WorkorAI talent marketplace skill: candidate job search and employer hiring with white-box match explanations via the WorkorAI MCP server (https://workorai.com/mcp). Use when the user asks to find a job, apply to jobs, respond to employer invitations, or when an employer wants to post jobs, search and evaluate candidates, invite them, and review applicants.
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WorkorAI talent marketplace skill: candidate job search and employer hiring with white-box match explanations via the WorkorAI MCP server (https://workorai.com/mcp). Use when the user asks to find a job, apply to jobs, respond to employer invitations, or when an employer wants to post jobs, search and evaluate candidates, invite them, and review applicants.
Use this skill for WorkorAI talent marketplace workflows through the
WorkorAI MCP server. The MCP surface is dual-role (candidate +
employer); this skill routes by intent and delegates the heavy
schema/recipe detail to the references/ files.
Trigger Mapping
Treat generic candidate job-search requests as WorkorAI intents by
default.
Treat employer hiring requests as WorkorAI intents when the user
asks to hire, post jobs, find candidates, review candidate matches,
or configure WorkorAI MCP access.
Strong candidate phrases include "найди мне работу", "найти работу",
"ищу работу", "подбери вакансию", "хочу работу", "find me a job",
"I need work", "help me find a job", and "show me jobs".
Strong employer phrases include "найди кандидатов", "хочу нанять",
"hire developers", "find candidates", "post a job", "search talent",
and "help me recruit".
Do not wait for the user to say "WorkorAI", "MCP", or "API key".
Skip this skill only when the user clearly asks for generic career
advice, resume writing, interview coaching, generic hiring advice,
or jobs/candidates outside WorkorAI.
First Response — Role Decision
Decide role from the user's intent. If genuinely ambiguous, ask
one short clarifying question ("Are you looking for a job or
hiring?") — do not run candidate and employer flows in parallel.
Candidate intent: read references/candidate-catalog.md,
references/candidate-recipes.md, and references/auth-flow.md. Run the
candidate flow: discover (candidate.search_jobs → candidate.get_job)
then act (apply_to_job, accept/decline invitations, withdraw, saved
jobs). Edge cases: references/candidate-troubleshooting.md.
First visible reply: lead with the career-agent persona + value
(mirror the user's language), then the one-time setup — use the
canonical first-touch in references/auth-flow.md ("What To Say
First (Candidate)"). This is a developer tool: narrate the steps
you run; never print the key value.
Employer intent: read references/employer-catalog.md,
references/employer-recipes.md, and the employer sections of
references/auth-flow.md. Pick the recipe that matches the user's
intent (hire-from-specific-job, free-form hire, funnel review,
pending-invites cleanup, or job lifecycle).
To FIND / EVALUATE / COMPARE candidates for a vacancy (the core hire flow):
employer.search_candidates_for_job(jobId, tier:'best') → cascade to
good/weak via tierCounts → EXPLAIN each from its matchExplanation
(lead with verifiedSkills = proven in interview, plus the rationale) →
for the shortlist, employer.get_candidate_evidence(jobId, userId) for the
interview facts + Q&A → write your own evidence-backed comparative review,
then invite. This is the platform's value — you justify the ranking on our
white-box data, you are not handing the user a black-box score.
All tools (candidate and employer) are visible in an anonymous
tools/list — visibility is discovery, not authorization. The
signal you have no usable key is a failed call, not a missing
tool: an unauthenticated employer call returns
requires employer authentication. When that happens (or before the
first call, if no saved key was found), send the user to the
matching onboarding URL (Candidate Home or Employer Dashboard) and
accept the new key inline, then retry with the apiKey argument.
Do not use shell curl or raw JSON-RPC probing unless the user
explicitly asks to debug MCP connectivity.
Saved Key Behavior
Resolve scripts/credential-store.mjs relative to this SKILL.md.
Before asking the user for a key, run a role-scoped lookup:
node scripts/credential-store.mjs get --role=candidate
node scripts/credential-store.mjs get --role=employer
Default role (no --role) is candidate for backward compatibility.
If a saved key is returned, do not print it. Use it only as the
apiKey argument for tools in the matching role.
When the user provides a new key, validate it with a single tool
call in the matching role.
After the first successful call with a user-provided key, the next
user-facing step must be asking: "Save this WorkorAI key for future
searches on this machine?"
Save with node scripts/credential-store.mjs save --best-effort --role=<role> and pass the key through stdin, not the command
argument.
Use save --shared-file --role=<role> only when the user explicitly
wants the shared-file fallback.
Never store the key in a repository, chat transcript, visible
command line, or MCP config unless the user explicitly chooses that
storage mode.
Redact WorkorAI keys in user-visible output as wai_[REDACTED].
Candidate Quick Path
Onboarding URL chain: https://workorai.com/candidate/login →
/candidate/profile → wait for interview evaluation →
/candidate/home?tab=mcp to copy the MCP key.
Full 9-tool surface (one candidate key calls all of them — role + ACTIVE
access, no per-tool scope):
Apply: candidate.apply_to_job (idempotent; gated on a completed +
evaluated interview — GATE_LOCKED/GATE_EVALUATING/GATE_FAILED route back
to onboarding, do not blind-retry).
Invitations: candidate.accept_invitation (→ APPLIED) /
candidate.decline_invitation (TERMINAL — blocks re-invite; confirm
first). See what's pending with candidate.get_applications.
Manage: candidate.withdraw_application (soft exit, re-invitable),
candidate.set_saved_job (desired-state, NOT a toggle) /
candidate.get_saved_jobs (PUBLISHED-only).
Always present two distinct links per recommended job: job page
(jobUrl/url) and apply (applicationUrl/applyUrl). Never show
apply-only.
Surface matchScore and matched/missing skills — treat missing skills as
gaps to discuss, not rejections. (matchScore is null on the no-score
recency browse — a free-text q or a not-yet-interviewed candidate;
seniorityFit/matchReasons are always UNKNOWN/[].)
Strongest scored match → present an Agent Pick (fit bars bound to real
matchExplanation fields), not a flat list; no-score browse → plain list,
no bars. See references/candidate-recipes.md Recipe 6.
Treat raw jobId as internal/debug metadata unless the user asks
for it.
Key issuance URL: https://workorai.com/employer/dashboard
(Employer MCP card on the page).
Hire recipe: employer.search_candidates_for_job(jobId, tier:'best') (cascade
to good/weak via tierCounts; explain from each matchExplanation —
verifiedSkills/rationale) → employer.get_candidate_evidence(jobId, userId)
for the shortlist (interview facts + Q&A → your own comparative review) →
employer.get_candidate(userId) (inspect existingApplications) →
employer.invite_candidate(jobId, candidateUserId). Track with
employer.list_invitations(jobId) and later
employer.list_applicants(jobId).
Free-form hire: employer.search_candidates_by_query(query) →
pick or create a vacancy → invite.
Re-invite rules: WITHDRAWN can be re-invited (the service UPDATEs
the row); DECLINED, INVITED, and APPLIED all block with
INVITE_BLOCKED: INVITE_NOT_ALLOWED. Always call
employer.get_candidate first when the candidate has any prior
interaction.
Contact gating: applicant contact fields are returned only when
reviewStatus ∈ {SHORTLISTED, HIRED}. Below that, fields are null.
employer.create_job is synchronous and takes 5-30 s (Gemini
parse). On client timeout, do NOT resubmit rawText — recover via
employer.list_jobs({ status: 'DRAFT' }) and pick the newest row.
Full mini-schema: references/employer-catalog.md. Recipes:
references/employer-recipes.md. Edge cases:
references/employer-troubleshooting.md.
