enhance-orchestrator
Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report.
Best use case
enhance-orchestrator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report.
Teams using enhance-orchestrator should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/enhance-orchestrator/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How enhance-orchestrator Compares
| Feature / Agent | enhance-orchestrator | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# enhance-orchestrator
Coordinate all enhancement analyzers in parallel and produce a unified report.
## Critical Rules
1. **MUST run enhancers in parallel** - Use Promise.all for efficiency
2. **MUST only run enhancers for existing content** - Skip if no files found
3. **MUST report HIGH certainty first** - Priority order: HIGH → MEDIUM → LOW
4. **NEVER auto-fix without --apply flag** - Explicit consent required
5. **NEVER auto-fix MEDIUM or LOW issues** - Only HIGH certainty
## Workflow
### Phase 1: Parse Arguments
```javascript
const args = '$ARGUMENTS'.split(' ').filter(Boolean);
const targetPath = args.find(a => !a.startsWith('--')) || '.';
const flags = {
apply: args.includes('--apply'),
focus: args.find(a => a.startsWith('--focus='))?.split('=')[1],
verbose: args.includes('--verbose'),
showSuppressed: args.includes('--show-suppressed'),
resetLearned: args.includes('--reset-learned'),
noLearn: args.includes('--no-learn'),
exportLearned: args.includes('--export-learned')
};
// Validate focus type
const VALID_FOCUS = ['plugin', 'agent', 'claudemd', 'claude-memory', 'docs', 'prompt', 'hooks', 'skills', 'cross-file'];
if (flags.focus && !VALID_FOCUS.includes(flags.focus)) {
console.error(`Invalid --focus: "${flags.focus}". Valid: ${VALID_FOCUS.join(', ')}`);
return;
}
```
### Phase 2: Discovery
Detect what exists in target path:
```javascript
const discovery = {
plugins: await Glob({ pattern: 'plugins/*/.claude-plugin/plugin.json', path: targetPath }),
agents: await Glob({ pattern: '**/agents/*.md', path: targetPath }),
claudemd: await Glob({ pattern: '**/CLAUDE.md', path: targetPath }) ||
await Glob({ pattern: '**/AGENTS.md', path: targetPath }),
docs: await Glob({ pattern: 'docs/**/*.md', path: targetPath }),
prompts: await Glob({ pattern: '**/prompts/**/*.md', path: targetPath }) ||
await Glob({ pattern: '**/commands/**/*.md', path: targetPath }),
hooks: await Glob({ pattern: '**/hooks/**/*.md', path: targetPath }),
skills: await Glob({ pattern: '**/skills/**/SKILL.md', path: targetPath }),
// Cross-file runs if agents OR skills exist (analyzes relationships)
'cross-file': discovery.agents?.length || discovery.skills?.length ? ['enabled'] : []
};
```
### Phase 3: Load Suppressions
```javascript
// Use relative path from skill directory to plugin lib
// Path: skills/enhance-orchestrator/ -> ../../lib/
const { getSuppressionPath } = require('../../lib/cross-platform');
const { loadAutoSuppressions, getProjectId, clearAutoSuppressions } = require('../../lib/enhance/auto-suppression');
const suppressionPath = getSuppressionPath();
const projectId = getProjectId(targetPath);
if (flags.resetLearned) {
clearAutoSuppressions(suppressionPath, projectId);
console.log(`Cleared suppressions for project: ${projectId}`);
}
const autoLearned = loadAutoSuppressions(suppressionPath, projectId);
```
### Phase 4: Launch Enhancers in Parallel
**CRITICAL**: MUST spawn these EXACT agents using Task(). Do NOT use Explore or other agents.
| Focus Type | Agent to Spawn | Model | JS Analyzer |
|------------|----------------|-------|-------------|
| `plugin` | `plugin-enhancer` | sonnet | `lib/enhance/plugin-analyzer.js` |
| `agent` | `agent-enhancer` | opus | `lib/enhance/agent-analyzer.js` |
| `claudemd` | `claudemd-enhancer` | opus | `lib/enhance/projectmemory-analyzer.js` |
| `docs` | `docs-enhancer` | opus | `lib/enhance/docs-analyzer.js` |
| `prompt` | `prompt-enhancer` | opus | `lib/enhance/prompt-analyzer.js` |
| `hooks` | `hooks-enhancer` | opus | `lib/enhance/hook-analyzer.js` |
| `skills` | `skills-enhancer` | opus | `lib/enhance/skill-analyzer.js` |
| `cross-file` | `cross-file-enhancer` | sonnet | `lib/enhance/cross-file-analyzer.js` |
Each agent has `Bash(node:*)` to run its JS analyzer. Do NOT substitute with Explore agents.
```javascript
// EXACT agent mapping - do not change
const ENHANCER_AGENTS = {
plugin: 'plugin-enhancer',
agent: 'agent-enhancer',
claudemd: 'claudemd-enhancer',
docs: 'docs-enhancer',
prompt: 'prompt-enhancer',
hooks: 'hooks-enhancer',
skills: 'skills-enhancer',
'cross-file': 'cross-file-enhancer'
};
const promises = [];
for (const [type, agentType] of Object.entries(ENHANCER_AGENTS)) {
if (focus && focus !== type) continue;
if (!discovery[type]?.length) continue;
// MUST use exact subagent_type - these agents have Bash(node:*) to run JS analyzers
promises.push(Task({
subagent_type: agentType,
prompt: `Analyze ${type} in ${targetPath}.
