Creator · agent-sh
Last updated · Sep 2, 2026
Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report.
Creator · agent-sh
Last updated · Sep 2, 2026
Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report.
Creator · agent-sh
Last updated · Sep 2, 2026
Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report.
Creator · agent-sh
Last updated · Sep 2, 2026
Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report.
Sandbox only
Install targets
Codex install prompt
Install the "enhance-orchestrator" agent skill from https://github.com/agent-sh/agentsys/tree/main/.kiro/skills/enhance-orchestrator. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"agent-sh-enhance-orchestrator","task":"Install enhance-orchestrator","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add agent-sh/agentsys --skill enhance-orchestrator
Maintenance
fresh
9d since push
Risk
Safe to try
Quality score needs review
GitHub quality
981
77/100 Quality · 80/100 Trust
Coverage tags
Review notes
Quality score needs review
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Safe to tryA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
981 GitHub stars
Repo activity
981 stars, 113 forks
Maintenance
9d since push
License
MIT
Install
npx skills add agent-sh/agentsys --skill enhance-orchestrator
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add agent-sh/agentsys --skill enhance-orchestratorDo not use when
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20enhance-orchestrator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20enhance-orchestrator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/agent-sh-enhance-orchestrator/install
Agent should check
Copy prompt
Task: Use enhance-orchestrator in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20enhance-orchestrator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/agent-sh-enhance-orchestrator/install
Install command: npx skills add agent-sh/agentsys --skill enhance-orchestrator
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/agent-sh-enhance-orchestrator/install
LLM text format
/api/skills/agent-sh-enhance-orchestrator/install?format=text
Find alternatives
/api/skills/search?q=enhance-orchestrator&limit=3
Agent prompt
Use enhance-orchestrator for this task. Review https://www.openagentskill.com/api/skills/agent-sh-enhance-orchestrator/install, then install with: npx skills add agent-sh/agentsys --skill enhance-orchestratorRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/agent-sh-enhance-orchestrator
LLM text
/api/registry/manifest/agent-sh-enhance-orchestrator?format=text
Install alias
/api/registry/install/agent-sh-enhance-orchestrator
Recommend
/api/registry/recommend?task=Use%20enhance-orchestrator%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Research agents
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO981 GitHub stars
Stars/forks activity
INFO981 stars, 113 forks; issue activity unavailable in current metadata
Recent maintenance
PASS9d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Automate repeated work
I need my agent to automate a repeated workflow across tools and files.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Alternative shortlist
Similar skills that may fit this task.
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--- name: enhance-orchestrator description: "Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report." version: 5.1.0 argument-hint: "[path] [--apply] [--focus=TYPE]" ---
# 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 issues
Source provenance
Decision snapshot
981 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for enhance-orchestrator, ready for a manual X post.
A practical pick for a repeatable workflow: enhance-orchestrator: Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report. 981 stars https://www.openagentskill.com/skills/agent-sh-enhance-orchestrator?ref=x
Listing + install path for enhance-orchestrator: https://www.openagentskill.com/skills/agent-sh-enhance-orchestrator?ref=x Install: npx skills add agent-sh/agentsys --skill enhance-orchestrator
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Registry indexed listing is attributed to agent-sh but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/agent-sh-enhance-orchestrator?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/agent-sh-enhance-orchestrator?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/agent-sh-enhance-orchestrator/audit)
[](https://www.openagentskill.com/skills/agent-sh-enhance-orchestrator?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)agent-sh
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Sandbox only
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Install targets
Codex install prompt
Install the "enhance-orchestrator" agent skill from https://github.com/agent-sh/agentsys/tree/main/.kiro/skills/enhance-orchestrator. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"agent-sh-enhance-orchestrator","task":"Install enhance-orchestrator","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add agent-sh/agentsys --skill enhance-orchestrator
Maintenance
fresh
9d since push
Risk
Safe to try
Quality score needs review
GitHub quality
981
77/100 Quality · 80/100 Trust
Coverage tags
Review notes
Quality score needs review
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Safe to tryA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
981 GitHub stars
Repo activity
981 stars, 113 forks
Maintenance
9d since push
License
MIT
Install
npx skills add agent-sh/agentsys --skill enhance-orchestrator
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add agent-sh/agentsys --skill enhance-orchestratorDo not use when
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20enhance-orchestrator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20enhance-orchestrator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/agent-sh-enhance-orchestrator/install
Agent should check
Copy prompt
Task: Use enhance-orchestrator in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20enhance-orchestrator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/agent-sh-enhance-orchestrator/install
Install command: npx skills add agent-sh/agentsys --skill enhance-orchestrator
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/agent-sh-enhance-orchestrator/install
LLM text format
/api/skills/agent-sh-enhance-orchestrator/install?format=text
Find alternatives
/api/skills/search?q=enhance-orchestrator&limit=3
Agent prompt
Use enhance-orchestrator for this task. Review https://www.openagentskill.com/api/skills/agent-sh-enhance-orchestrator/install, then install with: npx skills add agent-sh/agentsys --skill enhance-orchestratorRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/agent-sh-enhance-orchestrator
LLM text
/api/registry/manifest/agent-sh-enhance-orchestrator?format=text
Install alias
/api/registry/install/agent-sh-enhance-orchestrator
Recommend
/api/registry/recommend?task=Use%20enhance-orchestrator%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Research agents
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO981 GitHub stars
Stars/forks activity
INFO981 stars, 113 forks; issue activity unavailable in current metadata
Recent maintenance
PASS9d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Automate repeated work
I need my agent to automate a repeated workflow across tools and files.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Alternative shortlist
Similar skills that may fit this task.
