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 itallstartedwithaidea/agent-skills --skill assistant-presetsgit clone --depth 1 https://github.com/itallstartedwithaidea/agent-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/itallstartedwithaidea/agent-skills/assistant-presets)<a href="https://agentmods.dev/skills/itallstartedwithaidea/agent-skills/assistant-presets"><img src="https://agentmods.dev/badge/skills/itallstartedwithaidea/agent-skills/assistant-presets.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00026 | $0.01499 |
| Opus 5 | $0.00013 | $0.00749 |
| Sonnet 5 | $0.00005 | $0.00300 |
| Haiku 4.5 | $0.00003 | $0.00150 |
Grade A, and why
assistant-presets 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 8d 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 — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Assistant Presets
Part of Agent Skills™ by googleadsagent.ai™
Description
Assistant Presets provides a framework for creating, testing, and deploying specialized AI assistant configurations for domain-specific tasks. Each preset encapsulates a system prompt, model parameters, tool access permissions, output format constraints, and quality benchmarks into a reusable, versionable artifact that transforms a general-purpose LLM into a domain expert.
A bare LLM is a generalist. A well-crafted preset turns it into a specialist: a legal contract reviewer that flags liability clauses, a medical triage assistant that follows diagnostic protocols, a code reviewer that enforces team conventions, or a customer support agent that follows the company's tone guide. The difference between a useful AI assistant and a frustrating one is almost entirely in the preset configuration.
This skill codifies the process of building high-quality presets: defining the persona and constraints, writing few-shot examples, specifying output formats, selecting appropriate model parameters (temperature, top-p, max tokens), and validating against a benchmark of expected inputs and outputs. Presets are version-controlled and A/B tested before deployment.
Use When
- Creating domain-specific AI assistants (legal, medical, finance, code review)
- Standardizing AI behavior across a team or organization
- Building a library of reusable assistant configurations
- Optimizing system prompts for specific use cases
- A/B testing different assistant configurations
- The user asks for a "custom assistant", "persona", or "system prompt"
How It Works
graph TD
A[Define Domain + Task] --> B[Write System Prompt]
B --> C[Add Few-Shot Examples]
C --> D[Configure Parameters]
D --> E[Define Output Format]
E --> F[Create Benchmark Dataset]
F --> G[Evaluate Against Benchmark]
G --> H{Quality Threshold Met?}
H -->|No| I[Iterate on Prompt]
I --> B
H -->|Yes| J[Version + Deploy]
J --> K[A/B Test in Production]
K --> L[Monitor + Maintain]
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.
- 8d ago First seen · 167 lines · 26 tokens per session scan A e32c6fa8b8bd
assistant-presets is a skill published in the GitHub repository itallstartedwithaidea/agent-skills (37 stars, last pushed 4mo ago), licensed MIT. It adds 26 tokens to every session and 1,499 once invoked, about $0.0001 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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