Web Tool Fallback Strategy

When to Use This Skill

Apply this skill when all web-reading tools (read_webpage, search_web) fail simultaneously with unknown errors during a research or information-gathering task.

Recognition Criteria

Confirm this pattern before applying fallbacks:

• Multiple web tool calls have failed (not just one isolated failure)
• Errors are unknown/unexpected (not expected 404s or rate limits that can be handled normally)
• The information is still needed to complete the task

Fallback Procedure

Critical: execute_code_sandbox may also fail during system-wide issues. Always be prepared to immediately fall back to run_shell if sandbox execution returns errors.

Step 1: Attempt Alternative Sources

Before abandoning web access, try these alternatives:

1. Alternative URLs:

   • Archive.org / Wayback Machine versions
   • Alternative domains (e.g., .org instead of .com)
   • Different subdomains or paths

2. Simplified Requests:

   • Try reading just the domain root
   • Remove query parameters from URLs
   • Try HTTP instead of HTTPS (or vice versa)

# Example: Generate alternative URL formats
original_url = "https://example.com/research/report?id=123"
alternatives = [
    "https://example.com/research/report",
    "http://example.com/research/report?id=123",
    "https://web.archive.org/web/*/https://example.com/research/report"
]

Step 2: Use execute_code_sandbox for Embedded Knowledge

Step 2: Use execute_code_sandbox for Embedded Knowledge (May Fail)

When web access is unavailable, generate content from reliable embedded knowledge. Note: execute_code_sandbox can fail during cascading system issues—if it returns errors, immediately proceed to Step 2b.

code = '''
# Generate structured information from embedded knowledge
evaluation_frameworks = {
    "Kirkpatrick Model": ["Reaction", "Learning", "Behavior", "Results"],
    "Bloom's Taxonomy": ["Remember", "Understand", "Apply", "Analyze", "Evaluate", "Create"],
    "SMART Criteria": ["Specific", "Measurable", "Achievable", "Relevant", "Time-bound"]
}

# Create comprehensive reference material
for framework, levels in evaluation_frameworks.items():
    print(f"## {framework}\\n")
    for i, level in enumerate(levels, 1):
        print(f"{i}. {level}")
    print()
'''

If execute_code_sandbox returns any error (unknown error, timeout, execution failure):

• Do not retry execute_code_sandbox multiple times
• Immediately proceed to Step 2b (run_shell fallback)
• Document the sandbox failure in your Research Access Notes

- Established frameworks and methodologies
- Standard best practices
- Well-documented technical concepts
- Historical information that doesn't change frequently

### Step 2b: Fall Back to run_shell if execute_code_sandbox Fails
### Step 2b: Fall Back to run_shell if execute_code_sandbox Fails (REQUIRED)

**When to use**: execute_code_sandbox returns any error OR fails to produce output within reasonable time.

**Action**: Immediately switch to run_shell with direct Python execution. Do not continue attempting execute_code_sandbox.

1. **Use run_shell with direct Python execution** (simplest, most reliable):

1. **Use run_shell with direct Python execution**:
   ```bash
   python3 -c "print('content from embedded knowledge')"

2. Use heredoc for multi-line scripts:

   python3 << 'EOF'
   # Your Python code here
   frameworks = {"Kirkpatrick": ["Reaction", "Learning", "Behavior", "Results"]}
   for name, levels in frameworks.items():
       print(f"## {name}")
       for level in levels:
           print(f"- {level}")
   EOF

3. Capture output to file for further processing:

   python3 -c "print('structured content')" > output.txt

Why run_shell works when execute_code_sandbox fails:

• Direct system Python execution bypasses sandbox restrictions
• No additional abstraction layer that could fail
• More reliable during cascading tool failures
• Should be your go-to when sandbox is compromised

Step 3: Create Document with Placeholder Citations

For tasks requiring formal documentation:

1. Draft the document using available knowledge
2. Mark uncertain citations clearly:

   [WEB_ACCESS_LIMITED: URL https://example.com/source could not be accessed]

3. Use placeholder format for references:

   [Reference needed: Topic - URL attempted but inaccessible]

Step 4: Document the Limitation for Stakeholders

Always create a transparent "Research Access Notes" section:

## Research Access Notes

**Access Limitation**: All web-reading tools failed simultaneously during research.

**Fallback Actions Taken**:
- [ ] Attempted alternative URLs: [Yes/No]
- [ ] Used embedded knowledge generation: [Yes/No]
- [ ] Created placeholders for citations: [Yes/No]

**Confidence Level**: [High/Medium/Low] - based on reliance on embedded knowledge vs. current web sources

**Recommendation**: Verify critical claims with current web sources when access is restored.

Decision Tree

All web tools failed?
├─ Yes → Try alternative URLs
│   ├─ Success → Complete task normally
│   └─ Failed → Can content be generated from embedded knowledge?
│       ├─ Yes → Try execute_code_sandbox (expect potential failure)
│       │   ├─ Success → Use output + document limitation
│       │   └─ Failed/Errors → **IMMEDIATELY** use run_shell + document limitation
│       └─ No → Create document with placeholders + notify Executive Director
│       └─ No → Create document with placeholders + notify Executive Director
└─ No → Handle individual failures normally

Task-Type Adaptations

Example Application

# When gathering reference materials fails
try:
    # Primary: read_webpage attempts (all failed)
    pass
except:
    # Fallback 1: Try alternative sources
    alternative_content = execute_code_sandbox(generate_from_knowledge())
    
    # Fallback 2: Create document with transparency
    document = create_with_placeholders(
        content=alternative_content,
        citation_markers="[WEB_ACCESS_LIMITED]",
        stakeholder_note="Executive Director: Web access unavailable, content from embedded knowledge"
    )

Best Practices

1. Be transparent: Always document when web access failed
2. Preserve attempt records: Note which URLs/tools failed for future reference
3. Distinguish knowledge types: Clearly separate embedded knowledge from current web-sourced information
4. Prioritize critical info: If certain information is essential and cannot be generated, escalate rather than guess
5. Enable verification: Make it easy for stakeholders to verify claims when access is restored
6. Never stack failures: If execute_code_sandbox fails once, switch to run_shell immediately—do not retry the sandbox multiple times
7. Complete all steps: Step 4 (Document Limitation) is mandatory, not optional—even if fallback succeeds