Skip to main content
Glama

100Hires - AI ATS & Recruitment Software

by com.100hires

Search candidates

hires_list_candidates
Read-only

List candidates with optional filters. Supports filtering by job, stage, email, name, LinkedIn, and date ranges. Returns paginated results. Recommended size <= 10: candidate payloads include the full profile answers array and can be large; if the response exceeds the budget the tool returns isError:true with error_code=response_too_large and retry hints — reduce size, narrow filters, or fetch a single record via hires_get_candidate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoPlain-text search by name or email. Supports partial matches.
pageNoPage number (1-based).
sizeNoNumber of items per page.
viewNoResponse shape. Default `summary` excludes the `profile` array (custom profile-form answers). Use `full` only when those answers are genuinely needed; call hires_get_candidate for a single full record.summary
emailNoExact candidate email filter.
job_idNoFilter candidates by job ID.
includeNoComma-separated related data. Supported: `applications` — embeds each candidate's application summaries with job titles and pipeline stages. Recommended when the caller needs stage/pipeline context (e.g. UI rendering, candidate-status questions).
linkedinNoSearch by LinkedIn profile URL or alias (e.g. 'johndoe' or full URL).
stage_idNoFilter candidates by pipeline stage ID. Best used together with job_id.
full_nameNoCandidate full-name filter.
company_idNoFilter by company ID. Required only when the API key has access to multiple companies.
created_afterNoReturn only candidates created at or after this time. Unix timestamp (seconds) or ISO-8601 string (e.g. 2026-05-11T00:00:00Z). Fractional seconds accepted but truncated.
updated_afterNoReturn only candidates updated at or after this time. Unix timestamp (seconds) or ISO-8601 string (e.g. 2026-05-11T00:00:00Z). Fractional seconds accepted but truncated. Useful for incremental sync.

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already mark the tool as read-only. The description adds significant behavioral context: the risk of large responses (profile answers), potential error_code=response_too_large, retry hints, and the trade-off between summary/full views. This goes beyond the annotations.

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: two sentences plus an error-handling note. It is front-loaded with the tool's purpose, then filters, then important warnings. Every sentence adds value, and there is no 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?

Despite 13 parameters and no output schema, the description covers filters, pagination, payload size guidance, error handling, and a fallback option. It omits details about the response structure (e.g., what fields are returned), but given the lack of output schema, a slightly lower score is warranted. Still, it provides enough context for an agent to use the tool correctly.

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 input schema has 100% description coverage, so the description cannot add much per-parameter detail. However, it adds critical context for the 'size' parameter (recommend <=10) and reinforces the 'view' parameter's purpose. This extra guidance justifies a score above the baseline 3.

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 'List candidates' and enumerates specific filters (job, stage, email, name, LinkedIn, date ranges), distinguishing it from sibling list tools like hires_list_applications. It also notes paginated results, leaving no ambiguity about the tool's function.

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 gives explicit guidance on when to use this tool (listing with filters) and includes a critical warning about payload size (recommend size<=10) and error handling. It suggests an alternative (hires_get_candidate) for single full records. However, it does not explicitly state when not to use it or compare to other list tools.

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

All 100Hires - AI ATS & Recruitment Software toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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