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100Hires - AI ATS & Recruitment Software

by com.100hires

hires_update_candidate

Destructive

Update candidate fields, profile answers, and optional resume text. Used for bi-directional sync from ATS, CRM, sourcing, or enrichment tools. When the user provides an attached resume, parse it yourself from chat context and pass via resume_text — do not inline binary data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesCandidate ID (integer) or alias (string).
cityNoCandidate city for location/timezone resolution.
emailNoCandidate email address.
phoneNoCandidate phone number.
stateNoCandidate state or region.
job_idNoJob ID to create a new application for this candidate.
countryNoCandidate country name or ISO code.
profileNoKey-value map of profile field answers. Keys can be question text or question_id.
stage_idNoPipeline stage ID for the application. Requires job_id.
timezoneNoIANA timezone (e.g. 'America/Los_Angeles'). Auto-resolved from city/country if omitted.
last_nameNoCandidate last name.
first_nameNoCandidate first name.
resume_textNoPlain-text resume content extracted by the model from an attached file. Stored as a text/plain attachment. Do not pass binary or base64 — only parsed text.

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already indicate the tool is destructive (destructiveHint: true). The description adds important behavioral context: resume_text must be parsed plain text from an attachment, not inline binary data. This exceeds what annotations provide.

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?

The description is extremely concise with two sentences. The first states the core function, the second adds usage context and an explicit instruction. Every sentence adds value without redundancy.

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?

Given 13 parameters, no output schema, and a destructive operation, the description covers the key aspects: what is updated, use case, and specific resume handling. It lacks details on return values and idempotency but is generally adequate.

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

Parameters3/5

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

Schema coverage is 100% with all parameters described. The description adds specific guidance for the resume_text parameter (parse from chat, no binary), but this is already implied by the schema description. No significant additional semantics beyond schema.

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 clearly states the tool updates candidate fields, profile answers, and optional resume text, specifying its use for bi-directional sync from various tools. This differentiates it from sibling tools like hires_create_candidate (create) and hires_update_application (update application).

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 provides context that the tool is intended for bi-directional sync from ATS, CRM, sourcing, or enrichment tools, but does not explicitly mention when not to use it or direct alternatives. However, the sibling list implies other tools for different purposes.

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

A3.7/5.0
Disambiguation4/5

Most tools have clearly distinct purposes due to specific entity and action combinations. However, with 133 tools, there is some overlap (e.g., multiple ways to move applications) and similar-sounding operations (e.g., batch_remove_tags vs remove_candidate_tag) that could cause confusion. The detailed descriptions help but the sheer number increases ambiguity.

Naming Consistency5/5

All tools follow a consistent 'hires_verb_noun' pattern with snake_case. Verbs are descriptive (create, list, get, delete, update, batch) and nouns match the domain entities (candidate, application, job, etc.). No mixing of conventions like camelCase or inconsistent verb styles.

Tool Count2/5

133 tools is excessive for a typical server scope. While a full-featured ATS requires many operations, this count suggests insufficient aggregation. Tools for similar entities (e.g., multiple update/delete variants) could be consolidated. The high number overwhelms the tool surface and increases complexity.

Completeness4/5

The tool set covers core CRUD operations for major entities (candidates, applications, jobs, companies, users, messages, forms, etc.) plus batch operations, webhooks, and advanced features like AI scoring and nurture campaigns. Minor gaps exist (e.g., no direct reporting/analytics tools), but most workflows can be executed.

Resources