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 preset-io/agent-skills --skill preset-mcpgit clone --depth 1 https://github.com/preset-io/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/preset-io/agent-skills/preset-mcp)<a href="https://agentmods.dev/skills/preset-io/agent-skills/preset-mcp"><img src="https://agentmods.dev/badge/skills/preset-io/agent-skills/preset-mcp/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/preset-io/agent-skills/preset-mcp"><img src="https://agentmods.dev/badge/skills/preset-io/agent-skills/preset-mcp.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00038 | $0.00495 |
| Opus 5 | $0.00019 | $0.00247 |
| Sonnet 5 | $0.00008 | $0.00099 |
| Haiku 4.5 | $0.00004 | $0.00049 |
Grade A, and why
preset-mcp scanned grade A with 1 finding 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 12d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Do not use direct Preset Management API, Superset REST API, Snowflake Cortex API, curl, Python requests, exports, or database calls from this package. How it starts
The opening of the file, as written. The whole thing — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
preset-mcp
Use for Superset MCP intent, MCP tool routing, and MCP/API surface-boundary decisions.
Always
- Stay on MCP tools for MCP intent.
- Treat
superset/superset/mcp_serviceas the only source of truth for MCP tool names, schemas, tags, annotations, prompts, resources, and RBAC metadata. - Call tools directly with the obvious parameters; fetch a tool's schema only after a validation error. These skills are workflow guidance, not schema definitions.
- Do not use direct Preset Management API, Superset REST API, Snowflake Cortex API, curl, Python requests, exports, or database calls from this package.
- If MCP cannot satisfy the request, stop and explain the missing MCP capability. Do not switch surfaces.
Decision Rules
- MCP intent includes MCP tools, MCP clients, Superset MCP, Preset MCP, MCP resources, MCP prompts, tool discovery, and MCP tool errors.
- Direct API intent includes API credentials, REST endpoints, OpenAPI, curl/Python requests, Management API, workspace API, and Snowflake Cortex APIs.
- If the user starts with MCP intent and mentions direct API only as a fallback, keep MCP intent. Say: "No API fallback. Direct API is a different surface and requires separate explicit approval. Stop before API calls."
- When the session is connected through MCP tools and the user has not named a surface, default to MCP and proceed; ask only when the user explicitly mixes both surfaces in one request.
- Use a domain skill after routing: discovery, data, visualization, dashboard, sqllab, datasets, or troubleshooting.
Workflow Order
- Identify whether the user requested MCP or direct API.
- For MCP, choose the narrowest MCP domain skill.
- Call the tool with the obvious parameters; consult its schema only after a validation error.
- If MCP lacks a requested capability, explain the missing MCP capability.
- Ask before changing surfaces and stop before API calls.
Retrieve
- Tool categories and loading strategy: references/tool-categories.md
- Surface boundary examples: references/surface-boundary.md
What ships with it
2 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.
- 12d ago First seen · 38 lines · 38 tokens per session scan A b3d4241e2d0c
preset-mcp is a skill published in the GitHub repository preset-io/agent-skills (11 stars, last pushed yesterday), licensed Apache-2.0. It adds 38 tokens to every session and 495 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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