MUST use Skill tool to invoke your enhance-* skill.
The skill runs the JavaScript analyzer and returns structured findings.
verbose: ${flags.verbose}
Return JSON: { "enhancerType": "${type}", "findings": [...], "summary": { high, medium, low } }`
}));
}
// MUST use Promise.all for parallel execution
const results = await Promise.all(promises);
```
### Phase 5: Aggregate Results
```javascript
function aggregateResults(enhancerResults) {
const findings = [];
const byEnhancer = {};
for (const result of enhancerResults) {
if (!result?.findings) continue;
for (const finding of result.findings) {
findings.push({ ...finding, source: result.enhancerType });
}
byEnhancer[result.enhancerType] = result.summary;
}
return {
findings,
byEnhancer,
totals: {
high: findings.filter(f => f.certainty === 'HIGH').length,
medium: findings.filter(f => f.certainty === 'MEDIUM').length,
low: findings.filter(f => f.certainty === 'LOW').length
}
};
}
```
### Phase 6: Generate Report
Generate report directly from aggregated findings:
```javascript
const { generateReport } = require('../../lib/enhance/reporter');
const report = generateReport(aggregated, {
verbose: flags.verbose,
showAutoFixable: flags.apply
});
console.log(report);
```
### Phase 7: Auto-Learning
```javascript
if (!flags.noLearn) {
const { analyzeForAutoSuppression, saveAutoSuppressions } = require('../../lib/enhance/auto-suppression');
const newSuppressions = analyzeForAutoSuppression(aggregated.findings, fileContents, { projectRoot: targetPath });
if (newSuppressions.length > 0) {
saveAutoSuppressions(suppressionPath, projectId, newSuppressions);
console.log(`\nLearned ${newSuppressions.length} new suppressions.`);
}
}
```
### Phase 8: Apply Fixes
```javascript
if (flags.apply) {
const autoFixable = aggregated.findings.filter(f => f.certainty === 'HIGH' && f.autoFixable);
if (autoFixable.length > 0) {
console.log(`\n## Applying ${autoFixable.length} Auto-Fixes\n`);
const byEnhancer = {};
for (const fix of autoFixable) {
const type = fix.source;
if (!byEnhancer[type]) byEnhancer[type] = [];
byEnhancer[type].push(fix);
}
for (const [type, fixes] of Object.entries(byEnhancer)) {
await Task({
subagent_type: enhancerAgents[type],
prompt: `Apply HIGH certainty fixes: ${JSON.stringify(fixes, null, 2)}`
});
}
console.log(`Applied ${autoFixable.length} fixes.`);
}
}
```
## Output Format
```markdown
# Enhancement Analysis Report
**Target**: {targetPath}
**Date**: {timestamp}
**Enhancers Run**: {list}
## Executive Summary
| Enhancer | HIGH | MEDIUM | LOW | Auto-Fixable |
|----------|------|--------|-----|--------------|
| plugin | 2 | 3 | 1 | 1 |
| agent | 1 | 2 | 0 | 1 |
| **Total**| **3**| **5** | **1**| **2** |
## HIGH Certainty Issues
[Grouped by enhancer, then file]
## MEDIUM Certainty Issues
[...]
## Auto-Fix Summary
{n} issues can be fixed with `--apply` flag.
```
## Constraints
- MUST run enhancers in parallel (Promise.all)
- MUST skip enhancers for missing content types
- MUST report HIGH certainty issues first
- MUST deduplicate findings across enhancers
- NEVER auto-fix without explicit --apply flag
- NEVER auto-fix MEDIUM or LOW certainty issuesRelated Skills
image-enhancer
Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.
comprehensive-review-pr-enhance
You are a PR optimization expert specializing in creating high-quality pull requests that facilitate efficient code reviews. Generate comprehensive PR descriptions, automate review processes, and e...
enhance-hooks
Use when reviewing hooks for safety, timeouts, and correct frontmatter.
tdd-orchestrator
Master TDD orchestrator specializing in red-green-refactor discipline, multi-agent workflow coordination, and comprehensive test-driven development practices.
enhance-prompts
Use when improving general prompts for structure, examples, and constraints.
enhance-docs
Use when improving documentation structure, accuracy, and RAG readiness.
enhance-claude-memory
Use when improving CLAUDE.md or AGENTS.md project memory files.
enhance-agent-prompts
Use when improving agent prompts, frontmatter, and tool restrictions.
semgrep-rule-variant-creator
Creates language variants of existing Semgrep rules. Use when porting a Semgrep rule to specified target languages. Takes an existing rule and target languages as input, produces independent rule+test directories for each language.
searchnews
当用户要求"搜索新闻"、"查询AI新闻"、"整理新闻"、"获取某天的新闻",或提到需要搜索、整理、汇总指定日期的AI行业新闻时,应使用此技能。
search-specialist
Expert web researcher using advanced search techniques and
scorecard-marketing
Build quiz and assessment funnels that generate qualified leads at 30-50% conversion. Use when the user mentions "lead magnet", "quiz funnel", "assessment tool", "lead generation", or "score-based segmentation". Covers question design, dynamic results by tier, and automated follow-up sequences. For landing page conversion, see cro-methodology. For full marketing plans, see one-page-marketing.