| name | skill-construction |
| description | 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. |
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
- [ ] Step 1: Assess complexity level (1-3) from extracted content volume
- [ ] Step 2: Plan resource files (or decide SKILL.md alone is enough)
- [ ] Step 3: Draft SKILL.md frontmatter (name, description, triggers)
- [ ] Step 4: Draft SKILL.md body (workflow checklist, key patterns, guardrails)
- [ ] Step 5: Draft each resource file (focused topic, < 500 lines, WHY/WHAT structure)
- [ ] Step 6: Construct an evaluation rubric (10 criteria, 1-5 scale)
- [ ] Step 7: Output the constructed skill files
Inputs
extracted_components: structured terms / propositions / arguments / solutions from component-extraction
synthesis_output: the GO / GO_WITH_GAPS verdict from synthesis-application plus its gap-fill recommendations
target_dir: where the skill should be written (typically skills/{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 X then ## What to do structure (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
## Skill Construction Output
### Complexity assessment
Level: {1 | 2 | 3}
Rationale: {1-2 sentences}
Structure: {file list}
### Files created
- {target_dir}/SKILL.md ({line count} lines)
- {target_dir}/resources/{file}.md ({line count} lines) — {topic}
- ...
- {target_dir}/resources/evaluators/rubric_{name}.json (10 criteria)
### Self-evaluation against the rubric
- Average score: {X / 5}
- Below-3 criteria: {list}
- Recommended next-pass focus: {1-2 specific improvements}
### Gaps from upstream synthesis-application
{If the synthesis verdict was GO_WITH_GAPS, restate the gap list and how the construction addressed each (filled / deferred / surfaced as a TODO in the SKILL).}
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-application returned 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.md invokes this skill as its Step 5.