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 ADIKANT/datalens-dev-mcp --skill datalens-dashboardgit clone --depth 1 https://github.com/ADIKANT/datalens-dev-mcpWrote 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/adikant/datalens-dev-mcp/datalens-dashboard)<a href="https://agentmods.dev/skills/adikant/datalens-dev-mcp/datalens-dashboard"><img src="https://agentmods.dev/badge/skills/adikant/datalens-dev-mcp/datalens-dashboard/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/adikant/datalens-dev-mcp/datalens-dashboard"><img src="https://agentmods.dev/badge/skills/adikant/datalens-dev-mcp/datalens-dashboard.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 | $0.00029 | $0.00267 |
| Opus 5 | $0.00015 | $0.00133 |
| Sonnet 5 | $0.00006 | $0.00053 |
| Haiku 4.5 | $0.00003 | $0.00027 |
Grade A, and why
datalens-dashboard 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 yesterday.
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.
What it actually says
DataLens Dashboard
Separate object name, visible title, hint, and geometry. Apply explicit requirements first, then an explicit reference, project defaults, user defaults, and the generic recipe. For new recipe charts, carry the compiled visual_contract into item presentation so the selected title and hint owner survives placement; see the canonical example in the composition reference. On update, preserve live tabs, widgets, relations, and manual layout outside the requested change.
Read references/composition.md before composing selectors, parameters, or multi-object dashboards. Validate the full batch with dl_editor_validate(drafts=...), then create dependencies in explicit order. Use the typed dashboard draft for ordinary tabs/widgets and retain raw snapshots for exact imports or documented SDK gaps.
Follow authorized scope and delivery for mutations: explicit scoped work continues without repeated permission questions; read-only and save-only limits remain binding.
For new visual or semantic decisions, consult only the relevant part of visualization decisions; preserve the accepted reference and infer routine context without a mandatory questionnaire.
What ships with it
3 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.
- yesterday Changed · +4 lines 775225b132f8
- 2d ago First seen · 11 lines · 29 tokens per session scan A c3199a957631
datalens-dashboard is a skill published in the GitHub repository ADIKANT/datalens-dev-mcp (5 stars, last pushed yesterday), licensed Apache-2.0. It adds 29 tokens to every session and 267 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 2026-09-08.
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