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querying-gpt52

@costiash/CognivAgent
4
0

Queries GPT-5.2 for high-reasoning code analysis, root-cause bug fixing, and complex coding questions. Provides P0-P3 prioritized analysis reports, architecture audits, and security reviews with configurable reasoning effort (none/low/medium/high/xhigh). 400K context, 128K output.

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SKILL.md

name querying-gpt52
description Queries GPT-5.2 for high-reasoning code analysis, root-cause bug fixing, and complex coding questions. Provides P0-P3 prioritized analysis reports, architecture audits, and security reviews with configurable reasoning effort (none/low/medium/high/xhigh). 400K context, 128K output.
allowed-tools Read, Grep, Glob, Bash

Querying GPT-5.2

Queries GPT-5.2 for deep code analysis, root-cause bug fixing, and complex technical questions. Leverages GPT-5.2's 400K context window and extended reasoning capabilities to provide comprehensive analysis with P0-P3 prioritized findings.

Quick Reference

GPT-5.2 provides three specialized capabilities via standalone scripts:

Script Purpose Use Case
gpt52_query.py General queries Complex coding questions, algorithm design, concept explanations
gpt52_analyze.py Code analysis Pre-merge reviews, architecture audits, security scans
gpt52_fix.py Root-cause fixes Bug debugging that addresses underlying issues (not symptoms)

Key Features:

  • 400,000 token context window (analyze large codebases)
  • 128,000 token output limit (comprehensive responses)
  • Configurable reasoning effort (none/low/medium/high/xhigh)
  • Structured P0-P3 prioritization for findings
  • Aug 2025 knowledge cutoff

Scripts

gpt52_query.py

General-purpose queries with high reasoning capabilities.

Usage:

python .claude/skills/querying-gpt52/scripts/gpt52_query.py \
  --prompt "How should I implement retry logic with exponential backoff?" \
  --reasoning-effort high \
  --timeout 300 \
  --output-format markdown

Arguments:

Argument Required Default Values Description
--prompt Yes - string The question or request
--reasoning-effort No high none/low/medium/high/xhigh Reasoning depth
--timeout No 300 float Max wait time in seconds
--output-format No markdown markdown/json Output format

Example:

# Ask about Python async patterns
python .claude/skills/querying-gpt52/scripts/gpt52_query.py \
  --prompt "What are the best practices for handling asyncio.CancelledError?"

# Complex algorithm design
python .claude/skills/querying-gpt52/scripts/gpt52_query.py \
  --prompt "Design a rate limiter using token bucket algorithm" \
  --reasoning-effort xhigh

gpt52_analyze.py

Comprehensive code analysis for single files or complete projects.

Usage:

python .claude/skills/querying-gpt52/scripts/gpt52_analyze.py \
  --target "app/core/" \
  --focus-areas "security,performance" \
  --analysis-type comprehensive \
  --timeout 600 \
  --output-format markdown

Arguments:

Argument Required Default Values Description
--target Yes - path File or directory to analyze
--focus-areas No all security/performance/architecture/testing/quality/all Analysis dimensions (comma-separated)
--analysis-type No comprehensive quick/comprehensive/deep Analysis depth
--timeout No 600 float Max wait time in seconds
--output-format No markdown markdown/json Output format

Example:

# Security audit of API endpoints
python .claude/skills/querying-gpt52/scripts/gpt52_analyze.py \
  --target "app/api/" \
  --focus-areas "security" \
  --analysis-type deep

# Quick quality check before merge
python .claude/skills/querying-gpt52/scripts/gpt52_analyze.py \
  --target "app/services/new_feature.py" \
  --analysis-type quick

gpt52_fix.py

Root-cause bug fixing (NOT monkey patches).

Usage:

python .claude/skills/querying-gpt52/scripts/gpt52_fix.py \
  --target "app/api/endpoints.py" \
  --issues "TypeError: 'NoneType' object is not subscriptable on line 45 when session expires" \
  --fix-scope root_cause \
  --timeout 600 \
  --output-format markdown

Arguments:

Argument Required Default Values Description
--target Yes - path File or directory containing the issue
--issues Yes - string Detailed problem description (include error messages, stack traces)
--fix-scope No root_cause root_cause/minimal/comprehensive Fix approach
--timeout No 600 float Max wait time in seconds
--output-format No markdown markdown/json Output format

Example:

# Fix a concurrency bug
python .claude/skills/querying-gpt52/scripts/gpt52_fix.py \
  --target "app/core/session.py" \
  --issues "Race condition in session cleanup: multiple cleanup tasks running simultaneously causing KeyError"

# Fix with full stack trace
python .claude/skills/querying-gpt52/scripts/gpt52_fix.py \
  --target "app/services/" \
  --issues "$(cat error.log)" \
  --fix-scope comprehensive

When to Use

Use this skill for tasks requiring extended reasoning and deep analysis:

Code Analysis

  • Pre-merge code reviews
  • Architecture audits across multiple files
  • Security vulnerability scanning
  • Performance bottleneck identification
  • Technical debt assessment

Root-Cause Debugging

  • Complex bugs requiring tracing through call chains
  • Race conditions and concurrency issues
  • Memory leaks or performance degradation
  • Architectural flaws causing repeated issues

Complex Questions

  • Algorithm design and optimization
  • Framework integration strategies
  • Best practices for specific patterns
  • Trade-off analysis for technical decisions

When NOT to Use

Avoid this skill for:

  • Simple queries - Use Claude directly for straightforward questions
  • Real-time streaming - GPT-5.2 doesn't support streaming responses
  • Tool calling - GPT-5.2 via Responses API doesn't support function calling
  • Quick fixes - For obvious typos or simple bugs, direct editing is faster
  • Tasks requiring MCP tools - Use standard Claude Code capabilities

Limitations

File Size Constraints

  • 500KB maximum per file
  • 2MB total for all files in analysis
  • Files exceeding limits are excluded automatically

Security Restrictions

  • System directories blocked: /etc, /usr, /bin, /sbin, /var, /root
  • .env files automatically excluded (prevents secret exposure)
  • Path traversal attacks prevented

Output Constraints

  • Output truncated at 100,000 characters
  • JSON output available for programmatic parsing
  • Markdown output optimized for human readability

See Also

  • @CAPABILITIES.md - GPT-5.2 model specifications, reasoning effort levels, file limits
  • @PROMPTS.md - System prompt documentation with P0-P3 dimension descriptions
  • @WORKFLOWS.md - Step-by-step checklists for analysis and fixing workflows