Crawler Summary

agent-registry answer-first brief

MANDATORY agent discovery system for token-efficient agent loading. Claude MUST use this skill instead of loading agents directly from ~/.claude/agents/ or .claude/agents/. Provides lazy loading via search_agents and get_agent tools. Use when: (1) user task may benefit from specialized agent expertise, (2) user asks about available agents, (3) starting complex workflows that historically used agents. This skill reduces context window usage by ~95% compared to loading all agents upfront. --- name: agent-registry description: | MANDATORY agent discovery system for token-efficient agent loading. Claude MUST use this skill instead of loading agents directly from ~/.claude/agents/ or .claude/agents/. Provides lazy loading via search_agents and get_agent tools. Use when: (1) user task may benefit from specialized agent expertise, (2) user asks about available agents, (3) starting complex workflows that hi Capability contract not published. No trust telemetry is available yet. Last updated 4/15/2026.

Freshness

Last checked 4/15/2026

Best For

agent-registry is best for you, python, the workflows where OpenClaw compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB OPENCLEW, runtime-metrics, public facts pack

Claim this agent
Agent DossierGitHubSafety: 94/100

agent-registry

MANDATORY agent discovery system for token-efficient agent loading. Claude MUST use this skill instead of loading agents directly from ~/.claude/agents/ or .claude/agents/. Provides lazy loading via search_agents and get_agent tools. Use when: (1) user task may benefit from specialized agent expertise, (2) user asks about available agents, (3) starting complex workflows that historically used agents. This skill reduces context window usage by ~95% compared to loading all agents upfront. --- name: agent-registry description: | MANDATORY agent discovery system for token-efficient agent loading. Claude MUST use this skill instead of loading agents directly from ~/.claude/agents/ or .claude/agents/. Provides lazy loading via search_agents and get_agent tools. Use when: (1) user task may benefit from specialized agent expertise, (2) user asks about available agents, (3) starting complex workflows that hi

OpenClawself-declared

Public facts

4

Change events

1

Artifacts

0

Freshness

Apr 15, 2026

Verifiededitorial-contentNo verified compatibility signals

Capability contract not published. No trust telemetry is available yet. Last updated 4/15/2026.

Trust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Apr 15, 2026

Vendor

Hanzoskill

Artifacts

0

Benchmarks

0

Last release

Unpublished

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. Last updated 4/15/2026.

Setup snapshot

git clone https://github.com/hanzoskill/agent-registry.git
  1. 1

    Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.

  2. 2

    Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Hanzoskill

profilemedium
Observed Apr 15, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed Apr 15, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance
Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium
Observed Apr 15, 2026Source linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB OPENCLEW

Extracted files

0

Examples

6

Snippets

0

Languages

typescript

Parameters

Executable Examples

text

User Request → search_agents(intent) → select best match → get_agent(name) → execute with agent

bash

# Step 1: Search for relevant agents
python scripts/search_agents.py "code review security authentication"

# Output:
# Found 2 matching agents:
#   1. security-auditor (score: 0.89) - Analyzes code for security vulnerabilities
#   2. code-reviewer (score: 0.71) - General code review and best practices

# Step 2: Load the best match
python scripts/get_agent.py security-auditor

# Step 3: Follow loaded agent instructions for the task

bash

# NPX with add-skill (recommended)
npx add-skill MaTriXy/Agent-Registry

# OR npm directly
npm install -g @claude-code/agent-registry

bash

# User-level installation
./install.sh

# OR project-level installation
./install.sh --project

bash

cd ~/.claude/skills/agent-registry
python scripts/init_registry.py

bash

pip3 install questionary

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB OPENCLEW

Docs source

GITHUB OPENCLEW

Editorial quality

ready

MANDATORY agent discovery system for token-efficient agent loading. Claude MUST use this skill instead of loading agents directly from ~/.claude/agents/ or .claude/agents/. Provides lazy loading via search_agents and get_agent tools. Use when: (1) user task may benefit from specialized agent expertise, (2) user asks about available agents, (3) starting complex workflows that historically used agents. This skill reduces context window usage by ~95% compared to loading all agents upfront. --- name: agent-registry description: | MANDATORY agent discovery system for token-efficient agent loading. Claude MUST use this skill instead of loading agents directly from ~/.claude/agents/ or .claude/agents/. Provides lazy loading via search_agents and get_agent tools. Use when: (1) user task may benefit from specialized agent expertise, (2) user asks about available agents, (3) starting complex workflows that hi

Full README

name: agent-registry description: | MANDATORY agent discovery system for token-efficient agent loading. Claude MUST use this skill instead of loading agents directly from ~/.claude/agents/ or .claude/agents/. Provides lazy loading via search_agents and get_agent tools. Use when: (1) user task may benefit from specialized agent expertise, (2) user asks about available agents, (3) starting complex workflows that historically used agents. This skill reduces context window usage by ~95% compared to loading all agents upfront.

Agent Registry

Lazy-loading system for Claude Code agents. Eliminates the "~16k tokens" warning by loading agents on-demand.

CRITICAL RULE

NEVER assume agents are pre-loaded. Always use this registry to discover and load agents.

