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 event4u-app/agent-config --skill brand-identitygit clone --depth 1 https://github.com/event4u-app/agent-configWrote 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/event4u-app/agent-config/brand-identity)<a href="https://agentmods.dev/skills/event4u-app/agent-config/brand-identity"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/brand-identity/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/event4u-app/agent-config/brand-identity"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/brand-identity.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 | $0.00038 | $0.01314 |
| Opus 5 | $0.00019 | $0.00657 |
| Sonnet 5 | $0.00008 | $0.00263 |
| Haiku 4.5 | $0.00004 | $0.00131 |
Grade A, and why
brand-identity 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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
brand-identity
Grounding + Method skill. Turns a confirmed brand strategy into an identity constraint set: colour story, type story, logo direction, imagery direction. It DEFINES tokens and constraints — it does not render marks. Dependency direction: pack-brand (B) exports constraints; pack-ai-image (A) consumes them. brand-to-tokens emits the DTCG token file from these constraints. logo-generation and brand-asset-generation generate the actual marks from these constraints. Never invert that direction.
When to use
- After
brand-strategyis confirmed (archetype, voice, positioning settled). - When deriving the colour story, type story, logo direction, or imagery direction for a project.
- Before running
brand-to-tokensto emit the DTCG token file. - Before handing constraints to
logo-generationorbrand-asset-generationin pack-ai-image.
Procedure
-
Receive the confirmed strategy — archetype, voice, positioning, and target sector from
brand-strategy. Refuse to proceed if strategy is still a draft. -
Ground the colour story via the brand corpus:
./scripts-run <skills-root>/corpus-grounding/scripts/ground search \
--manifest <skills-root>/brand/data/manifest.json \
"<archetype + sector>" --domain color --json
Read confidence and evidence_gap from the response. Record both verbatim in the output. Derive colour roles (primary, secondary, neutral, accent) and direction (temperature, contrast ratio floor, emotional register).
- Ground the type story via:
./scripts-run <skills-root>/corpus-grounding/scripts/ground search \
--manifest <skills-root>/brand/data/manifest.json \
"<archetype + sector>" --domain typography --json
Output is a pairing-filter + heading/body class labels, not concrete tokens. Hand this filter to typography-system for the actual type tokens.
- Ground the logo direction via:
./scripts-run <skills-root>/corpus-grounding/scripts/ground search \
--manifest <skills-root>/brand/data/manifest.json \
"<archetype + sector>" --domain logo --json
What ships with it
1 file 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 · 105 lines · 38 tokens per session scan A df36e89ac8ef
brand-identity is a skill published in the GitHub repository event4u-app/agent-config (10 stars, last pushed today), licensed MIT. It adds 38 tokens to every session and 1,314 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 2026-08-31.
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