Semiotic is a React library for building data visualizations such as charts, network graphs, streaming displays, and coordinated dashboards. It is used by developers who need to render data-driven interfaces, including with AI coding assistants. Its schemas and MCP server support the catalogue's add-ons for generating chart code.
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 nteract/semiotic --skill semiotic-chartsgit clone --depth 1 https://github.com/nteract/semioticWrote 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/nteract/semiotic/semiotic-charts)<a href="https://agentmods.dev/skills/nteract/semiotic/semiotic-charts"><img src="https://agentmods.dev/badge/skills/nteract/semiotic/semiotic-charts/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/nteract/semiotic/semiotic-charts"><img src="https://agentmods.dev/badge/skills/nteract/semiotic/semiotic-charts.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 7 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 21 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 77 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 141 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 147 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 134 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 137 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium Agent Snooping · line 149 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00064 | $0.02065 |
| Opus 5.5 | $0.00026 | $0.00826 |
| Sonnet 5.5 | $0.00013 | $0.00413 |
| Haiku 4.5 | $0.00006 | $0.00206 |
Grade A, and why
semiotic-charts 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 18d 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 — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generating charts with Semiotic
Semiotic is a React data-visualization library with configuration validation, render evidence, structured access, and artifact revision support. Use this workflow to check the parts of a chart that the task requires. A capability comparison may conclude that the existing stack, a table, or another tool is the better fit; the skill does not authorize adding a dependency or migrating working charts.
The cardinal rule: do not hand-write chart JSX and hope it paints. Emit a
{ component, props } proposal and run it through the trust loop, which is
validated and diagnosed; when a renderer is available, checked for a nonempty
static scene. This does not establish correct data mapping, live browser
behavior, or usability with assistive technology. Check the expected values
and run the browser or reception checks relevant to the task. Failed proposals
return reasons and ranked alternatives to retry with.
Context discipline
Start with the task and the exact component schema. Use the MCP getSchema tool,
read semiotic://schema/{component}, or run
npx -p semiotic semiotic-ai --schema <Component>, then read one nearby example if needed.
Use semiotic://schema-index when the component is not known. Do not load the
full reference, schema, or example catalog by default; retrieve broader context
only when validation or diagnosis shows that it is necessary.
The trust loop — generate → validate → diagnose → repair → prove
prepareChart (from semiotic/ai) composes the whole loop. Call it on every
proposal before you show or stream a chart:
import { prepareChart } from "semiotic/ai"
const result = prepareChart(
{ component: "BarChart", props: { data, categoryAccessor: "region", valueAccessor: "revenue" } },
{ data } // supply the data so a poor chart→data fit is caught and alternatives ranked
)
if (result.ok) {
// result.jsx is a ready JSX string; result.config is the serializable ChartConfig
} else {
// result.reasons explains why; result.repair.alternatives ranks better charts.
// Retry with a fixed prop or a suggested component — do NOT paint.
}
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.
- 18d ago Changed bfe640e15ffb
- 24d ago Changed · +3 lines d22b5220e045
- 1mo ago Changed · +6 lines · -7 tokens per session cfffad3d0b26
- 1mo ago First seen · 160 lines · 71 tokens per session scan A b9c382f8e061
semiotic-charts is a skill published in the GitHub repository nteract/semiotic (2,716 stars, last pushed today), licensed Apache-2.0. It adds 64 tokens to every session and 2,065 once invoked, about $0.0003 per session on Opus 5.5. 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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