LangAlpha is an agent workspace for researching financial markets and supporting investment decisions through persistent research, news analysis, and parallel subagents. It is for investors who want to develop and update trading theses over time, including generating long-short pair-trade ideas. The catalogue entries provide the skills, instructions, MCP servers, and plugin that make up its agent workflow.
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 ginlix-ai/LangAlpha --skill interactive-dashboardgit clone --depth 1 https://github.com/ginlix-ai/LangAlphaWrote 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/ginlix-ai/langalpha/interactive-dashboard)<a href="https://agentmods.dev/skills/ginlix-ai/langalpha/interactive-dashboard"><img src="https://agentmods.dev/badge/skills/ginlix-ai/langalpha/interactive-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/ginlix-ai/langalpha/interactive-dashboard"><img src="https://agentmods.dev/badge/skills/ginlix-ai/langalpha/interactive-dashboard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to high
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 →
- high Privilege Escalation · line 515 Potential security issue detected. Manual review is recommended.Fix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
- high Privilege Escalation · line 646 Potential security issue detected. Manual review is recommended.Fix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
- medium Agent Snooping · line 366 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.
- medium Agent Snooping · line 21 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 | $0.00021 | $0.08679 |
| Opus 5.5 | $0.00008 | $0.03472 |
| Sonnet 5.5 | $0.00004 | $0.01736 |
| Haiku 4.5 | $0.00002 | $0.00868 |
Grade A, and why
interactive-dashboard scanned grade A with 2 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 28d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
for i in $(seq 1 15); do curl -sf http://127.0.0.1:8050/ > /dev/null && echo "Server ready" && exit 0 || sleep 1; done; echo "FAIL"; exit 1 Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
result = subprocess.run( How it starts
The opening of the file, as written. The whole thing — 685 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Interactive Dashboard
Build interactive web dashboards inside the sandbox and expose them to the user via GetPreviewUrl. Use this skill for any request involving dashboards, trackers, monitors, live visualizations, or interactive web apps.
When to Use
Use this skill for a live, served web app — one that needs a running server, not a single file:
- User asks for a dashboard, tracker, or monitor that refreshes live data (polling, auto-update)
- The app needs server-side logic — filtering/screening over a large dataset, on-demand fetches, computed endpoints
- Multi-page / routed apps, or anything that needs React-level component interactivity
- The dataset is too large to embed in a single HTML file
- User explicitly says "preview", "web view", "web app", or wants it running at a URL
Do NOT use if:
- User wants a self-contained HTML report — even an interactive one (sortable tables, tabs, hover/zoom charts) over a data snapshot. That's
.agents/skills/html-report/SKILL.md: one file in the task directory, keepable, printable, PDF-exportable, share-linkable. Interactivity by itself does not require a dashboard. - User wants a static chart image → matplotlib/plotly
savefig. - User wants an in-chat figure →
inline-widget(ShowWidget).
Dashboard vs. HTML Report
Both can be interactive, so the divide is live served app vs. self-contained snapshot file, not static vs. interactive:
| interactive-dashboard (this skill) | html-report | |
|---|---|---|
| Delivery | A running server, exposed via GetPreviewUrl |
One .html file in <task_name>/ |
| Data | Live / refreshing, fetched from a backend; large datasets OK | A snapshot embedded in the file |
| Interactivity | Full app — routing, server-side filtering, live updates | Client-side over the snapshot — sort, filter, tabs, chart hover/zoom |
| Keep / print / share | A URL, live only while the workspace runs | Downloadable, PDF-exportable, share-linkable as one artifact |
| Pick when | Data must be live, or compute/scale needs a server | The answer is a deliverable the user keeps |
What ships with it
10 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.
- references/chart-patterns.md 56 KB
- references/Dockerfile 770 B
- references/Dockerfile.fastapi-html 408 B
- references/requirements.txt 26 B
- references/server-main.fastapi-html.py 716 B runs code
- references/server-main.py 1.3 KB runs code
- references/start.sh 1001 B runs code
- references/ui-components.md 32 KB
- references/verification.md 3.7 KB
- references/vite.config.js 285 B runs code
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.
- 28d ago Changed 7027d0ab0580
- 1mo ago Changed d99563723d61
- 1mo ago Changed bf4a3f3c9309
- 1mo ago First seen · 685 lines · 21 tokens per session scan A 542a6c878179
interactive-dashboard is a skill published in the GitHub repository ginlix-ai/LangAlpha (1,826 stars, last pushed today), licensed Apache-2.0. It adds 21 tokens to every session and 8,679 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 2 findings (makes network calls, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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