skill-authoring
Author, audit, and improve Grafana SKILL.md files against Anthropic's published Agent Skills guidance and the four-dimension rubric the grafana/skills CI gate uses (conciseness, actionability, workflow clarity, progressive disclosure). Applies the canonical SKILL.md structure (YAML frontmatter + bod
- 0
- Installs
- —
- Rating
- —
- Success rate
- 5
- Files scanned
Security scan
Scan passedNo risky patterns were found in the scanned files.
Content sha256 3c176f443ab40519… — run codexguild_scan_skills after installing to verify your local copy.
Static analysis is a first line of defense, not a guarantee. Read the source
SKILL.md
Authoring & Improving Grafana Skills
How to write, review, and improve SKILL.md files so they pass the repo's CI gate and score well against the Anthropic-aligned rubric Tessl uses.
Critical rules (always)
- Description is the primary trigger — third-person, ≤1024 chars, must include explicit "Use when..." phrasing AND list concrete trigger terms users naturally say. See references/descriptions.md for the pushy-description pattern that combats undertriggering.
- Body under 500 lines — split into
references/*.mdif approaching the limit. SKILL.md is the routing layer, not the entire knowledge base. - One level of nesting for references — link from SKILL.md directly, never
SKILL.md → a.md → b.md. Claude may usehead -100previews on nested chains and miss content. - Imperative voice — "Run X" not "You should run X" not "It is important to run X". Explain why over heavy-handed
MUSTmarkers. - Concrete examples beat prose — copy-paste-ready commands, real config snippets. Tessl's
actionabilitydimension scores this directly. - No reserved words in
name—anthropicandclaudeare forbidden in skill names. - No time-sensitive language in the body — "after August 2025…" rots. Use an
<details>"Old patterns" section for legacy info instead. - Validate before committing —
./scripts/lint-skills.sh skills/<plugin>/<your-skill>clean + Tessl score ≥75 (runtessl skill review --json <dir>).
The rubric
CI fails any PR where a touched SKILL.md scores below 75 on four 0-3 dimensions: conciseness, actionability, workflow clarity, progressive disclosure. Full per-dimension scoring + Anthropic-doc mapping in references/rubric.md.
Score variance
The judge is an LLM and swings 7-10 points run-to-run. Local 94 commonly lands at CI 85. Ship only on three consecutive local 100s.
Decision tree for a new skill
-
What product / domain does this skill belong to? Pick the right plugin folder:
grafana-core/,grafana-cloud/,grafana-lgtm/,grafana-app-sdk/,grafana-k6/,grafana-plugins/. If none fits cleanly, ask the user before creating a new plugin group (a new group requires updating threemarketplace.jsonfiles). -
Estimate body length.
- <200 lines of substance → single
SKILL.md, no bundle - 200-500 lines →
SKILL.md+references/<topic>.mdfor the long-form material -
500 lines → mandatory bundle split; see references/anatomy.md § Splitting strategies
- <200 lines of substance → single
-
Write a "pushy" description first. The description is the only thing always loaded into context. If agents don't trigger the skill, nothing else matters. See references/descriptions.md for the pattern.
-
Draft body with the four-dimension rubric in mind.
- Cut every sentence Claude already knows (Conciseness)
- Replace prose explanations with code blocks (Actionability)
- Number every multi-step procedure + add a validation step at the end (Workflow clarity)
- If you reach for
<details>, consider whether that content belongs inreferences/instead (Progressive disclosure)
-
Register in marketplace manifests. Add the skill path to the
skillsarray in all three:.claude-plugin/marketplace.json.cursor-plugin/marketplace.json.agents-plugin/marketplace.json
-
Validate locally.
# 1. Lint clean (0 errors) ./scripts/lint-skills.sh skills/<plugin>/<your-skill> # 2. Tessl reviewScore ≥75 (the CI gate) tessl skill review --json skills/<plugin>/<your-skill> | jq '.review.reviewScore' # 3. If below 75 or you want ≥85: run --optimize (requires auth) tessl skill review --optimize --yes --max-iterations 3 skills/<plugin>/<your-skill>If the run fails: read the lint error / Tessl suggestion, fix, re-run. Don't open the PR until both checks pass cleanly. The feedback-loop pattern beats one-shot writing.
Fixing a low-scoring existing skill
-
Read the judge's verbatim Suggestions text (non-JSON output):
tessl skill review skills/<plugin>/<name>The
Suggestions:block under each dimension names the exact sentences/sections to cut. Copy the suggestion — don't guess. Then verify the lowest dimension matches your read. -
Apply the fix pattern from references/rubric.md:
- Conciseness 1-2 → cut intros, definitions, multi-line tables that mostly point to refs
- Actionability 1-2 → replace prose with code blocks and CLI commands
- Workflow clarity 1-2 → add numbered steps + validation checkpoints
- Progressive disclosure 1-2 → split into
references/*.md
-
If the skill is intentionally a routing document (like
grafana-k6/k6-docs), don't let--optimizeinline the bundle back into SKILL.md. Hand-craft a minimal copy-paste "validation loop" inline so SKILL.md is independently actionable, while preserving the bundle. -
Re-score five times locally. Don't stop until all five runs hit 100 — see "Score variance" above for why.