Run multimodal agents that operate desktop interfaces
Connect agents to hundreds of workflow automations
利用AI大模型,一键生成高清短视频 Generate short videos with one click using AI LLM.
Alternative firmware for ESP8266 and ESP32 based devices with easy configuration using webUI, OTA updates, automation using timers or rules, expandability and entirely local control over MQTT, HTTP, Serial or KNX. Full documentation at
--- name: enhance-orchestrator description: "Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report." version: 5.1.0 argument-hint: "[path] [--apply] [--focus=TYPE]" ---
# 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 issues
Source provenance
Decision snapshot
981 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for enhance-orchestrator, ready for a manual X post.
A practical pick for a repeatable workflow: enhance-orchestrator: Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report. 981 stars https://www.openagentskill.com/skills/agent-sh-enhance-orchestrator?ref=x
Listing + install path for enhance-orchestrator: https://www.openagentskill.com/skills/agent-sh-enhance-orchestrator?ref=x Install: npx skills add agent-sh/agentsys --skill enhance-orchestrator
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Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
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Run multimodal agents that operate desktop interfaces
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Install targets
Codex install prompt
Install the "enhance-orchestrator" agent skill from https://github.com/agent-sh/agentsys/tree/main/.kiro/skills/enhance-orchestrator. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"agent-sh-enhance-orchestrator","task":"Install enhance-orchestrator","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add agent-sh/agentsys --skill enhance-orchestrator
Maintenance
fresh
9d since push
Risk
Safe to try
Quality score needs review
GitHub quality
981
77/100 Quality · 80/100 Trust
Coverage tags
Review notes
Quality score needs review
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Safe to tryA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
981 GitHub stars
Repo activity
981 stars, 113 forks
Maintenance
9d since push
License
MIT
Install
npx skills add agent-sh/agentsys --skill enhance-orchestrator
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add agent-sh/agentsys --skill enhance-orchestratorDo not use when
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20enhance-orchestrator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20enhance-orchestrator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/agent-sh-enhance-orchestrator/install
Agent should check
Copy prompt
Task: Use enhance-orchestrator in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20enhance-orchestrator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/agent-sh-enhance-orchestrator/install
Install command: npx skills add agent-sh/agentsys --skill enhance-orchestrator
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/agent-sh-enhance-orchestrator/install
LLM text format
/api/skills/agent-sh-enhance-orchestrator/install?format=text
Find alternatives
/api/skills/search?q=enhance-orchestrator&limit=3
Agent prompt
Use enhance-orchestrator for this task. Review https://www.openagentskill.com/api/skills/agent-sh-enhance-orchestrator/install, then install with: npx skills add agent-sh/agentsys --skill enhance-orchestratorRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/agent-sh-enhance-orchestrator
LLM text
/api/registry/manifest/agent-sh-enhance-orchestrator?format=text
Install alias
/api/registry/install/agent-sh-enhance-orchestrator
Recommend
/api/registry/recommend?task=Use%20enhance-orchestrator%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Research agents
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO981 GitHub stars
Stars/forks activity
INFO981 stars, 113 forks; issue activity unavailable in current metadata
Recent maintenance
PASS9d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Automate repeated work
I need my agent to automate a repeated workflow across tools and files.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Alternative shortlist
Similar skills that may fit this task.
