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 brand-voicegit 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/brand-voice)<a href="https://agentmods.dev/skills/ericrisco/rsc-harness/brand-voice"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/brand-voice/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/brand-voice"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/brand-voice.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 | $0.00081 | $0.03004 |
| Opus 5 | $0.00041 | $0.01502 |
| Sonnet 5 | $0.00016 | $0.00601 |
| Haiku 4.5 | $0.00008 | $0.00300 |
Grade A, and why
brand-voice 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 10d 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 — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Brand Voice — How the Brand Sounds
You own the reusable voice-and-tone system: 3–5 personality traits → concrete linguistic rules → a position on the four tone dimensions → a use/avoid word bank → a tone-by-context matrix → a paste-into-the-prompt voice-DNA block. The output is a persisted document, never a finished piece of copy.
The line: brand-voice owns the reusable definition of how the brand sounds. The moment you write one finished piece against it, that is a copywriting skill — page hero/value prop/CTA is landing-copy; launch emails and channel posts are ../marketing/SKILL.md; blog and article systems are content-engine, article-writing, newsletter, social-publisher; an investor narrative is ../pitch-deck/SKILL.md; a live customer ticket is customer-support (it consumes this guide, it does not author it). The way the brand looks — logo, color, type, design tokens — is brand-identity, and layout/motion is ../design/SKILL.md.
Voice vs. tone (the load-bearing distinction)
Voice is constant; tone flexes by context. Voice is the brand's fixed personality across everything it writes. Tone is the local adjustment for the reader's emotional state and the topic's sensitivity. A frustrated user does not want a joke; a celebration screen does not read like a financial disclosure — yet both are the same voice. (Nielsen Norman Group, "The Four Dimensions of Tone of Voice," pub. 2016-07-17, updated 2023-08-16.)
Why it matters: you author one voice and apply many tones. Conflate them and you get a guide that says "be playful" on a fraud-alert page — unusable. The guide locks voice once and tabulates tone per context (Step 5).
Why bother at all: consistent brand presentation correlates with revenue uplift — ~23% average, up to ~33% at the upper range across 1,800 brands in 14 industries (Lucidpress/Marq, "State of Brand Consistency"). Treat it as calibration for the effort, not a causal promise — it is a correlational study.
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.
- 10d ago First seen · 157 lines · 81 tokens per session scan A db421da88d4c
brand-voice is a skill published in the GitHub repository ericrisco/rsc-harness (78 stars, last pushed today), licensed MIT. It adds 81 tokens to every session and 3,004 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 2026-08-30.
Other skills, from other repositories
build-subgraph
Traverses a full graph and returns a bounded subgraph around one target node -- its depth-bounded dependencies plus any disputed claims attached to it -- while proving everything else was left out.
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.
arbitrate-collision
Detects when two loops have proposed conflicting writes to the same node and field at close to the same time, applies a stated priority rule to accept exactly one, and records the rejected write with the reason it lost.
audit-sweep
Reviews a full set of the main loop's outputs together, from a wider vantage than any single one of them, looking specifically for cross-item patterns that a one-item-at-a-time loop is structurally unable to notice.
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.