How should crewai-output-guard-example be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this skill.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

Crawler Summary

crewai-output-guard-example answer-first brief

CrewAI + Agent Output Guard: validated task handoffs with zero LLM cost. Schema validation, hallucination detection, self-healing crews with retry. CrewAI + Agent Output Guard: Validated Task Handoffs **Problem:** CrewAI crews pass task outputs between agents automatically. When Agent A produces bad data — wrong format, hallucinated numbers, stale information — Agent B builds on it without question. By the time you notice, the whole crew's output is wrong. **Solution:** Add validation between crew task handoffs using $1. Zero LLM cost — pure computation that cat Capability contract not published. No trust telemetry is available yet. Last updated 5/31/2026.

Freshness

Last checked 5/31/2026

Best For

crewai-output-guard-example is best for crewai, multi-agent 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

Card Facts Snapshot Contract Trust

Claim this agent

Agent DossierGitHubSafety: 66/100

crewai-output-guard-example

OpenClawself-declared

Public facts

Change events

Artifacts

Freshness

May 31, 2026

Verifiededitorial-contentNo verified compatibility signals

Capability contract not published. No trust telemetry is available yet. Last updated 5/31/2026.

Trust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

May 31, 2026

Vendor

Agenson Tools

Artifacts

Benchmarks

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Unpublished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 5/31/2026.

View Source

Setup snapshot

git clone https://github.com/agenson-tools/crewai-output-guard-example.git

1
Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
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

Agenson Tools

profilemedium

Observed May 31, 2026Source link Provenance

Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium

Observed May 31, 2026Source link Provenance

Security (1)

Handshake status

UNKNOWN

trustmedium

Observed unknownSource link Provenance

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

Examples

Snippets

Languages

python

Executable Examples

bash

pip install crewai crewai-tools
npm install -g @agenson-horrowitz/agent-output-guard-mcp

export OPENAI_API_KEY=your-key
python examples/01_validated_crew.py
python examples/02_task_output_guard.py
python examples/03_crew_with_retry.py

text

Researcher Agent → "Revenue is $50B" (hallucinated)
    ↓ (no validation)
Analyst Agent → builds financial model on $50B
    ↓ (no validation)  
Writer Agent → publishes report with wrong numbers
    ↓
You → discovers the error after it's been shared

text

Researcher Agent → "Revenue is $50B"
    ↓
🛡️ Guard → flags uncertainty markers, checks schema
    ↓ (validated or rejected)
Analyst Agent → works with verified data only
    ↓
🛡️ Guard → validates model consistency
    ↓
Writer Agent → publishes reliable report

python

from crewai import Task
from guard_client import AgentOutputGuard

guard = AgentOutputGuard()

def validate_research(output):
    """Callback that runs after the research task completes."""
    result = guard.verify_json_schema(
        data=output.raw,
        schema=RESEARCH_SCHEMA,
        source_agent="researcher",
    )
    if not result.get("valid"):
        raise ValueError(f"Research output invalid: {result['errors']}")
    
    hallucination = guard.detect_hallucination_markers(
        text=output.raw,
        content_type="analysis",
        sensitivity="high",
    )
    if hallucination.get("confidence_score", 1.0) < 0.6:
        raise ValueError("Research output has high hallucination risk")

research_task = Task(
    description="Research competitor pricing...",
    agent=researcher,
    callback=validate_research,  # ← validation happens here
    expected_output="JSON with competitor data",
)

text

┌─────────────────────────────────────────────────┐
│                   CrewAI Crew                    │
│                                                  │
│  ┌──────────┐  callback  ┌──────────┐  callback │
│  │ Task A   │───────────▶│ Task B   │──────────▶│
│  │Researcher│  🛡️ Guard  │ Analyst  │  🛡️ Guard │
│  └──────────┘            └──────────┘           │
│                                                  │
│  Validation checks (zero LLM cost):             │
│  • JSON schema compliance                        │
│  • Hallucination marker detection                │
│  • Data freshness verification                   │
│  • Cross-reference between task outputs          │
└─────────────────────────────────────────────────┘

Docs & README

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

Self-declaredGITHUB OPENCLEW

Docs source

GITHUB OPENCLEW

Editorial quality

ready

Full README

CrewAI + Agent Output Guard: Validated Task Handoffs

Problem: CrewAI crews pass task outputs between agents automatically. When Agent A produces bad data — wrong format, hallucinated numbers, stale information — Agent B builds on it without question. By the time you notice, the whole crew's output is wrong.

Solution: Add validation between crew task handoffs using Agent Output Guard. Zero LLM cost — pure computation that catches problems before they cascade through your crew.

Quick Start

pip install crewai crewai-tools
npm install -g @agenson-horrowitz/agent-output-guard-mcp

export OPENAI_API_KEY=your-key
python examples/01_validated_crew.py
python examples/02_task_output_guard.py
python examples/03_crew_with_retry.py

What This Solves

The CrewAI handoff problem

Researcher Agent → "Revenue is $50B" (hallucinated)
    ↓ (no validation)
Analyst Agent → builds financial model on $50B
    ↓ (no validation)  
Writer Agent → publishes report with wrong numbers
    ↓
You → discovers the error after it's been shared

With Agent Output Guard

Researcher Agent → "Revenue is $50B"
    ↓
🛡️ Guard → flags uncertainty markers, checks schema
    ↓ (validated or rejected)
Analyst Agent → works with verified data only
    ↓
🛡️ Guard → validates model consistency
    ↓
Writer Agent → publishes reliable report

Examples

1. Validated Crew (`examples/01_validated_crew.py`)

A three-agent crew (Researcher → Analyst → Writer) with validation callbacks between each task handoff. The simplest way to add guards to an existing crew.

