accept AI-agent price negotiations through haggl.ai, with the concrete inclusion condition (Shopify app installed or snippet detected). It does not explicitly distinguish itself from close siblings like haggl_search_catalog or haggl_search_discounts, so it stops short of a 5.

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?

Provides a clear trigger and an explicit exclusion: use it when the user asks for a discount or wants to negotiate, not for a purchase at the listed price. It does not name the alternative sibling to use in the purchase case, leaving that to inference.

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