Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/work0r-ai/agent-kit/workorainpx skills add work0r-ai/agent-kit --skill workoraigit clone --depth 1 https://github.com/work0r-ai/agent-kitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/work0r-ai/agent-kit/workorai)<a href="https://agentmods.dev/skills/work0r-ai/agent-kit/workorai"><img src="https://agentmods.dev/badge/skills/work0r-ai/agent-kit/workorai.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00200 | $0.02769 |
| Opus 5 | $0.00100 | $0.01385 |
| Sonnet 5 | $0.00040 | $0.00554 |
| Haiku 4.5 | $0.00020 | $0.00277 |
Grade A, and why
workorai scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
5. Do not use shell `curl` or raw JSON-RPC probing unless the user How it starts
The opening of the file, as written. The whole thing — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WorkorAI
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, andreferences/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.
- 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
- Employer intent: read
references/employer-catalog.md,references/employer-recipes.md, and the employer sections ofreferences/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 togood/weakviatierCounts→ EXPLAIN each from itsmatchExplanation(lead withverifiedSkills= proven in interview, plus therationale) → 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.
- To FIND / EVALUATE / COMPARE candidates for a vacancy (the core hire flow):
- 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 returnsrequires 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 theapiKeyargument. - Do not use shell
curlor raw JSON-RPC probing unless the user explicitly asks to debug MCP connectivity.
What ships with it
13 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 554 B
- LICENSE.txt 1.0 KB
- references/auth-flow.md 10 KB
- references/candidate-catalog.md 12 KB
- references/candidate-recipes.md 6.6 KB
- references/candidate-troubleshooting.md 6.4 KB
- references/employer-catalog.md 20 KB
- references/employer-recipes.md 6.1 KB
- references/employer-troubleshooting.md 6.0 KB
- references/troubleshooting.md 5.1 KB
- scripts/__tests__/credential-store.role.test.mjs 7.7 KB runs code
- scripts/.npmignore 11 B
- scripts/credential-store.mjs 22 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 205 lines · 200 tokens per session scan A 1c27c401834d
workorai is a skill published in the GitHub repository work0r-ai/agent-kit (0 stars, last pushed 2mo ago), licensed MIT. It adds 200 tokens to every session and 2,769 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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