lyndonkl/claude/skill-construction
- community
Checking that the SKILL.md file is still in the repository.
Methodology for building a properly structured Claude Code skill (SKILL.md + optional resources + evaluation rubric) from extracted components. Assesses complexity (Level 1 simple - SKILL.md only; Level 2 moderate - SKILL.md plus 1-3 resources; Level 3 complex - SKILL.md plus 4-8 resources), plans the resource grouping, drafts SKILL.md following Anthropic's authoring best practices (concise frontmatter with what + when triggers, body under 500 lines, progressive disclosure to resource files one level deep, workflow checklists), and constructs an evaluation rubric. Use when extracted components and a synthesis verdict are in hand and the next step is to materialize them as a skill. Trigger keywords - construct skill, build SKILL.md, skill construction, skill scaffolding, generate skill files.
Install
npx vskill@latest install lyndonkl/claude/skill-constructionSKILL.md
skill-construction
Builds a Claude Code skill (the SKILL.md file plus any resource files and the evaluation rubric) from a structured set of extracted components and a synthesis verdict. The penultimate step in the skill-creator workflow.
The skill is invoked by the calling agent (typically the skill-creator agent) once synthesis-application has produced a GO or GO_WITH_GAPS verdict on the extracted components. NO_GO sends the agent back upstream.
Workflow
Inputs
extracted_components: structured terms / propositions / arguments / solutions fromcomponent-extractionsynthesis_output: the GO / GO_WITH_GAPS verdict fromsynthesis-applicationplus its gap-fill recommendationstarget_dir: where the skill should be written (typicallyskills/{skill-name}/)purpose_context: e.g.,skill_extraction_from_methodology(the standard case)
Complexity levels
Match structure to content volume. Don't over-engineer; don't under-engineer.
| Level | Steps in workflow | Estimated lines total | Structure | |
|---|---|---|---|---|
| 1 | 3-5 | < 300 | SKILL.md + rubric only | |
| 2 | 5-8 | 300-800 | SKILL.md + 1-3 resource files + rubric | |
| 3 | 8+ | 800+ | SKILL.md + 4-8 resource files + rubric |
Decide based on:
- Total workflow steps the methodology has
- Major decision points (each typically warrants a section)
- Number of distinct concepts that need explanation
- Examples needed (more examples → more lines → likely Level 2 or 3)
SKILL.md structure (always required)
YAML frontmatter:
name: lowercase-hyphens, ≤64 chars, no XML, no reserved words ("anthropic", "claude")description: third-person, both what the skill does AND when to use it, including trigger keywords. ≤1024 chars. This is the discovery surface — Claude uses it to decide whether to invoke the skill.
Body sections (typical order):
# {Skill Name}— title + one-paragraph framing## Workflow— checklist the calling agent can copy## {Domain-specific sections}— patterns, decision logic, key concepts## Common patterns— 2-4 named patterns with usage context## Guardrails— must-nots and anti-patterns## Related— pointers to adjacent skills (one level deep only)
Resource file structure (Level 2 and 3)
Each resource file:
- Focused on one cohesive topic (don't sprawl)
- < 500 lines
- Cross-referenced from SKILL.md as a one-level-deep link
- Follows a
## Why Xthen## What to dostructure (the WHY activates context; the WHAT gives concrete instructions)
Two grouping approaches:
- By workflow step (best for complex skills) — one resource file per major step, named for the step
- By topic (best for moderate skills) —
key-concepts.md,decision-framework.md,examples.md
Evaluation rubric
Always include resources/evaluators/rubric_{skill_name}.json. 10 criteria, each scored 1-5. Common criteria:
- Description specificity (third person, what + when, triggers)
- Workflow completeness (all major steps captured)
- Pattern coverage (common cases addressed)
- Guardrail clarity (must-nots are concrete)
- Example quality (examples are concrete, not abstract)
- Resource organization (files focused, one-level-deep links)
- Token efficiency (no over-explanation; assumes Claude is smart)
- Consistency (terminology stable; format matches across sections)
- Triggers explicit (key phrases listed in description)
- Tested (at least one real-world test case considered)
Target average ≥ 3.5 before shipping.
Output structure
Anchoring against authoring best practices
Conform to Anthropic's agent skills authoring best practices:
- Concise is key. Only add context Claude doesn't already have. Challenge each piece: "does Claude need this explanation?"
- Set appropriate degrees of freedom. High freedom (text instructions) for judgment calls; low freedom (specific scripts) for fragile procedures.
- Keep references one level deep. SKILL.md links directly to resource files; resources don't link to other resources.
- Workflow checklists for complex tasks. Calling agent can copy and check off as it progresses.
- Feedback loops. Validator → fix errors → repeat.
- Avoid Windows-style paths. Forward slashes always.
- Avoid offering too many options. One default with an escape hatch beats five alternatives.
- MCP tools use fully qualified names.
ServerName:tool_name.
Common patterns
Pattern A — From a methodology document (the standard skill-creation case)
The extracted components come from a methodology guide or framework doc. Workflow steps in SKILL.md mirror the methodology's steps. Resources cover decision logic, examples, and templates.
Pattern B — From a research paper
Less common but valid. The extraction yields propositions and arguments more than steps. SKILL.md becomes a "how to apply this paper's framework to a downstream task" guide. Resources cover the paper's framework and worked examples.
Pattern C — Refactoring an existing skill
The "extracted components" come from an existing skill that's grown too large or has overlap with another. The construction step writes a leaner version, deferring resources to focused files.
Guardrails
- Don't construct without a GO verdict. If
synthesis-applicationreturned NO_GO, return upstream — building a skill from incomplete components is wasted work. - Don't exceed 500 lines in SKILL.md body. Push depth into resource files.
- Don't skip the rubric. Self-evaluation gates ship-readiness; without a rubric there's no objective standard.
- Don't over-engineer. A 3-step methodology is Level 1 — don't build it as Level 3 because resources feel "more professional."
- Don't use Anthropic's reserved words in `name`. "claude", "anthropic" — silently breaks discovery.
- Don't claim test coverage you don't have. The rubric's "Tested" criterion is a real check; mark it 1 if no test scenario was considered.
Related
- `component-extraction` — produces the input this skill consumes.
- `synthesis-application` — runs immediately before this skill; its GO / GO_WITH_GAPS / NO_GO verdict gates this skill's invocation.
- `evaluation-rubrics` — the rubric construction in this skill's Step 6 mirrors the rubric design patterns there.
- The skill-creator skill at
skills/skill-creator/SKILL.mdinvokes this skill as its Step 5.
Security
- Security scanPassed, 95 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/skill-construction/SKILL.md
Popularity
- Repository stars
- 155
- Repository forks
- 23
- 7-day trend score
- 25
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 7 Sep 2026, a month ago.
Works with
Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.
- Claude Code
- Cursor
- GitHub Copilot
- Windsurf
- Codex
- Gemini CLI
- Cline
- Amp
- Roo Code
- Goose
- Continue
- Kilo Code
- Junie
- Trae
- OpenHands
- Qwen Code
- AI Agent
- Tabnine Chat
- Sourcegraph Cody
- Amazon Q
- Firebase Genkit
- Sweep
- Devin
- Phind
- Mentat
- Claude Desktop
- Aider
- GPT Pilot
- Plandex
- bolt.new
- v0
- Replit Agent
- Anse
- TypingMind
- BetterChatGPT
- LibreChat
- Warp AI
- Pieces
- Fig AI
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