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 Jamkris/everything-gemini-code --skill dashboard-buildergit clone --depth 1 https://github.com/Jamkris/everything-gemini-codeWrote 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/jamkris/everything-gemini-code/dashboard-builder)<a href="https://agentmods.dev/skills/jamkris/everything-gemini-code/dashboard-builder"><img src="https://agentmods.dev/badge/skills/jamkris/everything-gemini-code/dashboard-builder/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/jamkris/everything-gemini-code/dashboard-builder"><img src="https://agentmods.dev/badge/skills/jamkris/everything-gemini-code/dashboard-builder.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 | $0.00037 | $0.00532 |
| Opus 5 | $0.00018 | $0.00266 |
| Sonnet 5 | $0.00007 | $0.00106 |
| Haiku 4.5 | $0.00004 | $0.00053 |
Grade A, and why
dashboard-builder 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 6d 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.
This is a copy
88% identical to dashboard-builder — 26 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dashboard Builder
Use this when the task is to build a dashboard people can operate from.
The goal is not "show every metric." The goal is to answer:
- is it healthy?
- where is the bottleneck?
- what changed?
- what action should someone take?
When to Use
- "Build a Kafka monitoring dashboard"
- "Create a Grafana dashboard for Elasticsearch"
- "Make a SigNoz dashboard for this service"
- "Turn this metrics list into a real operational dashboard"
Guardrails
- do not start from visual layout; start from operator questions
- do not include every available metric just because it exists
- do not mix health, throughput, and resource panels without structure
- do not ship panels without titles, units, and sane thresholds
Workflow
1. Define the operating questions
Organize around:
- health / availability
- latency / performance
- throughput / volume
- saturation / resources
- service-specific risk
2. Study the target platform schema
Inspect existing dashboards first:
- JSON structure
- query language
- variables
- threshold styling
- section layout
3. Build the minimum useful board
Recommended structure:
- overview
- performance
- resources
- service-specific section
4. Cut vanity panels
Every panel should answer a real question. If it does not, remove it.
Example Panel Sets
Elasticsearch
- cluster health
- shard allocation
- search latency
- indexing rate
- JVM heap / GC
Kafka
- broker count
- under-replicated partitions
- messages in / out
- consumer lag
- disk and network pressure
API gateway / ingress
- request rate
- p50 / p95 / p99 latency
- error rate
- upstream health
- active connections
Quality Checklist
- valid dashboard JSON
- clear section grouping
- titles and units are present
- thresholds/status colors are meaningful
- variables exist for common filters
- default time range and refresh are sensible
- no vanity panels with no operator value
Related Skills
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.
- 6d ago First seen · 109 lines · 37 tokens per session scan A 0e668780a316
dashboard-builder is a skill published in the GitHub repository Jamkris/everything-gemini-code (88 stars, last pushed 3mo ago), licensed MIT. It adds 37 tokens to every session and 532 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to dashboard-builder, differing in 26 lines, and is treated as a copy.
Other skills, from other repositories
codeck
Route explicit requests from a host coding agent to one or more locally configured AI executors through Codeck, attach Markdown or other project files, moderate cross-model consultation, expose disagreements, and synthesize traceable results. Use when the user explicitly names Codeck or asks to consult, compare, or…
scan
Scan your AI coding tool ecosystem — Gemini CLI, Claude Code, Antigravity (Desktop, CLI, IDE), Continue, Windsurf, JetBrains AI, OpenCode. Produces a maturity score, advisory recommendations, and optionally generates reusable SKILL.md files from your conversation patterns. Use when the user asks to audit their…
review-work
Post-implementation review orchestrator. Launches 5 parallel background sub-agents: Oracle (goal/constraint verification), Oracle (code quality), Oracle (security), unspecified-high (hands-on QA execution), unspecified-high (context mining from GitHub/git/Slack/Notion). All must pass for review to pass. MUST USE after…
image-prompt
A Korean-language skill that turns a rough image idea into a detailed prompt for gpt-image-2, OpenAI’s image-generation model.
archify
Create polished, validated architecture, workflow, sequence, data-flow, and lifecycle/state diagrams as explorable standalone HTML with inline SVG, dark/light themes, optional trace motion, and PNG/JPEG/WebP/SVG/WebM export. Accept plain-language requirements or pasted Mermaid flowchart, sequenceDiagram, and…
visual-qa
Rigorous visual QA for any UI you built or changed, across BOTH web/page UIs and TUI/terminal UIs. MUST USE after building or changing any UI to verify it visually before declaring it done. Captures objective reference evidence with a bundled diff script (image-diff for screenshots, tui-check for terminal captures)…