IT & Software Engineering

Generates a unique 8-character UUID (Universally Unique Identifier) each time the tool is called.

Turn your raw platform data into instant, board-ready insights with this AI SQL Analyst Agent that automatically translates plain-English questions into optimized queries, clean tables, and compelling visual reports. Perfect for growth, product, and ops teams, it uncovers trends, user behavior, and agent performance in seconds—no SQL expertise required. How to use this SQL Agent This assistant helps you analyze your AI agent platform data using plain English. You ask business questions (e.g. “Top agents by completed runs last 7 days?”), and it turns them into SQL, runs them on your Postgres database, and returns clean tables (and charts if you ask). How to connect your agent to your data You can connect your database in two main ways: MCP database tool (preferred) Configure an MCP “database” tool with your Postgres connection (host, port, database, user, password, SSL). Use a read‑only analytics user with SELECT on your tables. Once configured, just ask questions like “Show daily runs by status for the last 30 days” and I’ll query live data and respond with results. Postgres: SQL query tool Configure this tool with the same Postgres connection. Then use me as a SQL generator: say “Generate SQL (don’t execute) to compute error rate per agent over the past month.” I’ll return an optimized query you paste into the Postgres tool yourself. You can bring results back here for interpretation or chart generation. You don’t need to know SQL; you just describe what you want analyzed. I handle query design, debugging, and summarizing insights.

Asabe researches companies and prospects using LinkedIn and web scraping tools, then generates comprehensive pre-call reports to help sales reps prepare for meetings and strategize their approach effectively.

Get meeting transcripts from Google Drive and summarise. Will look for a topic based on the title of the Google Docs in Google Drive. This is for anyone who wants to retrieve and summarise content from Google Drive.

Converts HTML content into an HTML file and uploads it to cloud storage, returning a URL to the file.

This tool takes an HTML string and converts it into a high-resolution PNG image using a headless Chromium browser via Playwright. It’s designed to reliably generate consistent, pixel-accurate screenshots of dynamic HTML layouts — perfect for carousels, slide decks, social posts, or any HTML-based visual asset.

Calcu Later parses numeric requests, writes minimalist Python code, executes calculations, and returns results in a flat, precise tone with dry humor. It restates requests simply, breaks down tasks into austere steps, and presents results with minimal commentary, avoiding excitement and embellishment.

Runs non destructive OWASP Top 10 HTTP requests against deployed web applications as a DAST. Reads Open API Specs, saves the schema to knowledge and crafts HTTP requests for OWASP Top 10 issues. Generates a report of potential vulnerabilities on endpoints.

Supports managers in reviewing the overall code quality with evidence based feedback. Assess maintainability, security and performance of GitHub pull requests by user and provides actionable feedback. Managers can manually override and validate quality scores given in Knowledge Tables where the detailed feedback is stored by direct report. The agent will manager validated scores to self improve assessments.

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This workforce consists of the Test Commander and the Test Striker, along with a "Target Agent". Replacing the current target agent lets you automatically test it

Assess GitHub pull requests for a particular user in the last 7 days (or custom date) on code quality. Provides a quantitative quality score out of 100 and looks at maintainability, performance and security. Provides detailed feedback with filenames and line numbers. The PRs are published to a Knowledge Table for manual assessment.

Gets the first N pull requests from a GitHub repository as an array of diffs.

Takes a string and encodes it into Base64 encoding. While LLMs can do this, it costs a lot of credits and takes a long time. Using Python instead, this will be a lot quicker and cost Actions, not LLM Credits. Save money, save time, win win!

Takes a Base64 encoded string and decodes it. While LLMs can do this, it costs a lot of credits and takes a long time. Using Python instead, this will be a lot quicker and cost Actions, not LLM Credits. Save money, save time, win win!

Built for the Liam Ottley × AAA Accelerator Hackathon The AskDB agent empowers business and support teams to query live PostgreSQL data through natural language in Slack—automating insights, reducing L2/L3 dependencies, accelerating decisions, and driving efficiency and cost savings across the organization. Documentation: https://drive.google.com/file/d/1rf8mBjWKs51NYY-62mi3mtv0bpHv7Tus/view?usp=sharing Explanation: https://drive.google.com/file/d/1fpnh2iWgkaeOBmvb3Jx436d7UdDUdgOe/view?usp=sharing Agent-Demo: https://drive.google.com/file/d/11uv7suJCrWZyV9ODupy5CpZCxVRvzIbb/view?usp=sharing

Automatically analyze and prioritize Freshdesk tickets using AI—no manual triage required. Priority Analyzer receives tickets via webhook, evaluates business criticality using AI, and assigns the correct priority level (Low, Medium, High, or Urgent). It analyzes system criticality, affected users, revenue impact, and time sensitivity, then updates the ticket and posts its analysis as an internal note. Why It Matters: Support teams miss urgent issues buried in ticket queues, causing delayed responses to critical problems. Automated AI triage ensures urgent issues get immediate attention. Unlike traditional systems that over-emphasize impatient customers, LLMs analyze request urgency with nuance based on actual business impact. How It Works: Webhook triggers on ticket creation → AI analyzes content → Determines priority → Updates ticket priority via API → Posts analysis note. Fully automated in seconds. Built for the Liam Ottley × AAA Accelerator Hackathon by TicketCloserAI.com

Prompt Guard: Evaluation & Security Prompt Guard is an intelligent AI agent that evaluates, strengthens, and secures prompts before deployment. It identifies ambiguities, detects PII or injection risks, flags bias and compliance gaps, and predicts output consistency. Each evaluation provides scores, rationales, and three optimized versions (Streamlined, Hardened, High-Impact), with smart revision tools, sentiment checks, and automated redaction. Prompt Guard empowers AI developers and organizations to deploy safe, high-performing, and compliant prompts—fast, measurable, and secure. Built for the *Liam Ottley × AAA Accelerator Hackathon.* 📘 User Guide & Technical Documentation ▶️ Demo

AEO Assistant analyzes any public url (or pasted HTML) and returns everything you need to improve answerability in AI Answer Engines with detected entities & intents, recommended schema.org types, and validated JSON-LD you can paste directly into your webpage. What it does: • Extracts page context with robust fallbacks • Detects ecommerce signals (Product), local signals (LocalBusiness), procedural content (HowTo/FAQ) and articles (BlogPosts). • Generates clean JSON-LD (Schema markup) • Includes install Advisor for Shopify/WordPress/Webflow/custom setups How to use: Enter a URL (or paste rendered HTML). Review schema types & copy JSON-LD. See Advisor tab to install. No user PII is stored; the tool only reads the URL/HTML you provide. Demo: https://cleva.bot/aeo-assistant Why it matters: Clear structured data improves machine understanding. This tool lets content teams quickly generate schema markup. (Built by Cleva.Bot for the Liam Ottley × AAA Accelerator Hackathon)

Database management agent assists non-profits with database selection, data migration, quality control, reporting, and data standardization to maintain reliable data infrastructure.

An expert technical documentation specialist that creates comprehensive, well-structured documentation from various sources including websites, files, codebases, and APIs. Specializes in generating user guides, API documentation, technical specifications, and developer resources.