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 build-ai-visibility-panelgit 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/build-ai-visibility-panel)<a href="https://agentmods.dev/skills/elvisun/newsjack/build-ai-visibility-panel"><img src="https://agentmods.dev/badge/skills/elvisun/newsjack/build-ai-visibility-panel/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/build-ai-visibility-panel"><img src="https://agentmods.dev/badge/skills/elvisun/newsjack/build-ai-visibility-panel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00117 | $0.02603 |
| Opus 5.5 | $0.00047 | $0.01041 |
| Sonnet 5.5 | $0.00023 | $0.00521 |
| Haiku 4.5 | $0.00012 | $0.00260 |
Grade A, and why
build-ai-visibility-panel 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 24d 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Build AI Visibility Panel
You are the orchestration molecule. Given a URL and description, research the market, recover buyer needs and language, and return a comprehensive prompt list plus resumable panel artifacts.
“Comprehensive” means every evidence-supported dimension is covered and every unsupported dimension is shown as a gap. It does not mean inventing a full Cartesian grid or claiming the panel represents all AI users.
This skill inherits the ethical floor from skills/ETHICS.md. It enforces anti-hallucination, source permission, contamination control, and decay-aware research. Anti-spray and human-send are not applicable because it produces research and measurement plans, not outreach.
Required starting input
Accept:
- one public URL;
- a plain-language description of the company/product/service.
Use optional user inputs when supplied: business decision, estimands, target population, exclusions, markets/locales, competitors, surfaces, lanes, run/review budget, customer evidence, campaign terms, prior panel, and approver.
Do not block when only URL and description are supplied. Build a provisional directional charter, research public evidence, complete the full workflow, and return a candidate panel with explicit assumptions and approval gaps. Do not mark it frozen or representative.
Read the contracts
Before producing artifacts, read references/artifact-contracts.md. Use its exact enum names, filenames, common envelope, source manifest, prompt table columns, and completion checklist.
Measurement charter
Define before generating:
- business decision;
- estimand(s) and exact numerator/denominator;
- target population and exclusions;
- products, markets, locales, and time horizon;
- surfaces and lanes;
- reporting strata;
- run/review budget;
- desired precision or
directional_only; - human approver.
Allowed estimands are unaided_brand_presence, aided_brand_knowledge, competitive_mention_share, citation_presence, answer_framing, and campaign_response.
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.
- 24d ago Changed · +2 lines 91f991f69b30
- 1mo ago First seen · 188 lines · 117 tokens per session scan A 7acf6249b99a
build-ai-visibility-panel is a skill published in the GitHub repository elvisun/newsjack (1,652 stars, last pushed 2d ago), licensed MIT. It adds 117 tokens to every session and 2,603 once invoked, about $0.0005 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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