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Adds a curated, Pi-native, skills+prompts-only profile at pi/core/ for downstream packagers that mirror GitHub Releases. - manifests/pi-core.json: explicit include lists, per-item exclusion reasons, curation rules, safety allowlists; every root skill and command must be classified. - scripts/build-pi-core.js regenerates pi/core deterministically (package.json from VERSION, LICENSE, README.md, CURATION.md, skills/, commands/); --check fails CI on drift. council is renamed ecc-council inside pi/core only. - Safety checks: no callable endpoints outside the allowlist, no npx/curl|sh/pip install, no secrets, no absolute home paths, no symlinks, valid frontmatter, no duplicate names. - CI: build + drift check and an offline Pi CLI load test of pi/core. - Release: VERSION, package.json and pi/core/package.json at 2.2.2, CHANGELOG, tag-triggered release verification, and a two-week cadence in CONTRIBUTING.md. pi/core: 123 of 293 skills and 24 of 94 commands; 35,006 characters of skill description text.
2.3 KiB
2.3 KiB
name, description, metadata
| name | description | metadata | ||||
|---|---|---|---|---|---|---|
| dashboard-builder | Build monitoring dashboards that answer real operator questions for Grafana, SigNoz, and similar platforms. Use when turning metrics into a working dashboard instead of a vanity board. |
|
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
research-opsbackend-patternsterminal-ops