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 rampstackco/claude-skills --skill ai-content-collaborationgit clone --depth 1 https://github.com/rampstackco/claude-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/rampstackco/claude-skills/ai-content-collaboration)<a href="https://agentmods.dev/skills/rampstackco/claude-skills/ai-content-collaboration"><img src="https://agentmods.dev/badge/skills/rampstackco/claude-skills/ai-content-collaboration/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/rampstackco/claude-skills/ai-content-collaboration"><img src="https://agentmods.dev/badge/skills/rampstackco/claude-skills/ai-content-collaboration.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 | $0.00134 | $0.04638 |
| Opus 5 | $0.00067 | $0.02319 |
| Sonnet 5 | $0.00027 | $0.00928 |
| Haiku 4.5 | $0.00013 | $0.00464 |
Grade A, and why
ai-content-collaboration 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 9d 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 — 282 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Content Collaboration
A senior editorial leader's playbook for how humans and AI compose in content workflows. Pragmatic, tool-agnostic, honest about both what AI in the loop enables and what it threatens.
Most content programs in 2026 use AI somewhere in the workflow. Pretending otherwise is dishonest; treating AI as a magic content factory is the failure mode this skill exists to prevent. The discipline is in between: knowing where AI legitimately accelerates, where humans must own, what hybrid patterns produce work that earns reader trust, and what crosses the line into AI slop or intellectual dishonesty.
This skill is the WORKFLOW layer that composes with every other content skill. Briefs can be AI-assisted; hub architectures can be AI-assisted; programmatic SEO is almost always AI-involved; editorial QA now includes AI-content audit by necessity. The collaboration discipline applies to all production stages, not to a single artifact type.
The voice is pragmatic and tool-agnostic deliberately. The methodology applies whether the AI in your loop is one of the major commercial models, an open-source model, or whatever ships next quarter. What stays constant is the workflow shape, the participation boundaries, the voice ownership question, and the ethical frame. What changes is which specific tool you reach for, which is implementation work that varies by team and budget.
When to use this skill: building or refining an AI-content workflow, calibrating a team on consistent AI usage, addressing the "we use AI but our work feels generic" problem, designing disclosure policies, or working through the ethics of AI-assisted content production for a regulated or trust-sensitive context.
What this skill is for
This skill spans the workflow layer of AI-assisted content production. It composes with all six other content-suite skills as the cross-cutting discipline.
content-strategyis program scope: what to produce. Strategy decisions can be AI-assisted; the program-level judgment stays human.pillar-content-architectureis hub scope: how the topical hub fits together. Hub architecture can be AI-suggested; the architectural commitment stays human.content-brief-authoringis per-piece scope: briefs each piece. Briefs can be AI-drafted from research; the contract decisions stay human.content-and-copyis execution scope: writes each piece. Drafts can be AI-produced; voice and editorial judgment stay human.programmatic-seois scaled scope: generates pages from data. AI generation is the dominant production model; sampling QA is the human gate.editorial-qais gate scope: verifies before publish. AI-content audit is now a load-bearing gate; the audit's judgment stays human.- This skill is workflow scope: how the human and AI layers compose across all six stages above.
What ships with it
9 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.
- references/ai-participation-boundaries.md 7.3 KB
- references/ai-slop-detection-and-avoidance.md 8.4 KB
- references/common-collaboration-failures.md 10 KB
- references/disclosure-and-transparency-patterns.md 9.2 KB
- references/ethics-and-intellectual-honesty.md 10 KB
- references/hybrid-workflow-patterns.md 8.1 KB
- references/quality-calibration-with-ai-in-loop.md 8.9 KB
- references/team-training-and-calibration.md 8.3 KB
- references/voice-ownership-preservation.md 8.2 KB
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.
- 9d ago First seen · 282 lines · 134 tokens per session scan A 8c31ddb0f217
ai-content-collaboration is a skill published in the GitHub repository rampstackco/claude-skills (830 stars, last pushed yesterday), licensed MIT. It adds 134 tokens to every session and 4,638 once invoked, about $0.0007 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 2026-08-30.
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