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 landedjobs/ai-job-hunt-os --skill salary-negotiatorgit clone --depth 1 https://github.com/landedjobs/ai-job-hunt-osWrote 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/landedjobs/ai-job-hunt-os/salary-negotiator)<a href="https://agentmods.dev/skills/landedjobs/ai-job-hunt-os/salary-negotiator"><img src="https://agentmods.dev/badge/skills/landedjobs/ai-job-hunt-os/salary-negotiator/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/landedjobs/ai-job-hunt-os/salary-negotiator"><img src="https://agentmods.dev/badge/skills/landedjobs/ai-job-hunt-os/salary-negotiator.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 | $0.00049 | $0.00900 |
| Opus 5 | $0.00024 | $0.00450 |
| Sonnet 5 | $0.00010 | $0.00180 |
| Haiku 4.5 | $0.00005 | $0.00090 |
Grade A, and why
salary-negotiator 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 — 41 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Salary Negotiator
Prepare the user to negotiate calmly, specifically, and by level. Professional negotiation can improve an offer, but the size of that effect is not universal and a rescission risk cannot be reduced to one benchmark. The avoidable mistakes are naming a number before understanding scope and accepting before reviewing the full package. The scripts below get users through both. Full scripts per moment live in references/negotiation-scripts.md; load them when the user reaches that moment.
Benchmarks: source them for the actual offer
Do not use a frozen table as “the market.” Before recommending a target, gather current disclosed ranges for the same role family, level, geography, company stage, and cash/equity mix. Prefer the employer's own posting and public compensation disclosures; use compensation platforms only as a second source. Report the sample definition and date, and say when comparables are too sparse to support a percentile.
Calibration rules:
- Do not promise an “AI premium.” Any premium changes by level, geography, company, and market cycle. Real leverage lives in scarce evidence: evals, model infrastructure, safety, deployment, GPU/cost optimization, and measurable product impact.
- Level before number. These bands blend mid through staff. Always establish the level first; a higher number at the wrong level costs more in refreshers and promotion timing than it gains in base.
- Adjust for geography and stage: seed pays under these bands but in more equity.
The method (blend of the three canon approaches)
- From Haseeb Qureshi: protect process. Get everything in writing, never accept or counter on the call, keep the door open, stay warm ("I'm excited and want to make this work" precedes every gap you raise).
- From patio11: remember the stakes. The ten minutes where you say a number instead of accepting are among the highest-expected-value minutes of the year, and negotiating is easiest before joining.
- From calibrated questions (Voss): make them solve it. "What flexibility is there on equity given the gap to market?" and "How can we close the gap with sign-on or refreshers?" outperform demands, and never sound like ultimatums.
What ships with it
1 file 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 · 41 lines · 49 tokens per session scan A 246114fdf6d4
salary-negotiator is a skill published in the GitHub repository landedjobs/ai-job-hunt-os (1 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 900 once invoked, about $0.0002 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.
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