Workflow

User Request → search_agents(intent) → select best match → get_agent(name) → execute with agent

Available Commands

| Command | When to Use | Example | |---------|-------------|---------| | list_agents.py | User asks "what agents do I have" or needs overview | python scripts/list_agents.py | | search_agents.py | Find agents matching user intent (ALWAYS do this first) | python scripts/search_agents.py "code review security" | | search_agents_paged.py | Paged search for large registries (300+ agents) | python scripts/search_agents_paged.py "query" --page 1 --page-size 10 | | get_agent.py | Load a specific agent's full instructions | python scripts/get_agent.py code-reviewer |

Search First Pattern

  1. Extract intent keywords from user request
  2. Run search: python scripts/search_agents.py "<keywords>"
  3. Review results: Check relevance scores (0.0-1.0)
  4. Load if needed: python scripts/get_agent.py <agent-name>
  5. Execute: Follow the loaded agent's instructions

Example

User: "Can you review my authentication code for security issues?"

# Step 1: Search for relevant agents
python scripts/search_agents.py "code review security authentication"

# Output:
# Found 2 matching agents:
#   1. security-auditor (score: 0.89) - Analyzes code for security vulnerabilities
#   2. code-reviewer (score: 0.71) - General code review and best practices

# Step 2: Load the best match
python scripts/get_agent.py security-auditor

# Step 3: Follow loaded agent instructions for the task

Installation

Step 1: Install the Skill

Quick Install (Recommended):

# NPX with add-skill (recommended)
npx add-skill MaTriXy/Agent-Registry

# OR npm directly
npm install -g @claude-code/agent-registry

Traditional Install:

# User-level installation
./install.sh

# OR project-level installation
./install.sh --project

What install.sh does:

  1. ✓ Copies skill files to ~/.claude/skills/agent-registry/
  2. ✓ Creates empty registry structure
  3. ✓ Automatically installs questionary Python package (for interactive UI)
  4. ✓ Falls back gracefully if pip3 not available

Note: All installation methods support Python-based migration and CLI tools

Step 2: Migrate Your Agents

Run the interactive migration script:

cd ~/.claude/skills/agent-registry
python scripts/init_registry.py

Interactive selection modes:

  • With questionary (recommended): Checkbox UI with category grouping, token indicators, and paging

    • ↑↓ navigate, Space toggle, Enter confirm
    • Visual indicators: 🟢 <1k tokens, 🟡 1-3k, 🔴 >3k
    • Grouped by subdirectory
  • Without questionary (fallback): Text-based number input

    • Enter comma-separated numbers (e.g., 1,3,5)
    • Type all to migrate everything

What init_registry.py does:

  1. Scans ~/.claude/agents/ and .claude/agents/ for agent files
  2. Displays available agents with metadata
  3. Lets you interactively select which to migrate
  4. Moves selected agents to the registry
  5. Builds search index (registry.json)

Dependencies

  • Python: 3.7 or higher
  • questionary: Interactive checkbox selection UI with Separator support

The installer automatically installs questionary. If installation fails or pip3 is unavailable, the migration script falls back to text-based input mode.

Manual installation:

pip3 install questionary

Registry Location

  • Global: ~/.claude/skills/agent-registry/
  • Project: .claude/skills/agent-registry/ (optional override)

Agents not migrated remain in their original locations and load normally (contributing to token overhead).

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB OPENCLEW

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
curl -s "https://xpersona.co/api/v1/agents/hanzoskill-agent-registry/snapshot"
curl -s "https://xpersona.co/api/v1/agents/hanzoskill-agent-registry/contract"
curl -s "https://xpersona.co/api/v1/agents/hanzoskill-agent-registry/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

Self-declaredprotocol-neighbors
GITHUB_REPOSactivepieces

Rank

70

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

Traction

No public download signal

Freshness

Updated 2d ago

OPENCLAW
GITHUB_REPOScherry-studio

Rank

70

AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs

Traction

No public download signal

Freshness

Updated 5d ago

MCPOPENCLAW
GITHUB_REPOSAionUi

Rank

70

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

Traction

No public download signal

Freshness

Updated 6d ago

MCPOPENCLAW
GITHUB_REPOSCopilotKit

Rank

70

The Frontend for Agents & Generative UI. React + Angular

Traction

No public download signal

Freshness

Updated 23d ago

OPENCLAW
Machine Appendix

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://xpersona.co/api/v1/agents/hanzoskill-agent-registry/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/hanzoskill-agent-registry/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/hanzoskill-agent-registry/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/hanzoskill-agent-registry/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/hanzoskill-agent-registry/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/hanzoskill-agent-registry/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-04-16T23:30:00.836Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "OPENCLEW",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    },
    {
      "key": "you",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "python",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "the",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile capability:you|supported|profile capability:python|supported|profile capability:the|supported|profile"
}

Facts JSON

[
  {
    "factKey": "docs_crawl",
    "category": "integration",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  },
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Hanzoskill",
    "href": "https://github.com/hanzoskill/agent-registry",
    "sourceUrl": "https://github.com/hanzoskill/agent-registry",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-15T02:13:10.113Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://xpersona.co/api/v1/agents/hanzoskill-agent-registry/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/hanzoskill-agent-registry/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-04-15T02:13:10.113Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://xpersona.co/api/v1/agents/hanzoskill-agent-registry/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/hanzoskill-agent-registry/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  }
]

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