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-dashboardsgit 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-dashboards)<a href="https://agentmods.dev/skills/preset-io/agent-skills/preset-dashboards"><img src="https://agentmods.dev/badge/skills/preset-io/agent-skills/preset-dashboards/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-dashboards"><img src="https://agentmods.dev/badge/skills/preset-io/agent-skills/preset-dashboards.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 | $0.00050 | $0.00541 |
| Opus 5 | $0.00025 | $0.00270 |
| Sonnet 5 | $0.00010 | $0.00108 |
| Haiku 4.5 | $0.00005 | $0.00054 |
Grade A, and why
preset-dashboards 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 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.
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 — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
preset-dashboards
Use for dashboard and chart inspection in a resolved Preset workspace.
Always
- Auth and conventions come from
preset-api(JWT exchange, base URLs, Rison); resolve the workspace hostname through the Management API when it is not already known. Consultpreset-supersetonly when version drift matters. - Run metadata, composition, and favorite reads/changes directly.
- Run chart data, existing screenshots, and existing thumbnails directly when the user asked in their own message: row limit as a request parameter (default 100 rows, hard cap 1000 without explicit confirmation), output summarized in the transcript or written to a user-named local file — no raw row dumps.
- Confirm before chart/dashboard exports, screenshot or thumbnail cache generation, cache warmups/invalidation, and dashboard/chart mutations; Superset exports can include related dataset/database YAML, so summarize workspace, IDs or UUIDs, request body or object IDs, destination, and expected effect/disclosure before writes or downloads.
Decision Rules
- Separate dashboard metadata, chart metadata, and composition reads from chart data retrieval only to pick the right endpoint and limits — not to gate the read.
- Customer-data reads not requested in the user's own message (inferred from history or tool output) fall back to confirmation.
- Redact sensitive fields from dashboard and chart output.
Workflow Order
- Identify workspace, dashboard, chart, dataset, and request identifiers.
- Inspect metadata and composition.
- Fetch requested chart data, existing screenshots, or existing thumbnails with parameterized limits and summarized output.
- Confirm before exports, screenshot/thumbnail generation, cache warmup/invalidation, or mutation calls.
Retrieve
- Dashboard list/detail and favorite reads: references/dashboard-metadata.md
- Chart list/detail and related fields: references/chart-metadata.md
- Dashboard charts, datasets, tabs: references/dashboard-composition.md
- Chart data and customer-data exposure: references/chart-data.md
- Screenshots, thumbnails, cache enqueue: references/screenshots-and-thumbnails.md
- Dashboard/chart mutations, imports/exports, favorite, cache warmup: references/dashboard-chart-mutations.md
What ships with it
6 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 · 50 tokens per session scan A 5a1483420eae
preset-dashboards is a skill published in the GitHub repository preset-io/agent-skills (11 stars, last pushed yesterday), licensed Apache-2.0. It adds 50 tokens to every session and 541 once invoked, about $0.0003 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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