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cascade-fail-recovery

Keep document creation moving when web searches and page retrieval repeatedly fail. The skill preserves the original task, uses the model’s existing knowledge, and clearly identifies information that could not be checked against external sources.

OriginalShow the original description

Handle cascading data retrieval tool failures by falling back to embedded knowledge generation

See how to install

Good for

  • Continue drafting after repeated web retrieval failures
  • Preserve task requirements during network errors
  • Mark information that could not be externally verified

Files included (2)

  • SKILL.md3.0 KB
  • .skill_id35 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

Cascade Failure Recovery

Purpose

When multiple data retrieval tools (read_webpage, search_web) fail in succession, immediately fall back to generating content from embedded knowledge rather than attempting repairs or abandoning the task. This preserves task context and ensures completion.

When to Apply

Use this pattern when you observe:

  • 2+ consecutive failures from data retrieval tools
  • Network/access errors preventing web content retrieval
  • Risk of task abandonment due to tool errors

Recovery Procedure

Step 1: Recognize Cascading Failure

Identify the failure pattern:

Iteration N: read_webpage failed - connection error
Iteration N+1: search_web failed - timeout/unavailable
Iteration N+2: [risk] Agent may abandon task or switch objectives

Step 2: Preserve Task Context

Before switching strategies, explicitly restate the original objective:

ORIGINAL OBJECTIVE: [Restate the core task goal]
CONTEXT PRESERVED: [Key requirements, constraints, deliverables]

Step 3: Invoke Fallback Strategy

Immediately switch to embedded knowledge generation:

  1. Acknowledge the limitation: Note that external data sources are unavailable
  2. Activate internal knowledge: Use pre-trained knowledge relevant to the task
  3. Generate content: Use write_file to create the deliverable from available knowledge
  4. Document the fallback: Note in the output what information could not be verified externally

Step 4: Execute write_file

Generate the required document:

# Fallback to generating from embedded knowledge
write_file(
    path="output/document.md",
    content="[Generate content from internal knowledge base]"
)

Example Application

Scenario: PACT Act veterans benefits document needed, but web access failing

Wrong approach (observed failure):

Iter 11: read_webpage failed - access error
Iter 12: search_web failed - unavailable
Iter 13: [ABANDONED] Switched to unrelated musician payroll task

Correct approach (with this skill):

Iter 11: read_webpage failed - access error
Iter 12: search_web failed - unavailable
Iter 13: CASCADE FAIL DETECTED - invoking fallback
Iter 14: write_file - generate PACT Act document from embedded knowledge
      - Note: "External verification unavailable; content based on training knowledge"

Guidelines

  1. Threshold: Trigger fallback after 2 consecutive retrieval failures
  2. No endless retries: Do not attempt more than 1 repair/retry cycle
  3. Preserve objective: Never switch to unrelated tasks when tools fail
  4. Transparency: Clearly mark any content that lacks external verification
  5. Document limitations: Note what could not be verified due to tool failures

Related Skills

  • write-file-fallback: Generate documents when data sources unavailable
  • task-context-preservation: Maintain objective continuity through errors

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