common-skill-creator
Tool for auditing and creating high-quality agent skills.
Install
mkdir -p .claude/skills/common-skill-creator && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/12740" && unzip -o skill.zip -d .claude/skills/common-skill-creator && rm skill.zipInstalls to .claude/skills/common-skill-creator
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Standardizes the creation and evaluation of high-density Agent Skills (Claude, Cursor, Windsurf). Ensures skills achieve high Activation (specificity/completeness) and Implementation (conciseness/actionability) scores. Use when: writing or auditing SKILL.md, improving trigger accuracy, or refactoring skills to reduce redundancy and maximize token ROI.Key capabilities
- →Draft SKILL.md using a template
- →Test skills with parallel subagents
- →Evaluate skill performance and token usage
- →Optimize skill description for trigger accuracy
- →Audit existing skills against quality checklist
- →Improve SKILL.md by fixing violations and compressing content
How it works
This skill provides a structured workflow for creating and refining agent skills, focusing on specificity, conciseness, and test-driven evaluation.
Inputs & outputs
When to use common-skill-creator
- →Optimizing a new skill
- →Auditing skill trigger accuracy
- →Refactoring existing skill documentation
About this skill
Agent Skill Creator Standard
Priority: P0 (CRITICAL)
Applies to every skill in this registry. Maximize Token ROI. Every line in SKILL.md must provide specific procedural value. Activation (how it triggers) and Implementation (how it helps) primary quality metrics.
Three-Level Loading System
- Level 1 Frontmatter:
name+description(Activation Anchor), ≤100 words. - Level 2 SKILL.md body: Core Rules + Workflows (Implementation Core), ≤100 lines.
- Level 3 references/: Detailed examples, schemas, and "TESTS.md" (On-demand).
Workflow (New or Existing Skill)
New skill:
- Research — web-search domain best practices, checklists, and standards; extract key terms → triggers, workflows → guidelines, mistakes → anti-patterns. See Web Search Research.
- Capture intent — what it , when it trigger, expected output format?
- Draft the SKILL.md — draft using TEMPLATE.md
- Test — spawn parallel subagents: one with-skill, one without-skill (baseline)
- Evaluate — grade assertions, review benchmark (pass rate, tokens, time)
- Iterate — rewrite based on feedback, rerun into next iteration dir, repeat
- Optimize description — run trigger eval queries, target ≥80% accuracy
- Pressure-test — for discipline skills, capture agent excuses, red flags, and stop conditions Existing skill:
- Audit — run Quality Checklist below; identify violations
- Snapshot —
cp -r <skill-dir> <workspace>/skill-snapshot/before any edits - Improve SKILL.md — fix violations, compress, move oversized content to
references/ - Test — spawn parallel subagents: one with-new-skill, one with-snapshot (baseline)
- Evaluate & iterate — same as steps 4–5 above
- Optimize description — re-run trigger eval if description changed
- Harden — add rationalization counters where agents still fail under pressure See Eval Workflow for full testing + iteration details.
Description Quality (Activation)
- Third-Person Voice: Use
Standardizes...,Audits...,Encrypts.... Avoid "I will" or "This skill helps to". - What + When Structure:
- What: Define 5–8 specific capabilities (e.g., "Generates JWT tokens, rotates keys").
- When: Explicitly define triggers (e.g., "Use when user says 'rotate keys'").
- Specificity: Avoid vague verbs like "manage" or "handle". Use "Validate", "Inject", "Refactor", "Sanitize".
- Trigger Hint: Include
(triggers: *.ext, keyword)suffix for technical skills.
Content Quality (Implementation)
- No Redundant Knowledge: NOT explain concepts AI already knows (e.g., HTTP status codes, standard library docs, basic SOLID principles). Focus strictly on project-specific rules.
- Caveman Compression: Use "Caveman Mode" for rules to save tokens. Drop articles (, , ), remove filler words ("should", "will", "), and use telegraphic snippets.
- Standard: "You should ensure that database connection closed after every query to prevent leaks." (15 tokens)
- Caveman: "Close DB connection after query. Prevent leaks." (7 tokens)
- Actionability: Examples must copy-paste ready and executable.
- Workflow Clarity: Use sequential ordered lists for multi-step processes.
- Progressive Disclosure: Move code blocks >10 lines to
references/. - Pressure Hardening: Discipline skills must name red flags, common excuses, and exact stop/restart conditions.
Behavior Guardrails
- Use pressure tests for discipline skills: TDD, debugging, verification, review, protocol, and workflow skills need baseline failure evidence.
- Capture rationalizations: Save the exact excuses agents use when they skip the rule.
- Add red flags: Short phrases that tell the agent to stop and restart the protocol.
- Encode behavior in evals: Add
pressure_scenarios,rationalizations,red_flags, andbehavior_assertionswhen the skill is guardrail-oriented. - Keep it local: Put behavior details in evals or
references/; keepSKILL.mdcompact.
Anti-Patterns
- No "AI-splaining": not explain why pattern good unless it's unique project constraint.
- No Vague Triggers: Never use
src/**or**/*. surgical. - No Description Bloat: If description exceeds 100 words, some capabilities belong in body.
- No long code blocks: >10 lines → extract to
references/ - No redundancy: don't repeat frontmatter content in body
- No untested guardrails: Rules that were never pressure-tested are speculation.
Quality Checklist (Tessl-Aligned)
- Activation ≥ 90%: Description covers both capabilities ("What") and triggers ("When").
- Implementation ≥ 90%: No general-purpose explanations; all examples executable.
- Structural Compliance: SKILL.md ≤ 100 lines; code blocks moved to
references/. - Trigger rate ≥80% on should-trigger queries.
- Guardrail skills include rationalizations, red flags, behavior eval fields, and
should_trigger/should_not_triggercases.
References
- Skill Template — load when starting new skill from scratch
- Anti-Patterns Detail — load when fixing or reviewing anti-pattern format
- Size & Limits — load when SKILL.md approaches 100 lines
- Resource Organization — load when deciding where to place content (scripts/, references/, assets/)
- Testing & Trigger Rate — load when writing evals or measuring trigger rate
- Eval Workflow — load when running parallel subagent tests
- Full Lifecycle — load for complete phase-by-phase creation guide
- Web Search Research — load when creating skill for unfamiliar or non-engineering domain
When not to use it
- →When explaining concepts the AI already knows
- →When using vague verbs like 'manage' or 'handle'
- →When using vague triggers like 'src/**' or '**/*'
Limitations
- →Does not explain concepts AI already knows
- →Does not permit vague verbs in descriptions
- →Does not permit vague trigger patterns
How it compares
This workflow uses a standardized, iterative process with parallel testing and specific quality metrics to ensure high-density and actionable skills, unlike ad-hoc skill creation.
Compared to similar skills
common-skill-creator side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| common-skill-creator (this skill) | 0 | 1mo | No flags | Intermediate |
| prompt-optimize | 13 | 9mo | No flags | Advanced |
| ai-cost-optimizer | 9 | 5mo | Caution | Intermediate |
| self-improving-agent | 12 | 1mo | Review | Intermediate |
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