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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely useful context beyond that: no additional account is needed, the same key and credit balance apply, and the call itself is free ("Kostet nichts"). It does not describe the shape of the result (separate tool vs. endpoint lists), which is the remaining 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 purpose and routing are front-loaded, but the body is a long run-on sentence that dumps a dozen-plus keyword domains, then repeats the same content in a trailing English summary. The bilingual duplication and enumeration dilute the routing information the agent actually needs. It could be cut by half without losing decision-relevant content.

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 read-only discovery tool with three fully documented parameters and no output schema, the description covers purpose, cost/auth context, and the follow-up execution path. The main omission is what the response looks like (tool list vs. endpoint list, and how ORG_AMBIGUOUS surfaces), though the schema hints at the latter.

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 query, limit and organization are already documented with examples and the ORG_AMBIGUOUS prerequisite. The description only adds that keywords may be German or English, which is a minor semantic contribution. Baseline 3 is appropriate when the schema carries the parameter burden.

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 opening sentence names a specific verb and resource: it searches Skael tools and endpoints by keyword, in German or English. The long capability list (enrichment, e-mail finding, Google Maps, LinkedIn, etc.) clarifies the domain but is example enumeration rather than sharper definition. It is clearly distinguishable from siblings like run_endpoint or get_results, which are execution/retrieval tools rather than discovery.

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 explicitly routes the agent: discovered tools are executed with run_endpoint {tool, arguments} and endpoints with run_endpoint {endpoint, input}, whole lead lists go to start_lead_project, and social leads to find_instagram_leads / find_tiktok_leads / find_youtube_leads. This is a concrete when-to-use-this-versus-that mapping, not an implied one.

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