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 agentmods add skills/agentlas-ai/agentlas-desktop/authornpx skills add agentlas-ai/agentlas-desktop --skill authorgit clone --depth 1 https://github.com/agentlas-ai/agentlas-desktopWrote 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/agentlas-ai/agentlas-desktop/author)<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/author"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/author.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 | $0.00016 | $0.00510 |
| Opus 5 | $0.00008 | $0.00255 |
| Sonnet 5 | $0.00003 | $0.00102 |
| Haiku 4.5 | $0.00002 | $0.00051 |
Grade A, and why
author 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 4d 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.
What it actually says
Purpose
Turn a table into a portable data.<name>.flint object. The host compiles the
same object to Vega-Lite and renders it with the local Desktop runtime or the
Web server runtime. This skill is an authoring contract, not a compiler.
Input shape
Put the chart input beside the table rows and reference it with a chart
widget:
{
"data": {
"sales": {
"type": "table",
"rows": [{"month": "Jan", "revenue": 120}],
"flint": {
"chart_spec": {
"chartType": "Bar Chart",
"title": "Revenue by month",
"encodings": {"x": "month", "y": "revenue"},
"baseSize": {"width": 560, "height": 320},
"canvasSize": {"width": 900, "height": 520}
},
"semantic_types": {"month": "Month", "revenue": "Currency"},
"options": {"addTooltips": true}
}
}
},
"widgets": [{"type": "chart", "data": "sales"}]
}
Rules
- Use inline rows only. Never put secrets, credentials, arbitrary URLs, or executable expressions in the chart input.
- Keep the table bounded: at most 2,000 rows and 64 columns for a chart.
- Use a real Flint template name such as
Bar Chart,Line Chart, orScatter Plot; encodings refer only to fields present in the rows. - Mark important numeric claims with the surrounding Surface evidence/claims fields. A chart is not evidence by itself.
- Preserve the table as the source of truth. The chart is a view over the rows, not a second copy of the dataset.
Verification
The host rejects oversized or malformed input, disallows remote data sources, and reports a renderer error instead of silently showing a blank chart. A successful Desktop/Web render means the input compiled and the Vega renderer completed; it does not verify the underlying data claims.
Provenance
This workflow follows the public Flint Chart authoring contract: https://github.com/microsoft/flint-chart/blob/main/agent-skills/flint-chart-author/SKILL.md
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.
- 4d ago First seen · 63 lines · 16 tokens per session scan A 61bd6d835d6d
author is a skill published in the GitHub repository agentlas-ai/agentlas-desktop (5 stars, last pushed yesterday), licensed Apache-2.0. It adds 16 tokens to every session and 510 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 2026-08-31.
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