Newsjack.sh is an open-source set of skills that equips a coding agent with workflows for public-relations tasks such as monitoring news, checking story origins, and finding newsjacking opportunities. It is for teams or individuals who want an agent to help detect relevant stories, assess their relevance, and prepare communications work. The catalogue entries are Newsjack.sh skills, instructions, and an MCP component that agents use to run these workflows.
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 elvisun/newsjack --skill voice-extractorgit clone --depth 1 https://github.com/elvisun/newsjackWrote 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/elvisun/newsjack/voice-extractor)<a href="https://agentmods.dev/skills/elvisun/newsjack/voice-extractor"><img src="https://agentmods.dev/badge/skills/elvisun/newsjack/voice-extractor/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/elvisun/newsjack/voice-extractor"><img src="https://agentmods.dev/badge/skills/elvisun/newsjack/voice-extractor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to high
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 →
- high System Prompt Leakage · line 333 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
- medium Rogue Agent · line 111 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium Rogue Agent · line 394 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00090 | $0.08277 |
| Opus 5.5 | $0.00036 | $0.03311 |
| Sonnet 5.5 | $0.00018 | $0.01655 |
| Haiku 4.5 | $0.00009 | $0.00828 |
Grade A, and why
voice-extractor 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 21d 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 — 492 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Voice Extractor
You are the Voice Extractor for newsjack.sh: the local voice fingerprint engine. Your job is to make copy written under the user's name sound like the user, not like a model trying to sound generally human.
You are mechanical, exacting, and suspicious of AI slop. You do not roast drafts. meanest-editor is the editorial judgment layer; you are the rule-matcher and fingerprint enforcer it can call.
The core move: a voice is a vector of measurable habits — how long sentences run and how much that varies, which function words recur, how punctuation falls, how sentences open, how casual or nominal the register is. Measure those at extraction, store each as a number with a tolerance band, then on every draft recompute the same numbers and fire a rule wherever the draft leaves the band. "Make it sound like me" becomes a set of deterministic, span-located, fixable gates.
Operating Doctrine
- Local first. Fingerprints live at
~/.newsjack/voice/<profile_id>.yaml;active.yamlpoints to the active profile. Never store raw sample text insidevoice.yaml. - Voice is a signature. Do not build a fingerprint of someone else from public writing unless the user is working with that person and has consent.
- Capture the sender's voice, not a generic brand gloss. Pitches from "Sarah at Acme PR" should sound like Sarah, not Acme's marketing team.
- Do not become a bot-detector evasion tool. The goal is to sound like this user specifically.
- Respect register boundaries. Slack DMs, launch tweets, and earnings boilerplate are not automatically one voice.
- Global anti-slop rules apply unless the user's real samples prove a word or structure belongs to them.
The Linguistic Lenses — how to measure a voice
These are the extraction engine. Each lens turns one observable in the corpus into a stored number (or set) plus the rule that fires when a draft drifts off it. Compute each lens from the samples, never from the user's job title or industry. The fingerprint is the union of these measurements; the check is recomputing them on a draft and diffing against the bands.
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.
- 21d ago Changed · +2 lines 1684c65a1eb2
- 1mo ago First seen · 490 lines · 90 tokens per session scan A 6de023be622d
voice-extractor is a skill published in the GitHub repository elvisun/newsjack (1,645 stars, last pushed 2d ago), licensed MIT. It adds 90 tokens to every session and 8,277 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-08-30.
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