dd-analyse-sap

SAP Log Analysis — SAP-Specific Extensions

This skill extends dd-analyse-core's analysis with SAP-specific grouping and context. It runs only when INTEGRATION_TYPE = SAP.

Input: /tmp/dd-analysis/analysis.json (from dd-analyse-core) /tmp/dd-analysis/summary.json (accumulated counters — SAP categories already extracted) Output: Updated /tmp/dd-analysis/analysis.json with sap_integration field

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SAP Log Tag Prefixes

These tags are specific to SAP integrations and supplement the core tag reference:

Tag	Source	Level	What it means
SAP-WARN	SAP Connector errorHandling.ts	Warning	SAP returned error messages (code "E")
SAP-Error	SAP Connector errorHandling.ts	Debug/Warning	Failed to extract SAP messages, or failed to log error to entity
SAP-DATA	SAP Connector sapUtilities.ts	Debug	Raw SAP response data
SAP-Filter	SAP Connector utilities.ts	Debug	SAP OData filter string

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How SAP Categorisation Works

The streaming accumulator (accumulator.py) already categorises SAP issues during the fetch phase. SAP-related categories in summary.json follow these patterns:

Category pattern	What it means
SAP HTTP <NNN>	SAP returned an HTTP error with status code NNN
SAP ERROR · <detail>	SAP-ERROR or SAP-FATAL with first 60 chars of message
SAP <NNN> · Record lock	SAP error NNN where "already being processed" in message
SAP <NNN> · Invalid time range	SAP error NNN with start/finish time mismatch
SAP <NNN> · Future date	SAP error NNN with future actual date
SAP <NNN> · <detail>	Other SAP returned error with code NNN
SAP-WARN (other)	SAP warning that didn't match specific patterns
Integration · <detail>	Integration error or connector failure

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Step 1 — Extract SAP Categories from Summary

import json

with open('/tmp/dd-analysis/summary.json') as f:
    summary = json.load(f)

with open('/tmp/dd-analysis/analysis.json') as f:
    analysis = json.load(f)

# Filter SAP-related categories from the accumulated summary
sap_categories = {}
sap_total = 0

for category, data in summary.get('categories', {}).items():
    is_sap = (
        category.startswith('SAP ') or
        category.startswith('SAP-') or
        category.startswith('Integration ·')
    )
    if is_sap:
        sap_categories[category] = data
        sap_total += data['count']

# Sort by count descending
sorted_sap = sorted(sap_categories.items(), key=lambda x: x[1]['count'], reverse=True)

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Step 2 — Extend the Analysis Object

Add the sap_integration field with SAP-specific detail. Do NOT re-merge into top_issues — dd-analyse-core already built top_issues from ALL categories (including SAP ones) in the accumulated summary. Re-adding would double-count.

analysis['sap_integration'] = {
    "total": sap_total,
    "categories": [
        {
            "label": cat,
            "count": data['count'],
            "severity": data.get('severity', 'warn'),
            "samples": data.get('samples', [])
        }
        for cat, data in sorted_sap
    ],
    "work_orders": summary.get('work_orders', []),
    "affected_steps": summary.get('affected_steps', []),
    "affected_flows": summary.get('affected_flows', []),
}

# Write updated analysis
with open('/tmp/dd-analysis/analysis.json', 'w') as f:
    json.dump(analysis, f, indent=2)

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Handoff

SAP analysis complete. → Proceed to dd-report/SKILL.md to format and deliver.