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 marketinggit 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/marketing)<a href="https://agentmods.dev/skills/ericrisco/rsc-harness/marketing"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/marketing/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/marketing"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/marketing.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 | $0.00078 | $0.03631 |
| Opus 5 | $0.00039 | $0.01816 |
| Sonnet 5 | $0.00016 | $0.00726 |
| Haiku 4.5 | $0.00008 | $0.00363 |
Grade A, and why
marketing 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 5d 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 — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Marketing — Conversion Copy for Landings & Web Pages
The words, not the pixels. Ground in the brand study first, then write copy that is specific, benefit-led, and unmistakably this brand.
This skill owns conversion copywriting: value proposition, headlines, section-by-section landing copy, microcopy, CTAs, email/launch sequences, channel adaptation, and SEO-aware copy structure. The sibling design skill owns the visual/UX (type, color, layout, motion); nextjs owns the build — including rendering in React the Metadata and JSON-LD this skill specifies. Long-form articles, blog posts, or social content systems with no landing/web surface are a content job, not landing copy. When asked for "a landing page", you write the copy.
Brand grounding (read this first)
Hard rule: never produce landing, web-page, or marketing copy without a complete brand study. Generic copy is the failure mode this skill exists to prevent, and the cure is grounding every word in a real, persisted brand profile. An incomplete brand study is a hard STOP, not a warning.
Run this gate before writing a single line of copy:
-
Locate the brand study. Read the project's root
CLAUDE.mdand look for a## Brand & voicesection linking into02-DOCS/wiki/brand/(theharnessKarpathy-wiki convention: compiled brand articles live under02-DOCS/wiki/brand/, raw inputs the user pastes live under02-DOCS/raw/brand/). IfCLAUDE.mdis absent, the link is missing, or it points nowhere, treat the study as ABSENT. -
Check completeness against the checklist in
references/brand-grounding.md. The study is complete only when every dimension is filled: brand name & one-line positioning; ICP / audience & their pains & desires; value proposition & differentiation; tone & voice WITH do/don't word lists and 3–5 voice samples pasted from the user's real writing; proof/credibility; offers & primary CTA; channels; SEO keywords. Any empty dimension = INCOMPLETE. -
If ABSENT or INCOMPLETE, STOP and interview the user. Ask the targeted questions from
references/brand-grounding.md, one focused batch at a time (do not dump all questions at once; ask, wait, then continue). Voice samples are mandatory — request 3–5 pieces of the user's real writing; never fabricate a voice. Then:- a. Write/update the brand study into
02-DOCS/wiki/brand/as wiki articles (one article per dimension or a singleindex.mdplus per-dimension articles), following the wiki article format inreferences/brand-grounding.md, and index it in02-DOCS/wiki/index.md(the Knowledge map). Save any raw text the user pastes verbatim into02-DOCS/raw/brand/and link to it from the article's> Raw:line. Create the directories if they do not exist. - b. Add or update a
## Brand & voicesection in the rootCLAUDE.mdlinking to the brand study — a short pointer only. CreateCLAUDE.mdif absent (additive only — never delete existing sections). The exact snippet to insert is inreferences/brand-grounding.md.
- a. Write/update the brand study into
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.
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.
- 5d ago First seen · 184 lines · 78 tokens per session scan A 07a798c060ff
marketing is a skill published in the GitHub repository ericrisco/rsc-harness (74 stars, last pushed 2d ago), licensed MIT. It adds 78 tokens to every session and 3,631 once invoked, about $0.0004 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 2026-09-03.
Other skills, from other repositories
marketing-skills
42 marketing agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw, and 6 more coding agents. 7 pods: content, SEO, CRO, channels, growth, intelligence, sales. Foundation context + orchestration router. 27 Python tools (stdlib-only).
merge-aliases
Folds two surface names for the same backend system into one canonical entity, keeping every original mention individually retrievable, and refuses to merge pairs that only share spelling.
anchor-and-lock
Consults a check that sits outside the loop system before finalizing any decision the frozen facts bear on, and refuses every attempt by a loop to rewrite a node marked frozen, regardless of how convergent the loop's own reasoning looks.
trim-to-budget
Trims a task-scoped candidate subgraph down to a hard node-count budget, keeping the anchor plus the highest-relevance nodes, dropping any edge that touches a dropped node, and recording the exact cutoff score used.
scan-contradictions
Scans the fact graph for pairs of edges that cannot both hold true at once and flags each such pair, running as its own standing pass rather than as part of whatever task happens to be reading the graph.
counter-metric-check
Compares a watched loop's headline reading against an independently owned counter-metric reading for each period in a governance graph, and produces a governance edge for every period where the counter-metric crosses its recorded ceiling.