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:

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:

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:

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:

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