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 ericrisco/rsc-harness --skill content-enginegit clone --depth 1 https://github.com/ericrisco/rsc-harnessWrote 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/ericrisco/rsc-harness/content-engine)<a href="https://agentmods.dev/skills/ericrisco/rsc-harness/content-engine"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/content-engine/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/ericrisco/rsc-harness/content-engine"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/content-engine.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 YARA Match · line 3 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
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 | $0.00083 | $0.03125 |
| Opus 5.5 | $0.00033 | $0.01250 |
| Sonnet 5.5 | $0.00017 | $0.00625 |
| Haiku 4.5 | $0.00008 | $0.00313 |
Grade A, and why
content-engine 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 16d 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 — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Engine — The Calendar and the Pipeline That Feeds It
The factory floor and the production schedule, not the words off any single station. You own two machines: the calendar (what gets made and when — a dated, slotted plan anchored to pillars, so "what do we post Thursday?" is a lookup, not a weekly panic) and the pipeline (how each slot moves from idea to publish-ready through stage gates, so output is consistent regardless of who writes). You do not write the pieces and you do not publish them — you decide what gets made, you spec the brief, and you route each station to a specialist.
Content fails not from one bad post but from no system: no documented cadence, no brief, no stage gate, pillars that never get atomized. ~78% of high-performing content teams run a documented strategy and see ~3x the engagement of teams without one (InfluenceFlow, 2026). This skill is that system.
Ground first (STOP gate)
You plan content for a real brand; you do not invent its strategy. Before building anything, read what already exists.
- Read the brand study and pillars from
02-DOCS/(the project wiki). If the project uses the harness convention, that is02-DOCS/wiki/— see../harness/SKILL.md. - If voice/tone is missing → STOP. Route the user to
brand-voiceto codify do/don't words and voice samples. Do not invent a voice; a calendar built on a guessed voice produces off-brand drafts at every station. - If pillars/clusters/keywords are missing → STOP for the research half. Route topic-cluster and keyword work to
seo-geo. You consume pillars and clusters; you do not derive them from search data — that is its job. - Persist the calendar of record under
02-DOCS/wiki/content/and raw inputs (interviews, exports) under02-DOCS/raw/content/. Why: the calendar must be a durable artifact of record, not a chat message that scrolls away. - Cite what you grounded in (e.g. "pillars from
02-DOCS/wiki/brand-study.md"). If you grounded in nothing, say so and stop.
What ships with it
5 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.
- 16d ago Changed · +9 lines 9db32f5576b2
- 1mo ago First seen · 153 lines · 83 tokens per session scan A 76dc62942ca3
content-engine is a skill published in the GitHub repository ericrisco/rsc-harness (340 stars, last pushed today), licensed MIT. It adds 83 tokens to every session and 3,125 once invoked, about $0.0003 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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