How should ai-logs-analytics 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

ai-logs-analytics answer-first brief

CrewAI mini-app for incident analysis AI Logs Analytics Automated log incident analysis pipeline built with CrewAI. Parses application logs, extracts structured incidents, and generates a Markdown report. Tech Stack - **Framework:** CrewAI - **LLM:** Llama 3.1 (8B) via Ollama (ollama/llama3.1:8b) - **Validation:** Pydantic - **Language:** Python Architecture The application follows a **sequential two-agent pipeline**: 1. **Parse** — log_analyst extracts Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.

Freshness

Last checked 10/9/2026

Best For

ai-logs-analytics 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 REPOS, runtime-metrics, public facts pack

Card Facts Snapshot Contract Trust

Agent DossierGITHUB REPOSSafety: 66/100

ai-logs-analytics

OpenClawself-declared

Public facts

Change events

Artifacts

Freshness

Oct 9, 2026

Verifiededitorial-contentNo verified compatibility signals

Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.

Trust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Oct 9, 2026

Vendor

Aryabchi

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Unpublished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 10/9/2026.

View Source

Setup snapshot

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

Aryabchi

profilemedium

Observed Oct 9, 2026Source link Provenance

Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium

Observed Oct 9, 2026Source link Provenance

Security (1)

Handshake status

UNKNOWN

trustmedium

Observed unknownSource link Provenance

Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium

Observed Apr 15, 2026Source link Provenance

Release & Crawl Timeline

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

Self-declaredagent-index

Docs Update

Docs refreshed: Sign in to GitHub · GitHub

search_documentmedium

Fresh crawlable documentation was indexed for the official domain.

Observed Apr 15, 2026

Artifacts Archive

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

Self-declaredGITHUB REPOS

Extracted files

Examples

Snippets

Languages

python

Executable Examples

bash

python main.py

Docs & README

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

Self-declaredGITHUB REPOS

Docs source

GITHUB REPOS

Editorial quality

ready

Full README

AI Logs Analytics

Automated log incident analysis pipeline built with CrewAI. Parses application logs, extracts structured incidents, and generates a Markdown report.

Tech Stack

Framework: CrewAI
LLM: Llama 3.1 (8B) via Ollama (ollama/llama3.1:8b)
Validation: Pydantic
Language: Python

Architecture

The application follows a sequential two-agent pipeline:

Parse — log_analyst extracts all ERROR/WARN incidents from raw log text into structured JSON using the parse_incidents tool.
Report — report_writer analyzes the structured data, summarizes severity distribution, and generates a final Markdown report using the generate_markdown_report tool.

Prerequisites

Ollama must be running locally on http://localhost:11434
Pull the model before first run: ollama pull llama3.1:8b
Create a log file at logs/log.txt with at least 3 lines containing ERROR/WARN/INFO level entries

Project Structure

| File | Purpose | |------|---------| | main.py | Entry point; validates input, creates the crew, and kicks off the analysis | | agents.py | Agent definitions (log_analyst, report_writer) configured with the local LLM | | tasks.py | CrewAI task definitions (parse_task, report_task) with Pydantic validation | | tools.py | Custom tools: parse_incidents (log parser) and generate_markdown_report (report builder) | | pydantic_schemas.py | Pydantic models (Incident, ParsedIncidents) for strict output validation | | utils.py | Helper functions; validates that the input log file exists and is well-formed | | logs/ | Input directory; place your log file as logs/log.txt | | result/ | Output directory; final report is saved as result/incident_report.md |

Agent Roles

Log Analyst

Extracts structured incidents from raw log text. Calls parse_incidents exactly once and returns only the raw JSON result without modification.

Technical Writer

Receives parsed incidents, summarizes the analysis (counts and severity distribution), writes a brief one-sentence analysis per error, and generates the final Markdown report via generate_markdown_report.

Run

python main.py

After execution completes, the report will be saved at:

result/incident_report.md

Contract & API

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

MissingGITHUB REPOS

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-aryabchi-ai-logs-analytics/snapshot"

curl -s "https://www.xpersona.co/api/v1/agents/crewai-aryabchi-ai-logs-analytics/contract"

curl -s "https://www.xpersona.co/api/v1/agents/crewai-aryabchi-ai-logs-analytics/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.

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

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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-aryabchi-ai-logs-analytics/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-aryabchi-ai-logs-analytics/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-aryabchi-ai-logs-analytics/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-aryabchi-ai-logs-analytics/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-aryabchi-ai-logs-analytics/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-aryabchi-ai-logs-analytics/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_REPOS",
      "generatedAt": "2026-10-09T22:49:11.504Z"
    }
  },
  "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",
    "category": "vendor",
    "label": "Vendor",
    "value": "Aryabchi",
    "href": "https://github.com/aryabchi/ai-logs-analytics",
    "sourceUrl": "https://github.com/aryabchi/ai-logs-analytics",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-10-09T19:05:25.220Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-aryabchi-ai-logs-analytics/contract",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-aryabchi-ai-logs-analytics/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-10-09T19:05:25.220Z",
    "isPublic": true
  },
  {
    "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": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-aryabchi-ai-logs-analytics/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-aryabchi-ai-logs-analytics/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
  }
]