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.
git clone --depth 1 https://github.com/Aznatkoiny/zAI-SkillsWrote 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/commands/aznatkoiny/zai-skills/job-hunt)<a href="https://agentmods.dev/commands/aznatkoiny/zai-skills/job-hunt"><img src="https://agentmods.dev/badge/commands/aznatkoiny/zai-skills/job-hunt/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/aznatkoiny/zai-skills/job-hunt"><img src="https://agentmods.dev/badge/commands/aznatkoiny/zai-skills/job-hunt.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00021 | $0.01025 |
| Opus 5.5 | $0.00008 | $0.00410 |
| Sonnet 5.5 | $0.00004 | $0.00205 |
| Haiku 4.5 | $0.00002 | $0.00103 |
Grade A, and why
job-hunt scanned grade A with 0 findings 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 1mo 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are running the career-coach job-hunt pipeline: search for jobs matching the user's profile, enrich the best matches with salary and company data, score them by skill overlap, and produce a ranked report plus tracker entries.
Read career-profile.json from the project root first. If it doesn't exist, stop and tell the user to run the resume-updater skill first.
Arguments
$ARGUMENTS
- If arguments name a role focus (e.g., "staff platform engineer, remote"), search for that, still using the profile's locations, salary range, and remote preference as filters.
- If arguments are empty or say
from profile, search for every role intarget.rolesfrom career-profile.json.
Pipeline
1. Build search queries
For each target role, include common title variants (e.g., "ML Engineer" also searches "Machine Learning Engineer" and "Applied Scientist"). Apply target.locations and target.remote_preference as filters.
2. Search
Call mcp__job-intelligence__job_search_jobs once per role variant. Independent searches should be issued in parallel. Deduplicate results by company + title.
3. Enrich the top ~10
Rank the deduplicated results by initial fit, then for the top ~10 call, in parallel per job:
mcp__job-intelligence__job_get_salary_data(company + role + location) — compensation rangemcp__job-intelligence__job_get_company_info(company) — ratings, size, culture
These tools are scraper-backed and may fail or return partial data per company; note gaps in the output rather than blocking.
4. Score by skill overlap
For each enriched job, compute a skill-match score against the profile:
- Extract required skills from the listing text
- Match against
skills.technical,skills.tools, andskills_usedacross experience entries (case-insensitive, count close variants like "Postgres"/"PostgreSQL" as matches) - Score = matched required skills / total required skills; also note seniority fit, salary alignment vs
target.salary_range, and location fit
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.
- 1mo ago First seen · 87 lines · 21 tokens per session scan A 34404c689050
job-hunt is a command published in the GitHub repository Aznatkoiny/zAI-Skills (10 stars, last pushed 2mo ago), licensed MIT. It adds 21 tokens to every session and 1,025 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
budget
Manage the token budget for Claude Code sessions. Model-aware — picks the right effective context window and prices per model. The session's REAL model is read from the transcript by the budget hook; config.model is only the fallback. Everything from Sonnet 4.6 up is 1M; Haiku 4.5 is 200K.
orchestrate
Do this task as an orchestrator. The aim is the same result at a fraction of the cost: in a long session, every token in this conversation is re-read on each later request, while a subagent's reading is discarded when it returns. The plugin's subagents run on Haiku 5.5, about 40× cheaper per token than Opus 5.5.
conjure-agent
Creates or updates a Claude Code agent definition (/.claude/agents/ .md or project-local).
conjure
Use when you want to build a new Claude Code skill, agent, hook, or MCP server but aren't sure which — or when you want to describe what you want in plain language. Auto-detects the right artifact type, asks targeted questions, explains the reasoning, then builds it.
conjure-mcp
Create a Claude Code MCP (Model Context Protocol) server. Provide a description of what external system or data source you want Claude to connect to.
conjure-help
Show help for the conjure toolkit — all commands, argument syntax, update modes, and decision guide. Use when you want to know which conjure command to use or how any conjure command works.