---

name: skeall description: | Agent Skills (SKILL.md) builder, auditor, and improver for cross-platform LLM agents. Use for "skeall", "build a skill", "create skill", "improve skill", "audit skill", "skill review", or any SKILL.md question. Follows agentskills.io standard.

Skeall

Create, improve, and audit Agent Skills following the Agent Skills open standard. This skill encodes lessons from real-world skill development and cross-platform compatibility testing.

Quick start

/skeall --create              # Interview, then scaffold new skill
/skeall --improve <path>      # Analyze and improve existing skill
/skeall --scan <path>         # Audit only, no changes (report)
/skeall --scan .              # Audit skill in current directory
/skeall --scan-all            # Batch scan all skills in ~/.claude/skills/
/skeall --scan-all <dir>      # Batch scan all skills in custom directory
/skeall --healthcheck <path>  # Runtime check single skill (orphans, deps, env, URLs)
/skeall --healthcheck-all     # Runtime check all skills in ~/.openclaw/skills/
/skeall --healthcheck-all <dir> # Runtime check all skills in custom directory

---

Mode 1: Create (scaffold a new skill)

Process

1. Interview the user (ask questions 1-4 always, then 5-6 if user hasn't already specified complexity or distribution scope):

   • What does this skill do? (one sentence)
   • What category? Reference / Task / MCP Enhancement / Hybrid. See references/advanced-patterns.md
   • What triggers should activate it? (keywords users would type)
   • Does it accept arguments? (e.g., file path, topic — use $ARGUMENTS or $ARGUMENTS[N] in body)
   • How complex is it? (single file vs references/ needed)
   • Will this skill be shared? (personal / project / public) — affects README, license, metadata

2. Generate the skill structure:

{skill-name}/
├── SKILL.md                    # Core instructions (always loaded)
├── references/                 # On-demand detail files
│   ├── {topic-1}.md
│   └── {topic-2}.md
└── README.md                   # GitHub-facing (optional)

1. Write SKILL.md following these rules:

   • YAML frontmatter with name and description (see Frontmatter section)
   • Body under 500 lines, under 5000 tokens
   • Instruction-based framing, not persona-based
   • Progressive disclosure: core in SKILL.md, details in references/

2. Show the generated SKILL.md to user for review.

3. Run --scan on the generated skill. If any HIGH issues found, fix them before delivering.

Next step: "Optimize with reprompter?" (optional, see Reprompter section). Then suggest installing the skill.

---

Mode 2: Improve (refactor existing skill)

Process

1. Read SKILL.md first. Read reference files only if scan identifies issues requiring them (broken links, routing table mismatches).
2. Run the scan checklist (see Mode 3).
3. For each issue found, propose a specific before/after edit.
4. Group edits by priority: HIGH first, then MEDIUM, then LOW.
5. Ask user: "Fix all? Review one by one? Or just the HIGHs?" (recommended: fix all HIGHs automatically, review MEDIUMs)
6. Apply approved edits.
7. Re-scan once. If new issues appear, report them but do not enter an infinite fix loop.

Next step: "Run --scan to verify?" or "Commit changes?"

Common improvements

| Problem | Fix | |---------|-----| | Body over 5000 tokens | Move detail sections to references/ | | Redundant content | Single source of truth, reference elsewhere | | Persona-based framing | Switch to instruction-based framing | | Missing trigger phrases | Add keywords to description field | | Platform-specific patterns | Replace with universal formatting | | No progressive disclosure | Add routing table to reference files |

---

Mode 3: Scan (audit and report)

Process

1. Read the skill's SKILL.md and directory structure.
2. Check every item in the checklist below.
3. Output a severity-tagged report.

