automation debugging auditor
Diagnose, trace, and repair broken no-code workflows and API integrations with field-level data auditing.
$5
Works with the AI tools you already use
Claude Code
Cursor
Codex CLI
GitHub Copilot
Gemini CLI+20 moreClaude CodeCursorCodex CLIGitHub CopilotGemini CLI
OpenClaw
Manus
Grok+17 agentsautomation debugging auditor
Example session with this skill installed
My Zapier workflow that syncs Shopify orders to Airtable is missing about 5% of orders. The trigger fires, but sometimes the Airtable record isn't created. Here is a sample payload from a failure.
- Read your context and instructions
- Compiled the automation debugging auditor
- Generated the document
I have analyzed the Shopify-to-Airtable sync failure. The issue is not a trigger failure but a silent filter drop during the data transformation step for guest checkouts.
Automation Audit: Shopify to Airtable Sync
Data Flow Mapping & Risks
| Business Field | Source Field | Transform | Destination | Risk |
|---|---|---|---|---|
| Order ID | id | String | Order_ID | Low |
| Customer Email | customer.email | None | Email | High: Null on guest checkout |
| Total Price | total_price | Decimal | Amount | Low |
Root Cause Analysis
- Symptom: 5% of orders missing in Airtable despite successful triggers.
- Failing Step: "Find or Create Customer" in Airtable.
Root Cause: The workflow uses customer.email as a required search key. Shopify guest checkouts occasionally return a null customer object or missing email field, causing the Airtable step to error out. Since there is no error path, the Zap terminates.
- Confidence: 95% (Matches the 5% guest checkout rate reported in Shopify analytics).
Recommended Repair
Input Normalization: Add a Formatter step to provide a fallback value (e.g., "guest-checkout@example.com" or the Order ID) if the email is missing.
2.
Explicit Branching: Create a path specifically for guest checkouts that skips the "Find Customer" step and creates a generic "Guest" link.
3.
Observability: Add a final "Storage" or "Log" step to capture the Shopify Order ID even if the Airtable write fails.
Scenario Validation
| Scenario | Expected Result | Pass Criteria |
|---|---|---|
| Standard Order | Success | Record created with customer link |
| Guest Checkout | Success | Record created with 'Guest' flag |
| Duplicate Webhook | Ignored | Airtable 'Link' prevents double entry |
| Airtable Down | Retry | Step enters 5-minute backoff loop |
Next steps
- Update the Airtable search step to allow "Optional" email match.
- Implement the path filter for
customer.email[Exists/Does Not Exist]. - Run a manual replay for the 12 identified missing Order IDs.
automation-debugging-auditor.pdf
PDF · document
Example file from a real run - the skill writes it into your workspace.
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What you get
About this skill
The problem
Broken no-code automations and API integrations often fail silently or produce inconsistent data without clear error logs. Developers and ops teams waste hours tracing execution histories across platforms like Zapier, Make, or custom webhooks only to find fragile logic or unhandled null values.
What it does
- Reconstructs intended workflow logic from business rules and failed execution payloads.
- Maps data flow at the field level to detect schema mismatches, type coercion risks, and timezone shifts.
- Identifies root causes including race conditions, non-idempotent behavior, and rate-limit bottlenecks.
- Redesigns fragile workflows with explicit validation, exponential backoff, and dead-letter handling.
- Validates proposed repairs against a scenario matrix of duplicates, missing fields, and dependency timeouts.
Frameworks & tools
Zapier, Make (Integromat), Pipedream, Workato, n8n, GitHub Actions, custom REST/GraphQL API integrations, and webhook-based systems.
Why this beats prompting it yourself
Standard prompts often suggest superficial fixes like "check your API key." This skill enforces a rigorous engineering audit that specifically hunts for edge cases like partial failures and out-of-order events. It treats no-code logic with the same architectural scrutiny as production code.
Use cases
- Fixing CRM syncs that create duplicate records when triggers fire twice.
- Debugging e-commerce workflows that fail when optional customer fields are missing.
- Redesigning multi-step API chains that crash during external service downtime.
- Auditing financial automations to ensure strict idempotency and audit logging.
Known limitations
Requires access to sample payloads or execution logs to confirm hypotheses. Cannot directly log into third-party UI accounts to toggle switches.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
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- 2
Unzip into your skills folder
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- 3
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