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 naveedharri/benai-skills --skill create-an-assetgit clone --depth 1 https://github.com/naveedharri/benai-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/naveedharri/benai-skills/create-an-asset)<a href="https://agentmods.dev/skills/naveedharri/benai-skills/create-an-asset"><img src="https://agentmods.dev/badge/skills/naveedharri/benai-skills/create-an-asset/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/naveedharri/benai-skills/create-an-asset"><img src="https://agentmods.dev/badge/skills/naveedharri/benai-skills/create-an-asset.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, 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 Data Exfiltration · line 20 Code or instructions that leak agent conversation context to external services, potentially exposing sensitive user interactions.Fix: Remove any code that sends prompts, responses, or session data externally. Preserve user privacy; never exfiltrate conversation content.
- medium Memory Poisoning · line 53 Skill injects content designed to persist in agent memory or context across interactions. Persistent injection can alter agent behavior long after the initial interaction.Fix: Do not allow untrusted input to persist in agent memory or context. Validate all content before storing and implement memory isolation between sessions.
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 | $0.00048 | $0.00778 |
| Opus 5 | $0.00024 | $0.00389 |
| Sonnet 5 | $0.00010 | $0.00156 |
| Haiku 4.5 | $0.00005 | $0.00078 |
Grade A, and why
create-an-asset 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 11d 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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create an Asset
Generate custom sales assets tailored to prospect, audience, and goal. Four formats: interactive landing page, deck-style, one-pager, workflow/architecture demo. Works for any seller, any product, any prospect.
Triggers
Invoke this skill when:
- User says
/create-an-assetor/create-an-asset [CompanyName] - User asks to "create an asset", "build a demo", "make a landing page", "mock up a workflow"
- User needs a customer-facing deliverable for a sales conversation
Steps
Step 1: Collect context
Read references/context-collection.md. Detect seller context from the user's email domain, then collect the four inputs: (a) prospect, (b) audience, (c) purpose, (d) format. Parse what the user already gave before asking. If the format is a workflow demo, also collect components, flow, human touchpoints, and an example scenario (covered in the same file).
Step 2: Research the prospect
Read references/research.md. Assess context richness (rich / moderate / sparse) and run the matching research pass: prospect basics, leadership, and brand colors always; industry, tech stack, and competitive context when context is moderate or sparse; conversation analysis when transcripts or materials were uploaded.
Step 3: Decide the structure
Read references/format-selection.md. Pick sections, slides, or demo layers for the chosen format based on purpose and audience. If the format is a workflow demo, also read references/workflow-demo.md for component definitions, flow steps, and scenario narrative.
Step 4: Ask clarifying questions (required)
Read references/clarifying-questions.md. Summarize your plan back to the user, ask the standard questions plus the format-specific ones, and confirm before building. Max 2 rounds; if still ambiguous, make a reasonable choice and say so.
Step 5: Generate content
Read references/content-templates.md. Write every section using the templates and the general principles (their pain points, their language, explicit product-to-need mapping, proof points). For workflow demos, use references/workflow-demo.md for components, steps, and narrative.
What ships with it
8 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.
- 11d ago First seen · 56 lines · 48 tokens per session scan A 05f1efe7e3a0
create-an-asset is a skill published in the GitHub repository naveedharri/benai-skills (61 stars, last pushed 7d ago), licensed MIT. It adds 48 tokens to every session and 778 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 2026-08-30.
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