update_profileChange fields of the saved profile without re-uploading the CV. Send only the fields to change (full_name, contact_email, phone, location, city, address, postcode, professional_summary, skills, pinned_skills, languages, experience, education, projects, certifications, links, …); everything else is untouched. The feed is re-ranked against the new CV.
| Name | Required | Description | Default |
|---|---|---|---|
| patch | Yes | Profile fields to change, by name. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are all false, providing no safety hints, so the description carries the behavioral burden. It discloses that untouched fields remain untouched (patch semantics) and that the feed will be re-ranked as a side effect. This goes beyond the structured data and helps set expectations.
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 three sentences with no filler. The purpose is front-loaded, input semantics follow, and the side effect is stated last. Every sentence earns its place.
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?
Given the open-ended patch object and lack of output schema, the description provides the key details: what to send, that changes are partial, and that the feed re-ranks. The ellipsis acknowledges additional fields without an exhaustive enumeration. It doesn't cover validation or errors, but for this tool it is sufficiently complete.
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 schema only says 'Profile fields to change, by name.' The description greatly expands this by listing numerous concrete field names and explaining the partial-update behavior ('everything else is untouched'). This is essential for correctly constructing the patch object.
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 states a clear verb+resource: 'Change fields of the saved profile'. It also distinguishes the tool from upload_cv by explicitly saying 'without re-uploading the CV'. The list of concrete fields further clarifies exactly what the tool operates on.
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 explains when to use this tool: when changing profile fields without replacing the CV. It also gives usage guidance by telling the agent to send only the fields to change, implying a partial update. It doesn't explicitly name alternatives beyond the CV-upload distinction, but the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Tool purposes are generally distinct and well-described, but a few clusters overlap in function: answer_screening_question vs save_answer both write to the answer book, get_my_profile vs get_account both report plan status, and the CV preview/sent-CV/base-CV tools could be confused. The detailed descriptions mitigate most misselection, so this is only a minor issue.
The set almost uniformly uses snake_case verb_noun names like list_, get_, update_, create_, delete_, and start_/stop_. Minor deviations such as login, describe_what_i_want, and the get_my_* vs list_* alternation prevent a perfect score, but the overall pattern is predictable and readable.
49 tools is far above the 25+ threshold and will burden agent tool selection even though many are legitimate single-purpose operations. Several groups could be consolidated—billing links, API-key management, and the CV PDF family—without hurting clarity.
The surface covers the full lifecycle: account creation/auth, profile and CV, targeting, matching, apply runs, screening answers, tracking, billing, export, and deletion. Minor gaps remain, such as no application-level detail/withdrawal endpoint and no direct way to save a parsed CV without re-uploading, but agents can work around them.