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 opencue/cuecards --skill salary-negotiation-prepgit clone --depth 1 https://github.com/opencue/cuecardsWrote 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/opencue/cuecards/salary-negotiation-prep)<a href="https://agentmods.dev/skills/opencue/cuecards/salary-negotiation-prep"><img src="https://agentmods.dev/badge/skills/opencue/cuecards/salary-negotiation-prep.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 5.1 | $0.00021 | $0.02613 |
| Opus 5 | $0.00010 | $0.01307 |
| Sonnet 5 | $0.00004 | $0.00523 |
| Haiku 4.5 | $0.00002 | $0.00261 |
Grade A, and why
salary-negotiation-prep 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 4d 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.
This is a copy
100% identical to salary-negotiation-prep — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 379 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Salary Negotiation Prep
When to Use This Skill
Use this skill when the user wants to:
- Negotiate a job offer or salary
- Research market rates for their role
- Create a counter-offer strategy
- Understand total compensation packages
- Mentions: "salary negotiation", "negotiate offer", "counter offer", "compensation", "how much should I ask for"
Core Capabilities
- Research and validate market compensation
- Build negotiation strategy and scripts
- Calculate total compensation (not just base salary)
- Prepare counter-offer responses
- Identify negotiation leverage points
- Navigate difficult salary conversations
The Negotiation Mindset
Key Principles:
- Negotiation is expected - companies budget for it
- 84% of employers expect candidates to negotiate
- Not negotiating leaves $500K-$1M on the table over a career
- The goal is win-win, not adversarial
What You're Really Negotiating:
- Base salary
- Signing bonus
- Annual bonus/commission
- Equity (stock options, RSUs)
- Benefits (401k match, insurance)
- Perks (vacation, remote work, professional development)
- Start date
- Title
Research Phase
Step 1: Determine Market Rate
Sources to Check:
- Levels.fyi (best for tech)
- Glassdoor (general, take with grain of salt)
- LinkedIn Salary
- Blind (anonymous reports)
- PayScale
- Salary.com
- H1B salary data (publicly available)
Build a Range:
Low (25th percentile): $XXX,XXX
Target (50th percentile): $XXX,XXX
High (75th percentile): $XXX,XXX
Stretch (90th percentile): $XXX,XXX
Step 2: Know Your Value
Factors That Increase Your Worth:
- Years of relevant experience
- Specialized/rare skills
- Track record of results
- In-demand certifications
- Current competing offers
- Referral from employee
- Market demand in your field
Factors That May Limit:
- Entry level or career change
- Less experience than ideal candidate
- Gaps in required skills
- Location arbitrage (lower cost of living)
Step 3: Calculate Total Compensation
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.
- 4d ago First seen · 379 lines · 21 tokens per session scan A efac612f8ab5
salary-negotiation-prep is a skill published in the GitHub repository opencue/cuecards (5 stars, last pushed today), licensed MIT. It adds 21 tokens to every session and 2,613 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to salary-negotiation-prep, differing in 0 lines, and is treated as a copy.
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