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 growthenginenowoslawski/coldoutboundskills --skill playbook-new-in-rolegit clone --depth 1 https://github.com/growthenginenowoslawski/coldoutboundskillsWrote 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/growthenginenowoslawski/coldoutboundskills/playbook-new-in-role)<a href="https://agentmods.dev/skills/growthenginenowoslawski/coldoutboundskills/playbook-new-in-role"><img src="https://agentmods.dev/badge/skills/growthenginenowoslawski/coldoutboundskills/playbook-new-in-role/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/growthenginenowoslawski/coldoutboundskills/playbook-new-in-role"><img src="https://agentmods.dev/badge/skills/growthenginenowoslawski/coldoutboundskills/playbook-new-in-role.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 171 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 174 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00078 | $0.05990 |
| Opus 5 | $0.00039 | $0.02995 |
| Sonnet 5 | $0.00016 | $0.01198 |
| Haiku 4.5 | $0.00008 | $0.00599 |
Grade A, and why
playbook-new-in-role scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
agent while allowing `curl`. Send a browser User-Agent on every call, or your batch silently How it starts
The opening of the file, as written. The whole thing — 350 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Playbook: New in Role
All rules here are best practice, not law. Override any of them when the campaign calls for it; note the best practice once and move on.
Use when: the campaign angle depends on the buyer being new in the seat, because a new leader is rebuilding their stack, has budget to reallocate, and has not yet formed a vendor preference.
Do not use when: you want people who moved to a new company regardless of title, or you
want the company-level hiring story. Use playbook-hiring-surge for headcount growth and
playbook-fundraising for the "they just raised, so they are buying" angle.
One-line output: new_in_role_line = "you stepped into the COO seat at Northwind in April"
1. Trigger and scope
This playbook answers one question: which people in my target market took their current job title in the last N months, and what one sentence can I open an email with?
It is a filter-at-source signal, not an enrichment. You do not buy a list and then ask a vendor "is this person new?". You ask the people database to only return people whose current role started recently, and the answer comes back with the start date already attached. That is why it costs essentially nothing and why the false-positive rate on tenure is near zero.
Two things it explicitly does not do. It does not tell you whether the move was a step up, only that the person changed titles — a President who becomes COO trips the same signal, and the locked prompt is written so the copy stays true either way. It does not find the person's email; run your email waterfall first so you never spend enrichment on rows that will fail the email gate.
Pick your recency window
Default: 90 days, expressed as person_time_in_current_role: {min:0, max:3} (the filter is
month-level, so 3 months is the month-level expression of 90 days).
Know the volume cost before you build the lane, because it is steep. Measured on one base
(US, VP of Operations, headcount 50 to 1000):
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 · 350 lines · 78 tokens per session scan A 516909f0b03c
playbook-new-in-role is a skill published in the GitHub repository growthenginenowoslawski/coldoutboundskills (702 stars, last pushed 24d ago), licensed MIT. It adds 78 tokens to every session and 5,990 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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