Agent skill · design visual · axiomhq
building-dashboards
Designs and builds Axiom dashboards via API. Covers chart types, APL and metrics/MPL query patterns, SmartFilters, layout, and configuration options. Use when creating dashboards, migrating from Splunk, or configuring chart options.
Why this skill is useful
Provides specific Axiom dashboard design patterns and API usage that the AI wouldn't reliably generate on its own.
What it needs
Requires axiom-cli installed locally. About 10k tokens when loaded. Last updated 2026-07-14. 14 stars on the source repository.
What this skill does
Building Dashboards Philosophy 1. Decisions first. Every panel answers a question that leads to an action. 2. Overview → drilldown → evidence. Start broad, narrow on click/filter, end with raw logs. 3. Rates and percentiles over averages. Averages hide problems; p95/p99 expose them. 4. Simple beats dense. One question per panel. No chart junk. 5. Validate with data. Never guess fields—discover schema first. 6. Compute what's asked, or defer. If a panel can't be computed, replace it with a Note documenting the blocker. Never substitute a different quantity, even disclosed. See Compute or Defer. --- Entry Points Starting from Workflow --------------- ---------- Vague description Intake → check dataset kind → design blueprint (APL or MPL) → queries per panel → deploy Template Pick template → customize dataset/service/env → deploy Splunk dashboard Extract SPL → translate via spl-to-apl → map to chart types → deploy Grafana dashboard Project canonical panel spec (expr, legendFormat, unit, title, description) → translate PromQL → map chart types → deploy. See reference/grafana-migration.md. Exploration Use axiom-sre to discover schema/signals → productize into panels --- Intake: What to Ask First 1. Audience & decision Oncall triage? (fast refresh, error-focused) Team health? (daily trends, SLO tracking) Exec reporting? (weekly summaries, high-level) 2. Scope Service, environment, region, cluster, endpoint? Single service or cross-service view? 3. Dataset kind. Run scripts/metrics/datasets <deploy> and check kind. otel:metrics:v1 → metrics dataset, follow the Metrics path. anything else → events/logs dataset, follow the APL path. Never run getschema on a metrics dataset. It returns 0 rows without error. APL path: discover fields with ['dataset'] where time between (ago(1h) .. now()) getschema. Continue to steps 4–5. Metrics path: scripts/metrics/metrics-spec <deploy> <dataset> — required before any MPL query. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills axiomhq/building-dashboards