Рекомендации о кандидате от бывших коллег и руководителей (с их согласия) — trust-сигнал перед офером. / References from former colleagues and managers.
| Name | Required | Description | Default |
|---|---|---|---|
| candidate | No | Slug кандидата (из search_candidates). В личном режиме не обязательно: отправьте null или не передавайте параметр. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that references come with the consent of former colleagues and managers, which is useful behavioral context, but it does not state whether this operation is read-only, whether any external parties are contacted, or what side effects might occur. The 'get' prefix implies reading, but the description itself is moderately informative.
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 short, front-loaded with the core meaning, and adds a purpose signal. The Russian and English versions repeat the same information, which is slightly redundant but not harmful, so it earns a 4 rather than a 5.
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 tool with one optional parameter and no output schema, the description explains what the tool returns and when to use it. It could mention output format or empty-reference behavior, but the core information needed for correct invocation is present.
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%, so the single `candidate` parameter is already documented in the schema. The description adds no additional meaning about how the parameter should be used, which keeps this at the baseline 3 rather than higher.
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 clearly identifies the tool as returning references about a candidate from former colleagues and managers, giving a specific resource and content type. It also frames it as a trust signal before an offer, which distinguishes it from siblings like get_profile, get_resume, and get_contacts.
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 phrase 'trust-сигнал перед офером' explicitly indicates when to use this tool: before making an offer. It does not name alternatives or exclusions, but the timing context is clear enough for an agent to select it appropriately among the listed siblings.
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.
Each tool targets a distinct candidate resource or workflow step: profile, resume, conditions, contacts, FAQ, references, interview, assessment, vacancy matching, and messaging are clearly separated. Even similar get_* tools are differentiated by description, and ask_about_experience is explicitly a targeted query rather than a full document.
Most tools follow a clear imperative get_/send_/manage_/match_/message_ pattern, making the set predictable. The exceptions are 'assessment' and 'recruiter_context', which are noun-only names and break the verb-led convention, though the lowercase snake_case style is consistent throughout.
Thirteen tools is well within the ideal range for a recruiting-focused server. Each tool covers a meaningful step in the candidate engagement workflow, from initial context and profile retrieval to vacancy sending, matching, interviewing, and assessment, with no obvious bloat.
The core candidate lifecycle is well covered: viewing candidate information, contacting them, sending vacancies, matching against job descriptions, proposing interviews, and managing assessments. Minor gaps exist around post-assessment progression, explicit offer/rejection handling, and broader pipeline or status management, but agents can mostly work around these.