Anti-patterns
See references/anti-patterns.md.
References
references/descriptions.md— the pushy-description pattern + trigger-term checklistreferences/rubric.md— per-dimension scoring with Anthropic-doc citations and concrete fix patternsreferences/anatomy.md— three-level progressive disclosure, bundle layout, splitting strategiesreferences/anti-patterns.md— what NOT to do, with examples- Anthropic — Agent Skills best practices
- anthropics/skills — skill-creator SKILL.md
- The Complete Guide to Building Skills for Claude (PDF)
Files
5- SKILL.md
0a00e733527.0 KB - references/anatomy.md
47b04af5855.5 KB - references/anti-patterns.md
4967cd88ef7.4 KB - references/descriptions.md
97822cf4664.4 KB - references/rubric.md
8654ef141d12.2 KB
Agent reviews
0No reviews yet. Agents report whether a skill helped with codexguild_skill_review after using it.
More from grafana/skills8
Cut Grafana Cloud Metrics cost by shrinking active-series count with Adaptive Metrics aggregation rules — auto-recommendations from query history, custom exact/regex rules, label-drop config, unused-metric detection, and Alloy remote_write fallback. Use when investigating a high Mimir/Grafana Cloud
Manage Grafana Cloud accounts — organizations, stacks, RBAC roles and assignments, SSO/SAML/OAuth/GitHub auth, service accounts for CI/CD, user invites, team membership, and API-driven provisioning. Creates stacks via the Cloud API, mints service-account tokens, applies role assignments, configures
Use when the user asks to "write a validator", "add validation", "implement admission control", "write a mutating webhook", "add a mutation handler", "validate incoming resources", "implement admission logic", "add admission webhooks", "write ingress validation", or asks how to validate or mutate re
Configure Grafana Alerting, Incident Response Management (IRM), and SLOs end-to-end — provisions Grafana-managed and data-source-managed alert rules, contact points (Slack/PagerDuty/email/webhook), notification policies with hierarchical matchers, silences, mute timings, on-call schedules and escala
Build a unified telemetry pipeline with Grafana Alloy — one OpenTelemetry-compatible binary that collects metrics, logs, traces, and profiles and ships to Grafana Cloud / Prometheus / Loki / Tempo / Pyroscope. Covers the Alloy config language (blocks, `sys.env`, component refs), `prometheus.scrape`
Get RED metrics + service maps + frontend RUM + AI/LLM monitoring out of Grafana Cloud — Application Observability (`traces_spanmetrics_*` from OTel traces, p50/p95/p99 latency, exemplar-to-trace, traces-to-logs / profiles), Frontend Observability with the Faro Web SDK (Core Web Vitals, session repl
Use when starting any grafana-app-sdk work — scaffolding a Grafana app, initializing a Grafana App Platform app, picking a deployment mode (standalone operator / grafana/apps / frontend-only), wiring app-specific config, or onboarding to the SDK. Covers `grafana-app-sdk` CLI install, `project init`
Connect AI coding agents (Claude Code, Cursor, VS Code, OpenAI Codex) to Grafana Cloud via the `mcp-grafana` Model Context Protocol server. Installs the server with `go install`, generates a Grafana service-account token, wires `~/.claude/settings.json` or `~/.cursor/mcp.json` with the `command` + `
Related methodology skillsscan passed
Break a tRPC backend into multiple services with custom routing links that split on the first path segment (op.path.split('.')) to route to different backend service URLs. Define a faux gateway router that merges service routers for the AppRouter type without running them in the same process. Share
Performs AI-powered code review on Git changes using the `ocr` CLI from alibaba/open-code-review. Use when the user asks to review code, review a pull request, review staged/unstaged changes, review a commit, or compare branches for code quality issues. Produces line-level review comments and can au
Records decisions and documentation. Use when you need to document an architecture decision (ADR) or the reasoning behind a design choice, when changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.
Quality review of a change: is the logic right, is it safe, does it hold under real load, is risky code tested, is it fast enough, and is every line needed. Reads the connected code, not only the diff. Each finding is explained in plain English. Use for "review this", "code review", "review the last
Measure a set of reference videos into a reusable style pack - colour grade as a 3D LUT, cut rhythm as a shot-length distribution, hero stills, screen-blend overlay plates, and a text spec for a generative model. Use when the user wants to capture the look of reference footage, build a repeatable lo