Report format

## Skill Audit: {skill-name}

Score: X.X/10

STRUCTURE
  [PASS] S1 -- SKILL.md exists at root
  [FAIL] S3 HIGH -- name does not match directory name
  [WARN] S5 MEDIUM -- No references/ directory

FRONTMATTER
  [PASS] F2 -- Trigger phrases present
  [FAIL] F1 HIGH -- description over 1024 characters

CONTENT
  [WARN] C5 MEDIUM -- Persona-based framing ("You are an expert")
  [FAIL] C3 HIGH -- Same content repeated 3 times (lines 45, 120, 280)

LLM-FRIENDLINESS
  [WARN] L4 MEDIUM -- Unicode arrows instead of markdown tables
  [PASS] L3 -- No emoji markers in headings

SECURITY
  [PASS] SEC1 -- No XML angle brackets in frontmatter
  [PASS] SEC3 -- No hardcoded secrets

CROSS-PLATFORM
  [PASS] X1 -- No {baseDir} placeholders
  [WARN] X4 LOW -- No multi-platform install instructions in README

Total: 3 HIGH | 4 MEDIUM | 1 LOW

Next step after scan: "Want me to fix these? Run /skeall --improve <path>"

Error handling

| Input | Response | |-------|----------| | No SKILL.md found at path | "No skill found at {path}. Did you mean --create?" | | Empty directory for --scan-all | "No skills found in {dir}. Skills must have a SKILL.md file." | | Invalid YAML frontmatter | Report the parse error, suggest fixing frontmatter first | | --improve on non-skill file | "Not a valid skill (no YAML frontmatter). Try --create instead." | | --improve on a skill scoring 10/10 | "Scan found 0 issues (score 10.0/10). No changes needed. Consider running trigger and functional tests." |

---

Agent Skills spec reference

Frontmatter (required)

---
name: my-skill-name
description: What this skill does and when to use it. Include trigger phrases.
---

name rules:

• Must match the parent directory name
• Lowercase alphanumeric with hyphens only (unicode lowercase allowed)
• 1-64 characters, no leading/trailing/consecutive hyphens
• No spaces, no special characters, no reserved words ("anthropic", "claude")
• Recommended: gerund form (processing-pdfs, testing-code) or descriptive noun (pdf-processor)

description rules:

• Explain WHAT it does AND WHEN to use it
• Write in third person ("Processes files", not "I can process" or "You can use")
• Include trigger phrases users would actually type
• Put the most important keyword first (platforms weight first words)
• Spec limit: 1024 characters. Recommended: under 300 for best matching
• Use noun-phrase style ("Guide for X"), not persona style ("Expert in X")
• No XML angle brackets (<, >) in any frontmatter value (injection risk)

Optional frontmatter fields

These are silently ignored by platforms that do not support them:

license: MIT                          # For distributed skills
compatibility: "Node.js 18+"         # Environment requirements (max 500 chars)
metadata:                             # Arbitrary key-value (author, version)
  author: your-name
  version: 1.0.0
allowed-tools: "Bash Read"           # Experimental: space-delimited tool list
user-invocable: true                  # Show in /slash menu (false = hidden but still callable)
disable-model-invocation: true        # Block Claude from auto-loading this skill
argument-hint: "<file-path>"          # Hint shown in /skill autocomplete
model: opus                           # Override model for this skill
context: fork                         # Run in isolated subagent
agent: general-purpose                # Subagent type: general-purpose, Explore, Plan, or custom
hooks:                                # Skill-scoped lifecycle hooks
  PostToolCall: "validate.sh"

Directory structure

skill-name/
├── SKILL.md           # REQUIRED -- core instructions
├── references/        # OPTIONAL -- on-demand detail files
├── scripts/           # OPTIONAL -- executable scripts
├── assets/            # OPTIONAL -- static assets (images, etc.)
└── README.md          # OPTIONAL -- GitHub-facing docs

Token budget

| Level | Content | Budget | |-------|---------|--------| | Metadata (YAML frontmatter) | name + description | ~100 tokens | | Instructions (SKILL.md body) | Always loaded by LLM | < 5000 tokens | | References (each file) | Loaded on demand | ~2000-3000 tokens each |

Estimation: ~1.5 tokens per word for mixed code+prose markdown.

Progressive disclosure: SKILL.md body should handle ~70% of user requests. Reference files handle the remaining 30% (detailed workflows, complete examples, edge cases).

