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/jain777/jobclaw-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/rules/jain777/jobclaw-skills/apply-to-job)<a href="https://agentmods.dev/rules/jain777/jobclaw-skills/apply-to-job"><img src="https://agentmods.dev/badge/rules/jain777/jobclaw-skills/apply-to-job/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/rules/jain777/jobclaw-skills/apply-to-job"><img src="https://agentmods.dev/badge/rules/jain777/jobclaw-skills/apply-to-job.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 | $0.00120 | $0.00241 |
| Opus 5 | $0.00060 | $0.00120 |
| Sonnet 5 | $0.00024 | $0.00048 |
| Haiku 4.5 | $0.00012 | $0.00024 |
Grade A, and why
apply-to-job 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 12d 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.
What it actually says
apply-to-job
This task maps to the apply-to-job skill in this repo. Read skills/apply-to-job/SKILL.md and follow it exactly — it is the single source of truth for this workflow.
Before producing any output, obey the shared rules in skills/_shared/RULES.md (never fabricate, never echo the context: block, region-pack-first, no emoji, known-info gate).
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.
- 12d ago First seen · 11 lines · 120 tokens per session scan A accb49cac431
apply-to-job is a cursor rule published in the GitHub repository jain777/jobclaw-skills (5 stars, last pushed 3mo ago), licensed MIT. It adds 120 tokens to every session and 241 once invoked, about $0.0006 per session on Opus 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 cursor rules, from other repositories
reflection-basic
Basic reflection format for Level 2 Simple Enhancement tasks.
cursor-fable-rules
Fable coding lifecycle discipline and situational awareness for Cursor.
git-workflow
Rules for git operations, commit strategy, and GitHub CLI usage.
feedback-enhanced
Rules for an interactive feedback system that lets users and an AI agent discuss complex development work in real time. It includes guidance for recording decisions, tracking progress and handling detailed inputs such as code and diagrams.
122-swift-development
122: Swift development workflow including TDD, refactoring, and performance optimization.
ponytail
Ponytail, lazy senior dev mode. Always pick the simplest solution that works.