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/fmschulz/omics-skills/plotly-dashboard-skillnpx skills add fmschulz/omics-skills --skill plotly-dashboard-skillgit clone --depth 1 https://github.com/fmschulz/omics-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/fmschulz/omics-skills/plotly-dashboard-skill)<a href="https://agentmods.dev/skills/fmschulz/omics-skills/plotly-dashboard-skill"><img src="https://agentmods.dev/badge/skills/fmschulz/omics-skills/plotly-dashboard-skill.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 | $0.00031 | $0.00435 |
| Opus 5 | $0.00015 | $0.00217 |
| Sonnet 5 | $0.00006 | $0.00087 |
| Haiku 4.5 | $0.00003 | $0.00044 |
Grade A, and why
plotly-dashboard-skill 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
Plotly Dashboard Skill
Create interactive dashboards with a single source of truth for UI and figure styling.
Instructions
- Capture audience, questions, and data constraints.
- Pick a layout pattern and component library.
- Define a theme and Plotly figure template.
- Build the layout skeleton before callbacks.
- Implement callbacks with clear inputs/outputs.
- Optimize slow callbacks with caching or pre-aggregation.
Quick Reference
| Task | Action |
|---|---|
| UI style guide | See STYLE_GUIDE.md |
| Figure template | See FIGURE_STYLE.md |
| Palettes | See PALETTES.md |
| App architecture | See DASH_ARCHITECTURE.md |
| Performance | See PERFORMANCE.md |
| Copyable app patterns | See EXAMPLES.md |
| Runnable smoke app | Runnable app |
| Definition of done | QA checklist |
Input Requirements
- Audience and key decisions
- Data sources and update cadence
- Required filters and views
- Deployment constraints
Output
- Dash app scaffold (layout + callbacks)
- Consistent theming and figure templates
- README with usage notes
Quality Gates
- Layout communicates hierarchy and intent
- Callbacks are small and focused
- p95 interaction latency acceptable
- Styling is consistent across charts
-
uv run --script examples/app.py --smokereturns HTTP 200 and its measured pure-callback p95 is within the declared latency budget (300 ms by default).
Examples
Example 1: Layout-first workflow
Header + filters + KPI row + primary trends + breakdown table
Troubleshooting
Issue: Slow callbacks Solution: Cache expensive steps or pre-aggregate data.
What ships with it
8 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.
- 4d ago First seen · 65 lines · 31 tokens per session scan A 2561b4a9f80c
plotly-dashboard-skill is a skill published in the GitHub repository fmschulz/omics-skills (7 stars, last pushed 9d ago), licensed MIT. It adds 31 tokens to every session and 435 once invoked, about $0.0002 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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