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 ur-grue/autopunk-media-skills --skill newsroom-ai-policygit clone --depth 1 https://github.com/ur-grue/autopunk-media-skillsWrote 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/ur-grue/autopunk-media-skills/newsroom-ai-policy)<a href="https://agentmods.dev/skills/ur-grue/autopunk-media-skills/newsroom-ai-policy"><img src="https://agentmods.dev/badge/skills/ur-grue/autopunk-media-skills/newsroom-ai-policy/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/ur-grue/autopunk-media-skills/newsroom-ai-policy"><img src="https://agentmods.dev/badge/skills/ur-grue/autopunk-media-skills/newsroom-ai-policy.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 Excessive Agency · line 199 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 447 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00040 | $0.10009 |
| Opus 5 | $0.00020 | $0.05005 |
| Sonnet 5 | $0.00008 | $0.02002 |
| Haiku 4.5 | $0.00004 | $0.01001 |
Grade A, and why
newsroom-ai-policy 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 8d 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 — 520 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Newsroom AI Policy
What This Skill Does
Generates a complete, publication-ready AI usage policy document tailored to the newsroom's specific context — covering permitted uses, prohibited uses, disclosure requirements, quality gates, training, accountability, and review cadence.
When To Use This Skill
- Your newsroom has no AI policy and reporters are already experimenting with AI tools — you need clear rules before ad hoc habits calcify into unwritten norms
- Your existing AI policy is a one-paragraph statement ("use AI responsibly") and you need specific, enforceable guidance that reporters can actually follow
- You're launching a new publication or digital desk and want AI rules baked in from day one
- Your editor-in-chief or legal team has asked for a formal policy document they can circulate to all staff and freelancers
- You've had an incident — a factual error traced to AI-generated text, a source who discovered AI was used to process their interview, a reader who noticed AI-sounding prose in a bylined column — and you need a policy response fast
- You manage a publication that relies on freelancers and contributors, and you need a policy that extends to people who are not on staff but publish under your masthead
- Your newsroom is part of a larger media group and you need a local policy that fits within corporate guidelines but addresses your specific editorial context
- A journalism school, press association, or industry group has asked you to draft a model AI policy that others can adapt
What You Need To Provide
Required: A description of the newsroom — size (number of editorial staff), beats covered, publication type (daily newspaper, weekly magazine, digital-only, broadcast, etc.), and the editorial values or principles the publication already follows (even informally).
Optional inputs that improve the output:
- Specific AI tools already in use or under consideration (Claude, ChatGPT, Gemini, Otter.ai, Descript, Midjourney, etc.)
- Any incidents or concerns that motivated the policy request — the more specific, the more targeted the policy
- The newsroom's stance on transparency with readers (do you have a public trust statement, a reader advisory board, a corrections policy?)
- Existing style guide or ethics code to align with (SPJ Code of Ethics, AP style, internal house rules)
- Whether the policy needs to address freelancers, stringers, contributors, interns, or only full-time staff
- Any regulatory or union constraints (collective bargaining agreements, GDPR, state privacy laws, industry codes)
- The name and title of the person who will own the policy
- Whether the publication uses AI-adjacent tools already (automated CMS tagging, SEO suggestion tools, audience analytics dashboards) and whether those should be in scope
- The publication's stance on AI-generated images, audio, and video — not just text
- Whether the newsroom has a formal editorial workflow (story budgets, assignment trackers, CMS with tagging) or works informally
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.
- 8d ago First seen · 520 lines · 40 tokens per session scan A 2ebe0ce938c0
newsroom-ai-policy is a skill published in the GitHub repository ur-grue/autopunk-media-skills (32 stars, last pushed 12d ago), licensed MIT. It adds 40 tokens to every session and 10,009 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 2026-09-04.
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