2. Task Output Guard (`examples/02_task_output_guard.py`)

A reusable TaskOutputGuard class that wraps CrewAI's task output handling. Define schemas per task and the guard validates automatically. Drop-in addition to any existing crew.

3. Crew with Retry (`examples/03_crew_with_retry.py`)

When validation fails, the crew retries the failed task with feedback about what went wrong. Shows how to build self-healing crews that fix their own output quality issues.

Integration Pattern

CrewAI's task.callback is the natural integration point:

from crewai import Task
from guard_client import AgentOutputGuard

guard = AgentOutputGuard()

def validate_research(output):
    """Callback that runs after the research task completes."""
    result = guard.verify_json_schema(
        data=output.raw,
        schema=RESEARCH_SCHEMA,
        source_agent="researcher",
    )
    if not result.get("valid"):
        raise ValueError(f"Research output invalid: {result['errors']}")
    
    hallucination = guard.detect_hallucination_markers(
        text=output.raw,
        content_type="analysis",
        sensitivity="high",
    )
    if hallucination.get("confidence_score", 1.0) < 0.6:
        raise ValueError("Research output has high hallucination risk")

research_task = Task(
    description="Research competitor pricing...",
    agent=researcher,
    callback=validate_research,  # ← validation happens here
    expected_output="JSON with competitor data",
)

Architecture

┌─────────────────────────────────────────────────┐
│                   CrewAI Crew                    │
│                                                  │
│  ┌──────────┐  callback  ┌──────────┐  callback │
│  │ Task A   │───────────▶│ Task B   │──────────▶│
│  │Researcher│  🛡️ Guard  │ Analyst  │  🛡️ Guard │
│  └──────────┘            └──────────┘           │
│                                                  │
│  Validation checks (zero LLM cost):             │
│  • JSON schema compliance                        │
│  • Hallucination marker detection                │
│  • Data freshness verification                   │
│  • Cross-reference between task outputs          │
└─────────────────────────────────────────────────┘

Full Source

License

MIT

Contract & API

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

MissingGITHUB OPENCLEW

Endpoints

Dossier API Snapshot API Contract API Trust API

Contract coverage

Status

missing

Auth

None

Streaming

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://www.xpersona.co/api/v1/agents/crewai-agenson-tools-crewai-output-guard-example/snapshot"

curl -s "https://www.xpersona.co/api/v1/agents/crewai-agenson-tools-crewai-output-guard-example/contract"

curl -s "https://www.xpersona.co/api/v1/agents/crewai-agenson-tools-crewai-output-guard-example/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 OpenclewUpdated 4mo agoRank 65

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OPENCLAW

Github OpenclewUpdated 4mo agoRank 65

@langchain/langgraph-swarm

An implementation of a multi-agent swarm using LangGraph

OPENCLAW

Github OpenclewUpdated 4mo agoRank 65

@langchain/langgraph-supervisor

LangGraph Multi-Agent Supervisor

OPENCLAW

Github OpenclewUpdated 4mo agoRank 65

oceanbus-langchain

LangChain tools for OceanBus — give your LangChain and CrewAI agents a global identity, encrypted messaging, and Yellow Pages service discovery with a single import.

OPENCLAWoceanbuslangchainlangchain-tools

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://www.xpersona.co/api/v1/agents/crewai-agenson-tools-crewai-output-guard-example/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-agenson-tools-crewai-output-guard-example/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-agenson-tools-crewai-output-guard-example/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-agenson-tools-crewai-output-guard-example/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-agenson-tools-crewai-output-guard-example/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-agenson-tools-crewai-output-guard-example/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-10-08T23:09:50.748Z"
    }
  },
  "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": "crewai",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "multi-agent",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile capability:crewai|supported|profile capability:multi-agent|supported|profile"
}

Facts JSON

[
  {
    "factKey": "vendor",
    "label": "Vendor",
    "value": "Agenson Tools",
    "category": "vendor",
    "href": "https://github.com/agenson-tools/crewai-output-guard-example",
    "sourceUrl": "https://github.com/agenson-tools/crewai-output-guard-example",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-05-31T06:18:42.969Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "protocols",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "category": "compatibility",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-agenson-tools-crewai-output-guard-example/contract",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-agenson-tools-crewai-output-guard-example/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-05-31T06:18:42.969Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "handshake_status",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "category": "security",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-agenson-tools-crewai-output-guard-example/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-agenson-tools-crewai-output-guard-example/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true,
    "metadata": {}
  }
]

Change Events JSON

[]

crewai-output-guard-example answer-first brief

Executive Summary

Evidence Ledger

Release & Crawl Timeline

Artifacts Archive

Docs & README

CrewAI + Agent Output Guard: Validated Task Handoffs

Quick Start

What This Solves

The CrewAI handoff problem

With Agent Output Guard

Examples

1. Validated Crew (examples/01_validated_crew.py)

2. Task Output Guard (examples/02_task_output_guard.py)

3. Crew with Retry (examples/03_crew_with_retry.py)

Integration Pattern

Architecture

Full Source

License

Contract & API

Reliability & Benchmarks

Media & Demo

Related Agents

@x1pay/langchain

@langchain/langgraph-swarm

@langchain/langgraph-supervisor

oceanbus-langchain

1. Validated Crew (`examples/01_validated_crew.py`)

2. Task Output Guard (`examples/02_task_output_guard.py`)

3. Crew with Retry (`examples/03_crew_with_retry.py`)