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 skills add jasonjgarcia24/ai-assisted-job-search --skill likert-screening-tutorgit clone --depth 1 https://github.com/jasonjgarcia24/ai-assisted-job-searchWrote 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/jasonjgarcia24/ai-assisted-job-search/likert-screening-tutor)<a href="https://agentmods.dev/skills/jasonjgarcia24/ai-assisted-job-search/likert-screening-tutor"><img src="https://agentmods.dev/badge/skills/jasonjgarcia24/ai-assisted-job-search/likert-screening-tutor/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/skills/jasonjgarcia24/ai-assisted-job-search/likert-screening-tutor"><img src="https://agentmods.dev/badge/skills/jasonjgarcia24/ai-assisted-job-search/likert-screening-tutor.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 | $0.00142 | $0.01314 |
| Opus 5 | $0.00071 | $0.00657 |
| Sonnet 5 | $0.00028 | $0.00263 |
| Haiku 4.5 | $0.00014 | $0.00131 |
Grade A, and why
likert-screening-tutor 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.
How it starts
The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Likert-Scale Behavioral Screening Preparation
Assessment Overview
This skill focuses on Likert-scale behavioral screenings, particularly Google's Hiring Assessment (GHA) format, which is representative of this assessment type. Key facts about the GHA:
- Duration: ~30 minutes, 75-100 questions
- Format: One question per screen, no going back
- Response scale: 5-point Likert (Strongly Disagree → Strongly Disagree) for behavioral statements; multiple-choice for situational judgment
- Scoring: Automated pattern-matching against successful past applicant benchmarks
- Consistency checks: Similar questions rephrased throughout to detect inconsistency
- Mixed items: Some questions score you; others are test items for future assessments (you won't know which)
- Result timeline: Typically 24-72 hours
- Retest cooldown: 6 months if you fail; results valid for 2 years if you pass
- Confidentiality: Candidates agree not to record, screenshot, or share actual questions
Two Question Types
Type 1: Behavioral Likert Statements
A statement about workplace behavior. Rate your agreement: Strongly Disagree / Disagree / Neutral / Agree / Strongly Agree.
Type 2: Situational Judgment Scenarios
A workplace scenario with 4-5 possible actions. Select the best (and sometimes worst) course of action.
Eight Assessment Categories
All questions map to these categories. See references/question_bank.md for the full practice question bank organized by category.
- Ethics & Integrity — Honesty, doing the right thing even when no one is watching, handling confidential information
- Collaboration & Teamwork — Working across teams, valuing diverse perspectives, supporting colleagues
- Communication — Clarity, active listening, adapting message to audience, giving/receiving feedback
- Adaptability & Resilience — Handling ambiguity, pivoting under pressure, learning from failure
- Leadership & Initiative — Stepping up without formal authority, mentoring, influencing others
- Organizational Skills & Structured Thinking — Prioritization, planning, data-driven decisions
- User/Customer Focus — Putting the end user first, thinking about impact
- Continuous Learning & Growth Mindset — Seeking feedback, improving, intellectual humility
What ships with it
2 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.
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 · 97 lines · 142 tokens per session scan A c60b5f314262
likert-screening-tutor is a skill published in the GitHub repository jasonjgarcia24/ai-assisted-job-search (11 stars, last pushed 6mo ago), licensed MIT. It adds 142 tokens to every session and 1,314 once invoked, about $0.0007 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 skills, from other repositories
hr-onboarding
A new-hire onboarding plan as a single page — first week schedule, buddy + manager intro, learning track, equipment checklist, and "you're set when…" outcomes. Use when the brief mentions "onboarding", "new hire", "first week plan", or "入职".
book-mirror
Take any book (EPUB/PDF), produce a personalized chapter-by-chapter analysis. Each chapter is preserved in detail (The Chapter) and mirrored back to the reader's actual life (The Mirror) using brain context. The mirror observes and resonates — a friend pointing out parallels, NOT a consultant rearranging the reader's…
miniapp
Build a tiny interactive HTML playground only when someone asks to see, play with, or step through a mechanism.
eli5
Explain research, papers, or technical ideas in plain English with minimal jargon, concrete analogies, and clear takeaways. Use when the user says "ELI5 this", asks for a simple explanation of a paper or research result, wants jargon removed, or asks what something technically dense actually means.
deck-course-module
A course or workshop slide template with persistent learning goals, teaching pages, multiple-choice self-tests, and a wrap-up.
master-yinguang
A reference-based assistant for questions about Yinguang and Pure Land Buddhism, a Buddhist tradition focused on faith, ethical living, and practice connected with rebirth in the Pure Land. It can answer in Yinguang’s historical teaching style.