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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals the return shape ({items, next_cursor}), the matching behavior (q matches title only), and the ordering (newest first). It also mentions the presence of `role_url` in each item, which is useful for citations. However, details like pagination mechanics, response size limits, or error handling are omitted, so it's not fully transparent but substantially informative.

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?

Two sentences with zero filler. The first establishes the resource and ordering; the second packs the matching semantics, filters, and return format. Front-loaded and efficient, every clause contributes value.

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 tool with 6 parameters, an output schema, and no annotations, the description gives the essential behavioral contract (return shape, matching scope, filters). It does not explain the units for `comp_min` or the exact meaning of 'working arrangement' relative to the `remote` enum, but these are minor gaps given the schema's enum values provide some clarity. Overall, a well-rounded description that leaves few critical unknowns.

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 0%, so the description must compensate. It explains `q` (title match), `seniority` (seniority filter), `comp_min` (pay floor), and `remote` indirectly via 'working arrangement'. The `limit` and `cursor` are not individually described but are standard pagination parameters inferable from the return structure. This is a solid recovery given zero schema descriptions, though a couple of parameters rely on 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 the tool lists 'Open roles on Parlel' with a specific ordering ('newest first'), and explicitly notes that `q` matches the TITLE only. This gives a precise verb+resource and distinguishes it from sibling tools like search_agents, search_people, and search_companies, which target different entity types. The purpose is unmistakable.

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 implies usage for finding job postings on Parlel and mentions available filters (working arrangement, seniority, pay floor). It does not explicitly state when not to use it or name alternatives, but the sibling set clearly indicates that this is the go-to tool for open roles. The filtering hints help an agent decide how to narrow results, but explicit exclusion guidance is absent.

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