Advanced Web Search Skill

Objective: To conduct a thorough and effective web search to gather the information needed to solve a task. This skill is designed to find precise, actionable solutions rather than generic tutorials.

Instructions:

When you invoke this skill, you must follow this multi-round research protocol. You may conduct up to three rounds of searching.

Round 1: Initial Broad Search & AI Overview

1. •Query Generation: Formulate a concise, high-level search query that captures the core of the problem.
2. •Execute Search: Perform a Google search with your query.
3. •Extract Google AI Overview: Immediately prioritize and extract the full text of the Google AI Overview summary. This often contains a highly condensed and accurate solution.
4. •Initial Analysis: Briefly review the top 3-5 search results to get a general sense of the problem space.

Round 2: Deep Dive with High-Specificity Queries

1. •Refined Query Generation: Based on your initial findings, create one or more highly specific, low-frequency search queries. Include specific error messages, library names, and function names.
   • •Good Example: "flask sqlalchemy 'InterfaceError' (sqlite3.InterfaceError) invalid command"
   • •Bad Example: flask database error
2. •Source Prioritization: Add site:github.com or site:stackoverflow.com to your queries to prioritize results from these platforms, as they are more likely to contain actionable code.
3. •Deep Link Exploration: Open the top 3 search results (excluding any you've already reviewed) and analyze their content in detail. Look for code snippets, configuration examples, and explanations of the underlying problem.

Round 3: Verification and Alternative Solutions

1. •Query for Alternatives: If the previous rounds did not yield a definitive solution, search for alternative approaches or common pitfalls.
   • •Example Query: "python file upload alternative to flask-uploads"
2. •Quality Control: Throughout the process, actively filter out any search results that mention "Terminal Bench" or other benchmark-related terms to avoid contaminating your solution.
3. •Synthesize Findings: After completing your search rounds, create a consolidated summary of your findings. This summary should include:
   • •The most promising solution(s).
   • •Key code snippets or commands.
   • •A list of the URLs you found most helpful.

Example Usage:

Task: "I'm trying to connect to a PostgreSQL database with Python, but I'm getting a psycopg2.OperationalError: could not connect to server error."

Search Process:

• •Round 1 Query: python psycopg2.OperationalError: could not connect to server
  • •Action: Extract the Google AI Overview, which likely suggests checking the database connection string, firewall rules, and whether the database server is running.
• •Round 2 Query: "psycopg2.OperationalError" connection refused site:stackoverflow.com
  • •Action: Analyze the top StackOverflow answers, looking for code examples of correct connection strings and pg_hba.conf configurations.
• •Round 3 Query: python postgresql connection best practices
  • •Action: Look for articles on connection pooling or using context managers to ensure connections are properly closed.
• •Synthesis: "The psycopg2.OperationalError is likely due to an incorrect connection string or a firewall issue. The most common solution is to ensure the host, port, user, and password are correct in the DSN. This [StackOverflow link] provides a canonical example of a correct connection string. Additionally, one should check that the PostgreSQL server is running and that port 5432 is open on the firewall."