Run multimodal agents that operate desktop interfaces
Connect agents to hundreds of workflow automations
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Alternative firmware for ESP8266 and ESP32 based devices with easy configuration using webUI, OTA updates, automation using timers or rules, expandability and entirely local control over MQTT, HTTP, Serial or KNX. Full documentation at
--- name: enhance-orchestrator description: "Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report." version: 5.1.0 argument-hint: "[path] [--apply] [--focus=TYPE]" ---
# 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 issues
Source provenance
Decision snapshot
981 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for enhance-orchestrator, ready for a manual X post.
A practical pick for a repeatable workflow: enhance-orchestrator: Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report. 981 stars https://www.openagentskill.com/skills/agent-sh-enhance-orchestrator?ref=x
Listing + install path for enhance-orchestrator: https://www.openagentskill.com/skills/agent-sh-enhance-orchestrator?ref=x Install: npx skills add agent-sh/agentsys --skill enhance-orchestrator
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Registry indexed listing is attributed to agent-sh but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
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Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/agent-sh-enhance-orchestrator?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/agent-sh-enhance-orchestrator?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
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UI-TARS Desktop
Run multimodal agents that operate desktop interfaces
37.0K Starsn8n
Connect agents to hundreds of workflow automations
194.1K StarsMoneyPrinterTurbo
利用AI大模型,一键生成高清短视频 Generate short videos with one click using AI LLM.
88.5K StarsTasmota
Alternative firmware for ESP8266 and ESP32 based devices with easy configuration using webUI, OTA updates, automation using timers or rules, expandability and entirely local control over MQTT, HTTP, Serial or KNX. Full documentation at
24.7K StarsSandbox only
Install targets
Codex install prompt
Install the "enhance-orchestrator" agent skill from https://github.com/agent-sh/agentsys/tree/main/.kiro/skills/enhance-orchestrator. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"agent-sh-enhance-orchestrator","task":"Install enhance-orchestrator","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add agent-sh/agentsys --skill enhance-orchestrator
Maintenance
fresh
9d since push
Risk
Safe to try
Quality score needs review
GitHub quality
981
77/100 Quality · 80/100 Trust
Coverage tags
Review notes
Quality score needs review
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Safe to tryA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
981 GitHub stars
Repo activity
981 stars, 113 forks
Maintenance
9d since push
License
MIT
Install
npx skills add agent-sh/agentsys --skill enhance-orchestrator
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add agent-sh/agentsys --skill enhance-orchestratorDo not use when
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20enhance-orchestrator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20enhance-orchestrator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/agent-sh-enhance-orchestrator/install
Agent should check
Copy prompt
Task: Use enhance-orchestrator in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20enhance-orchestrator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/agent-sh-enhance-orchestrator/install
Install command: npx skills add agent-sh/agentsys --skill enhance-orchestrator
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/agent-sh-enhance-orchestrator/install
LLM text format
/api/skills/agent-sh-enhance-orchestrator/install?format=text
Find alternatives
/api/skills/search?q=enhance-orchestrator&limit=3
Agent prompt
Use enhance-orchestrator for this task. Review https://www.openagentskill.com/api/skills/agent-sh-enhance-orchestrator/install, then install with: npx skills add agent-sh/agentsys --skill enhance-orchestratorRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/agent-sh-enhance-orchestrator
LLM text
/api/registry/manifest/agent-sh-enhance-orchestrator?format=text
Install alias
/api/registry/install/agent-sh-enhance-orchestrator
Recommend
/api/registry/recommend?task=Use%20enhance-orchestrator%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Research agents
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO981 GitHub stars
Stars/forks activity
INFO981 stars, 113 forks; issue activity unavailable in current metadata
Recent maintenance
PASS9d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Automate repeated work
I need my agent to automate a repeated workflow across tools and files.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Alternative shortlist
Similar skills that may fit this task.
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--- name: enhance-orchestrator description: "Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report." version: 5.1.0 argument-hint: "[path] [--apply] [--focus=TYPE]" ---
# 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 issues
Source provenance
Decision snapshot
981 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for enhance-orchestrator, ready for a manual X post.
A practical pick for a repeatable workflow: enhance-orchestrator: Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report. 981 stars https://www.openagentskill.com/skills/agent-sh-enhance-orchestrator?ref=x
Listing + install path for enhance-orchestrator: https://www.openagentskill.com/skills/agent-sh-enhance-orchestrator?ref=x Install: npx skills add agent-sh/agentsys --skill enhance-orchestrator
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Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
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Strong README/SKILL.md context
Risk summary
Install readiness
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shell or command execution, filesystem or document access
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Risk summary
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