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Upload my CV (PDF or DOCX)

upload_cv

Upload a CV file and turn it into the account's profile: the same parser the app uses reads the document into name, contact, summary, roles, skills, languages and education. With save=true (default) the profile is saved and the job feed is built from it; with save=false the parsed profile is returned for review only. Max 8 MB.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
saveNo
filenameYese.g. cv.pdf
content_base64YesThe file's bytes, base64-encoded.

TDQS

A4.4/5.0
Behavior4/5

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

Annotations only indicate that this is not read-only, so the description carries the burden of explaining side effects. It does so by disclosing that the default behavior saves the profile and rebuilds the job feed, and that save=false avoids persistence. It also adds practical constraints: PDF/DOCX formats and an 8 MB limit.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three dense sentences with no filler: purpose, parsed fields, save behavior, and size limit are all covered. The most important outcome is front-loaded, and the conditional branch is explained immediately after.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers accepted formats, size limit, parsed fields, and the persistence vs review-only behavior, which is sufficient for most calls. The main gap is that it does not explicitly state what a successful save=true response contains, but the absence of an output schema is partially mitigated by describing the resulting profile state.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema documents filename and content_base64 and notes save's default, but the description adds meaningful semantics: save=true vs false changes whether the parser result is persisted or just returned, and file type/size constraints are called out. This supplements the schema rather than merely repeating it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource: it uploads a CV file and converts it into the account's profile. It also lists the parsed fields, making the tool's function concrete and distinct from read-oriented siblings like get_my_profile or preview_tailored_cv.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly explains the two modes of use: save=true saves the profile and builds the job feed, while save=false returns the parsed profile for review only. It does not explicitly name alternatives like update_profile or preview_tailored_cv, but the conditional behavior provides solid usage guidance.

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

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TDQS

A3.6/5.0
Disambiguation4/5

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.

Naming Consistency4/5

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.

Tool Count2/5

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.

Completeness4/5

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.

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