Line limits

| Guideline | Limit | |-----------|-------| | SKILL.md body | Under 500 lines (under 300 for complex skills with many references) | | Reference files | No hard limit, but keep each under 700 lines. Add TOC at top if over 100 lines |

---

Scan checklist

Structure checks

| ID | Severity | Check | |----|----------|-------| | S1 | HIGH | SKILL.md exists at skill root | | S2 | HIGH | YAML frontmatter present with --- delimiters | | S3 | HIGH | name field present and valid (lowercase, hyphens, 1-64 chars, no consecutive hyphens) | | S4 | HIGH | description field present | | S5 | MEDIUM | References in references/ not loose at root | | S6 | LOW | README.md present for GitHub-hosted skills | | S7 | LOW | No unnecessary files (node_modules, .DS_Store, etc.) | | S8 | HIGH | name field matches parent directory name |

Frontmatter checks

| ID | Severity | Check | |----|----------|-------| | F1 | HIGH | Description under 1024 characters (spec limit) | | F1b | LOW | Description under 300 characters (recommended for matching) | | F2 | HIGH | Description includes trigger phrases | | F3 | MEDIUM | Description starts with noun phrase, not "Expert in" | | F4 | MEDIUM | Name 1-64 characters, no leading/trailing/consecutive hyphens | | F5 | LOW | No platform-specific fields (keeps universal compatibility) |

Content checks

| ID | Severity | Check | |----|----------|-------| | C1 | HIGH | Body under 500 lines | | C2 | HIGH | Estimated tokens under 5000 | | C3 | HIGH | No content repeated in SKILL.md body (controlled repetition across reference files is acceptable) | | C4 | HIGH | Code examples use correct, verified patterns | | C5 | MEDIUM | Instruction-based framing (not "You are an expert") | | C6 | MEDIUM | Has routing table to reference files (if references/ exists) | | C7 | MEDIUM | Troubleshooting section present (for skills with code blocks or CLI commands) | | C8 | LOW | No deprecated content at the top (wastes prime token space) | | C9 | MEDIUM | Routing table completeness: if references/ exists, SKILL.md lists ALL files in references/ | | C10 | MEDIUM | Internal count consistency: claimed counts ("34 patterns", "8 phases") match actual content | | C11 | MEDIUM | No stale references: documented APIs, functions, model names exist in actual source |

LLM-friendliness checks

| ID | Severity | Check | |----|----------|-------| | L1 | HIGH | Tables for structured data (not bullet lists with arrows) | | L2 | HIGH | Imperative instructions ("Do X", not "You should consider X") | | L3 | MEDIUM | No emoji as structural markers. Emoji in headings is OK if it serves as a semantic signal (importance, warning) rather than replacing structural markup. Frontmatter metadata values are data, not markers | | L4 | MEDIUM | No Unicode arrows or special characters for data flow | | L5 | MEDIUM | Consistent heading hierarchy (no skipped levels). Ignore headings inside fenced code blocks | | L6 | MEDIUM | Code blocks have language tags | | L7 | LOW | Sentence case headings (not Title Case) | | L8 | LOW | No nested blockquotes (some LLMs parse poorly) |

Security checks

| ID | Severity | Check | |----|----------|-------| | SEC1 | HIGH | No XML angle brackets (<, >) in frontmatter values | | SEC2 | HIGH | Name does not contain reserved words ("anthropic", "claude") | | SEC3 | HIGH | No hardcoded API keys, tokens, or secrets in any skill file | | SEC4 | MEDIUM | Scripts include error handling (not bare commands) | | SEC5 | HIGH | No credential patterns (Bearer eyJ, sk-/pk- prefixes, api_key=/token= + long strings). Ignore $ENV_VAR refs and YOUR_KEY_HERE placeholders |

Cross-platform checks

| ID | Severity | Check | |----|----------|-------| | X1 | HIGH | No {baseDir} placeholders (breaks non-OpenClaw platforms) | | X2 | MEDIUM | Relative paths from SKILL.md to references/ | | X3 | MEDIUM | Internal links use standard markdown [text](path) | | X4 | LOW | README has multi-platform install paths |

