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

With no annotations, the description carries the full burden and does so thoroughly: it discloses the OAuth access token requirement in the Authorization header, the filtering rule (only orgs with at least one live plan are listed), the 1000-item listing cap, and that zero organizations is a success rather than an error. It also explains the billing consequence that motivates the user-confirmation rule.

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?

Purpose is front-loaded and the sentence order (what it does, why, how to behave, auth, return shape, edge cases) is logical. It is on the long side and the triple negative example ('not the first listed, not the only one with a plan flag, not the one whose name resembles the work') is slightly repetitive, though it does add concrete clarification.

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?

Without an output schema, the description still documents the return shape ('organizations' with id, name, website, useZapi and useScrapycloud flags) and semantics of the flags. Combined with the auth and edge-case notes, an agent has everything needed to call and interpret this tool correctly.

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, which sets a baseline of 4. The description reinforces this with 'Takes no arguments; the answer is always about the credential's own user,' adding meaning beyond the empty schema without needing to document any parameter.

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 precise verb and resource ('List the Zyte organizations your credential belongs to') and enumerates the three concrete reasons to call it: identity check, obtaining an organizationId, and detecting multi-org credentials. No sibling tool overlaps this identity-listing role, so an agent can distinguish it immediately.

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?

Explicitly covers the when: it names the follow-on use (passing the result as another tool's organizationId) and gives concrete decision rules for the ambiguous case — ask the user when multiple orgs come back, never default to the first/plan-flagged/similar-named one, and reuse the single org all session when exactly one exists. This is when/how guidance with an explicit exclusion ('do not choose for them').

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