get_my_cv_pdfThe account's base CV (the saved profile, untailored) rendered as a PDF in the chosen design, returned as a file. No model call.
| Name | Required | Description | Default |
|---|---|---|---|
| design | No | Optional; defaults to the saved design. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is known. The description adds useful behavior beyond annotations: the result is returned as a file and no model call is made. No contradiction with annotations is present.
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 entire description is one efficient sentence that front-loads the primary purpose and adds only relevant differentiating details. Every clause contributes: untailored base CV, PDF rendering, file return, and no model call. There is no redundancy or filler.
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 simple read-only tool with one optional parameter, the description is complete: it specifies the resource, output format, file return behavior, and model-call behavior. The absence of an output schema is not a gap because the returned artifact is described as a file.
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 description coverage is 100%, and the single optional 'design' parameter is already documented with its default behavior. The description only references 'the chosen design' without adding new parameter meaning. Baseline 3 is appropriate because the schema handles parameter semantics.
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 specific resource, 'the account's base CV', and a clear action, 'rendered as a PDF ... returned as a file.' The parenthetical '(the saved profile, untailored)' distinguishes this from tailored CV variants like get_sent_cv_pdf or preview_tailored_cv. There is no ambiguity about what the tool does.
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 gives clear context: use this when you need the saved, untailored base CV as a PDF, and the 'No model call' note signals a low-cost retrieval. It does not explicitly name sibling tools or exclusion conditions, so it falls just short of fully explicit usage guidance.
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.