Runtime checks (healthcheck mode only)

| ID | Severity | Check | |----|----------|---------| | R1 | HIGH | Orphan skill: not referenced in any config or skill registry | | R2 | HIGH | Duplicate name: same name field found in 2+ skill directories | | R3 | HIGH | Trigger collision: description phrases 80%+ overlap with another skill | | R4 | HIGH | Broken dependency: file referenced in SKILL.md does not exist | | R5 | MEDIUM | Stale endpoint: URL in curl command returns 404 or times out | | R6 | MEDIUM | Missing env var: $VAR reference found but not set in environment | | R7 | LOW | Token cost: estimated tokens loaded per session |

LLM-friendliness patterns

These patterns come from real cross-platform testing. Apply them when creating or improving skills.

Do

• Tables over prose for structured data (parameters, options, comparisons)
• Single source of truth for any concept explained more than once
• Instruction-based framing: "This skill provides instructions for X. Follow these patterns exactly."
• Imperative verbs: "Call X after Y", "Use Z for W"
• Compact routing table at the top pointing to reference files
• Parameter comments inline in code blocks: providerAddress, // 1st: wallet address
• Copyable progress checklists for multi-step workflows (LLM tracks completion)
• Validation feedback loops for quality-sensitive output (generate, score, retry if needed)
• Consistent freedom level per section — do not mix exact scripts with vague guidance. See references/advanced-patterns.md

Do not

• Persona-based framing: "You are an expert in..." (Claude-leaning, other LLMs respond better to instructions)
• Emoji as structural markers (replacing headings, bullets, or section dividers). Emoji used as semantic signals in headings (e.g., ⚠️ for warnings) is acceptable if the heading structure comes from markdown # syntax. Frontmatter metadata emoji is data and always acceptable
• Unicode arrows (→, ←) for data flow — use tables or plain prose
• Blockquote warnings at top of SKILL.md (wastes prime token space, primes distrust)
• "When Users Ask" checklists with 10+ items (bury critical rules, use tables instead)
• Synonym cycling for the same concept (confuses LLMs about whether it's the same thing)
• Repeated content (wastes tokens, risks contradictions if copies drift)
• Assuming exclusive activation (other skills may load simultaneously — declare dependencies explicitly)

Description field optimization

Good description pattern:

{Product/Tool name} guide for {primary use case}. Covers {feature list}.
Use this skill for {trigger phrases separated by commas}.

Example:

description: 0G Compute Network guide for decentralized AI inference and fine-tuning.
  Covers chatbots, image generation, speech-to-text, SDK integration, CLI commands.
  Use this skill for any 0G compute, 0G AI, or decentralized GPU question.

---

Cross-platform compatibility

Universal format (works everywhere)

Only name and description in frontmatter. Standard markdown body. Relative paths. No platform-specific syntax.

Platform discovery paths

| Platform | User-wide | Project | |----------|-----------|---------| | Claude Code | ~/.claude/skills/{name}/ | .claude/skills/{name}/ | | OpenAI Codex | ~/.agents/skills/{name}/ | .agents/skills/{name}/ | | OpenClaw | ~/.openclaw/skills/{name}/ | .openclaw/skills/{name}/ | | Cursor | Standard SKILL.md discovery | Project skills dir | | Gemini CLI | Standard SKILL.md discovery | Project skills dir |

Codex-specific extensions

OpenAI Codex adds an optional openai.yaml file alongside SKILL.md for platform metadata (interface, policy, dependencies). SKILL.md itself stays cross-platform. See references/advanced-patterns.md for details.

Things that break cross-platform

| Pattern | Problem | Fix | |---------|---------|-----| | {baseDir} placeholder | Only OpenClaw resolves it | Use relative paths | | Platform-specific instructions | Confuse other LLMs | Keep instructions generic | | Hardcoded paths | Break on other OS/platforms | Use relative from SKILL.md |

Token estimation

Estimate: wc -w SKILL.md × 1.5 (prose) or × 1.7 (code-heavy files).

