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-apigit 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-api)<a href="https://agentmods.dev/skills/preset-io/agent-skills/preset-api"><img src="https://agentmods.dev/badge/skills/preset-io/agent-skills/preset-api/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-api"><img src="https://agentmods.dev/badge/skills/preset-io/agent-skills/preset-api.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 | $0.00047 | $0.00737 |
| Opus 5.5 | $0.00019 | $0.00295 |
| Sonnet 5.5 | $0.00009 | $0.00147 |
| Haiku 4.5 | $0.00005 | $0.00074 |
Grade A, and why
preset-api scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Read and format JSON responses with `curl ... | jq`: use `jq -r` when capturing scalar shell values such as tokens, IDs, and hostnames; use plain `jq` for structured JSON output; do not use inline `python -c` parsers. How it starts
The opening of the file, as written. The whole thing — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
preset-api
Use as the prerequisite for direct Preset API skills. If the user is working through Preset/Superset MCP tools, stay on MCP unless they approve direct API calls.
Always
- Keep
PRESET_CLIENT_ID,PRESET_CLIENT_SECRET, and tokens out of source, logs, reports, and examples. - When checking whether credential environment variables are present, use a zsh-safe
printenv "$VAR_NAME"pattern. Do not use bash-only indirect expansion such as${!var}. - Read and format JSON responses with
curl ... | jq: usejq -rwhen capturing scalar shell values such as tokens, IDs, and hostnames; use plainjqfor structured JSON output; do not use inlinepython -cparsers. For reusable parsing, loadskills/preset-api/examples/preset_client.pyinstead of improvising. - Use the workspace hostname or API base URL directly when it is already known from trusted context (for example, an earlier Management API response or user-supplied configuration); derive it through the Management API when provenance is missing.
- Run reads directly: metadata reads always; customer-data reads (chart data, samples, distinct values, existing screenshots/thumbnails, own query history) when the user asked in their own message, with row limits as request parameters and summarized output.
- Require explicit confirmation before mutations, imports, role/RLS changes, guest-token creation, permalink creation, screenshot/thumbnail cache generation, cache invalidation, all asset exports, credential-bearing reads, audit downloads, and SQL that is not a confidently classified single-statement SELECT.
- When a target, owner, workspace, output destination, SQL classification, or credential boundary cannot be proven from trusted context, fall back to confirmation.
Decision Rules
- Use existing authenticated Preset API context; never ask users to paste secrets.
- Select base URL from discovered team, workspace, or Superset workspace facts.
- Use pagination and Rison for list, filter, sort, and search calls.
- Load safety policy before risky follow-up calls.
- If the user starts with direct API intent and mentions MCP only as a fallback, keep direct API intent. Say: "No MCP fallback. MCP tools are a different surface and require separate explicit approval. Stop before MCP calls."
- Do not stop direct API planning just because MCP was mentioned. Stop only before MCP calls or before direct API operations that require confirmation.
What ships with it
4 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.
- 1mo ago First seen · 44 lines · 47 tokens per session scan A 1f9ca2e29b7b
preset-api is a skill published in the GitHub repository preset-io/agent-skills (13 stars, last pushed 18d ago), licensed Apache-2.0. It adds 47 tokens to every session and 737 once invoked, about $0.0002 per session on Opus 5.5. 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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