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 + body + references/ + scripts/ + assets/), the "pushy description" trigger pattern, the three-level progressive-disclosure model, and the validate-fix-rerun feedback loop. Use when creating a new skill in this repo, when reviewing a skill PR, when a skill's Tessl review score is below 75 (the merge gate), when a skill's description isn't getting picked up by agents, when restructuring a long SKILL.md into a bundle, or when the user asks how to write, improve, optimize, audit, or fix a skill - even if they don't say "skill" explicitly (e.g. "this isn't triggering", "Tessl scored this 72", "split this doc").
Works with
--- name: skill-authoring description: 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 + body + references/ + scripts/ + assets/), the "pushy description" trigger pattern, the three-level progressive-disclosure model, and the validate-fix-rerun feedback loop. Use when creating a new skill in this repo, when reviewing a skill PR, when a skill's Tessl review score is below 75 (the merge gate), when a skill's description isn't getting picked up by agents, when restructuring a long SKILL.md into a bundle, or when the user asks how to write, improve, optimize, audit, or fix a skill - even if they don't say "skill" explicitly (e.g. "this isn't triggering", "Tessl scored this 72", "split this doc"). license: Apache-2.0 --- # 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) 1. **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](references/descriptions.md) for the pushy-description pattern that combats undertriggering. 2. **Body under 500 lines** — split into `references/*.md` if approaching the limit. SKILL.md is the routing layer, not the entire knowledge base. 3. **One level of nesting for references** — link from SKILL.md directly, never `SKILL.md → a.md → b.md`. Claude may use `head -100` previews on nested chains and miss content. 4. **Imperative voice** — "Run X" not "You should run X" not "It is important to run X". Explain *why* over heavy-handed `MUST` markers. 5. **Concrete examples beat prose** — copy-paste-ready commands, real config snippets. Tessl's `actionability` dimension scores this directly. 6. **No reserved words in `name`** — `anthropic` and `claude` are forbidden in skill names. 7. **No time-sensitive language in the body** — "after August 2025…" rots. Use an `<details>` "Old patterns" section for legacy info instead. 8. **Validate before committing** — `./scripts/lint-skills.sh skills/<plugin>/<your-skill>` clean + Tessl score ≥75 (run `tessl 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](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 1. **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 three `marketplace.json` files). 2. **Estimate body length.** - <200 lines of substance → single `SKILL.md`, no bundle - 200-500 lines → `SKILL.md` + `references/<topic>.md` for the long-form material - >500 lines → mandatory bundle split; see [references/anatomy.md § Splitting strategies](references/anatomy.md#splitting-strategies) 3. **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](references/descriptions.md) for the pattern. 4. **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 in `references/` instead (Progressive disclosure) 5. **Register in marketplace manifests.** Add the skill path to the `skills` array in all three: - `.claude-plugin/marketplace.json` - `.cursor-plugin/marketplace.json` - `.agents-plugin/marketplace.json` 6. **Validate locally.** ```bash # 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 1. Read the judge's verbatim Suggestions text (non-JSON output): ```bash 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. 2. Apply the fix pattern from [references/rubric.md](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` 3. If the skill is **intentionally a routing document** (like `grafana-k6/k6-docs`), don't let `--optimize` inline 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. 4. 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/anti-patterns.md). ## References - [`references/descriptions.md`](references/descriptions.md) — the pushy-description pattern + trigger-term checklist - [`references/rubric.md`](references/rubric.md) — per-dimension scoring with Anthropic-doc citations and concrete fix patterns - [`references/anatomy.md`](references/anatomy.md) — three-level progressive disclosure, bundle layout, splitting strategies - [`references/anti-patterns.md`](references/anti-patterns.md) — what NOT to do, with examples - [Anthropic — Agent Skills best practices](https://platform.claude.com/docs/en/agents-and-tools/agent-skills/best-practices) - [anthropics/skills — skill-creator SKILL.md](https://github.com/anthropics/skills/blob/main/skills/skill-creator/SKILL.md) - [The Complete Guide to Building Skills for Claude (PDF)](https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf)
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