Budget allocation guide

| Skill complexity | SKILL.md target | References needed? | |-----------------|-----------------|-------------------| | Simple (one topic, few commands) | 100-200 lines / ~1500 tokens | No | | Medium (multiple features, some code) | 200-350 lines / ~3000 tokens | 1-2 files | | Complex (multi-domain, many patterns) | 300-450 lines / ~4500 tokens | 3-5 files |

Severity reference

| Severity | Meaning | Action | |----------|---------|--------| | HIGH | Breaks spec compliance or causes LLM confusion | Must fix | | MEDIUM | Reduces quality or cross-platform compatibility | Should fix | | LOW | Minor improvement opportunity | Fix if time permits |

---

Mode 4: Batch scan (scan-all)

Scan every skill in a directory at once. Useful for auditing your entire skill collection.

Process

1. List all subdirectories containing SKILL.md in the target path (default: ~/.claude/skills/).
2. Run Mode 3 (scan) on each skill. Output each skill's score as you complete it.
3. Output a summary table sorted by score ascending (worst first).

Report format

## Batch Skill Audit

| Skill | Score | HIGH | MEDIUM | LOW | Status |
|-------|-------|------|--------|-----|--------|
| seo-optimizer | 5/10 | 3 | 2 | 1 | NEEDS WORK |
| reprompter | 6/10 | 2 | 3 | 0 | NEEDS WORK |
| blogger | 7/10 | 1 | 1 | 2 | NEEDS WORK |
| humanizer-enhanced | 8/10 | 0 | 2 | 1 | PASS |

Total: 4 skills scanned
PASS: 1 | NEEDS WORK: 3

Top issues across all skills:
1. [HIGH] C2 reprompter: Body exceeds 5000 tokens (est. 8,200)
2. [HIGH] C3 seo-optimizer: Content repeated 4 times
3. [HIGH] C5 reprompter: Persona-based framing

PASS threshold: Score 7+ with zero HIGH issues.

Next step: "Start with the lowest-scoring skill. Run /skeall --improve <path> on it."

---

Mode 5: Health check (runtime audit)

Checks whether a skill actually works at runtime — beyond what static scan can catch. Run static scan (Mode 3) first and fix HIGH issues before health check.

Process

1. Run R1-R7 checks against the target skill.
2. For --healthcheck-all: cross-check all skills for duplicates (R2) and trigger collisions (R3).
3. Output severity-tagged report with sections: RUNTIME, DUPLICATES, TRIGGER COLLISIONS.
4. Labels: [FAIL] for HIGH issues (must fix), [WARN] for MEDIUM (runtime risk), [INFO] for LOW.

For detection algorithms, report format examples, and batch output format, see references/healthcheck.md.

---

Scoring methodology

Formula: Score = max(0, 10 - (HIGHs x 1.5) - min(MEDIUMs x 0.5, 3) - min(LOWs x 0.2, 1))

PASS threshold: Score 7+ AND zero HIGH issues. For detailed examples, see references/scoring.md.

---

Troubleshooting

| Issue | Fix | |-------|-----| | Token estimate seems wrong | Use wc -w and multiply by 1.5 (prose) or 1.7 (code-heavy) | | Scan reports FAIL but skill works fine | HIGHs indicate spec/LLM issues, not runtime bugs. Fix them anyway. | | Batch scan misses a skill | Skill directory must contain SKILL.md at root | | Two fixes contradict each other | Flag the conflict, ask user to choose (e.g., "shorten file" vs "add section") | | Score 7+ but still NEEDS WORK | Check for HIGH issues. Any HIGH = NEEDS WORK regardless of score |

---

References

For detailed checklists and examples, see:

• Anti-patterns with before/after examples
• Runtime health check algorithms and real examples
• Complete SKILL.md template
• Scoring methodology details
• Testing patterns and examples
• Advanced patterns: categories, freedom levels, distribution, MCP, workflows

Testing your skill: After create or improve, test trigger activation (3-5 keyword variants), functional output, and negative (unrelated queries stay quiet). See references/testing.md.

MCP integration: Use fully qualified tool names (mcp__server__tool_name). Document required MCP servers and provide fallbacks. See references/advanced-patterns.md.

Reprompter integration (optional): After --create interview, say "reprompter optimize" to score description variants and validate code examples. Works standalone if reprompter is not installed.