Borrowing it
Nothing to install: this file belongs to cypggs/ai-job-search-cn. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/cypggs/ai-job-search-cn/master/.claude/commands/apply.mdgit clone --depth 1 https://github.com/cypggs/ai-job-search-cnWrote 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/cypggs/ai-job-search-cn/apply)<a href="https://agentmods.dev/commands/cypggs/ai-job-search-cn/apply"><img src="https://agentmods.dev/badge/commands/cypggs/ai-job-search-cn/apply/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/cypggs/ai-job-search-cn/apply"><img src="https://agentmods.dev/badge/commands/cypggs/ai-job-search-cn/apply.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 | $0.00000 | $0.04990 |
| Opus 5 | $0.00000 | $0.02495 |
| Sonnet 5 | $0.00000 | $0.00998 |
| Haiku 4.5 | $0.00000 | $0.00499 |
Grade A, and why
apply 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 11d 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 — 314 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/apply - Drafter-Reviewer Job Application Workflow
You are orchestrating a two-agent job application workflow. The job posting is provided below as $ARGUMENTS (either a URL or pasted text).
Follow these steps exactly in order. Do not skip steps.
Token-efficiency rules for this workflow:
- Never re-Read a file whose contents are already in your context from an earlier step. If you read it in Step 1, it is still available in Step 2.
- When dispatching the reviewer agent, pass draft content inline in the agent prompt rather than asking the agent to Read files you already have in memory.
- Run the full verification checklist exactly once, at the end (Step 6). The reviewer focuses on content critique, not verification.
- Step 5 (compile and inspect PDFs) is mandatory and non-skippable — LaTeX page-break decisions are unpredictable, and
.texfiles that look fine often produce broken PDFs (orphaned entry titles, cover letters spilling to page 2, bullet fonts mismatching).
Step 0: Parse Input
- If
$ARGUMENTSlooks like a URL, useWebFetchto retrieve the job posting content. Chinese job portals (BOSS 直聘, 拉勾, 猎聘, 智联招聘, 前程无忧) often block automated access; ifWebFetchfails or returns a login/antibot page, ask the user to paste the job description text. - If it is pasted text, use it directly.
- Extract: company name, role title, department (if mentioned), location, and language of the posting (Chinese or English).
- Determine the target market: if the posting is in Chinese, targets a Chinese company, or uses Chinese salary conventions (e.g.
20k-30k·14薪), treat it as a China market application. - Store these for use throughout the workflow.
Step 1: DRAFTER - Evaluate Fit
Read the evaluation framework:
.claude/skills/job-application-assistant/04-job-evaluation.md.claude/skills/job-application-assistant/01-candidate-profile.md
Using the framework from 04-job-evaluation.md, evaluate the job posting against the candidate's profile. If the salary lookup tool is configured, run:
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.
- 11d ago First seen · 314 lines · 0 tokens per session scan A 765f1bfaff34
apply is a command published in the GitHub repository cypggs/ai-job-search-cn (61 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 4,990 tokens. 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 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.