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ABAPilot

ABAPilot

by NicoHern
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

sap_lookup_error

Analyze SAP error messages using T100, SAP Help, web, and SAP Notes to identify root causes. Get ranked results with documentation links.

Instructions

Analyze a SAP error message using all available external knowledge sources. Queries: T100 message table, SAP Help Portal, web search (SAP community, StackOverflow), SAP Notes (if S-user configured), and previously learned error patterns. Use this AFTER getting dump/syslog data to understand root cause. Returns ranked results from multiple sources with links to documentation.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "error_message": "<error_message>"
    },
    "name": "sap_lookup_error"
  }
}

Input Schema

NameRequiredDescriptionDefault
contextNoOptional additional context: transaction code, program name, or description of what was happening when the error occurred.
sourcesNoOptional list of sources to query. Defaults to all. Values: t100 (SAP messages), sap_help (documentation), web (community/StackOverflow), sap_notes (SAP Notes), learned (previously seen patterns).
error_messageYesThe error message to analyze. Can include SAP message codes like 'ME 003', dump error texts, or any error description from SAP.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.2

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden and does substantial work: it discloses multi-source aggregation, the S-user prerequisite for SAP Notes, and ranked output with documentation links. It omits latency/cost implications of fanning out to web search and any privacy implication of sending error text to external services, but the core behavior is transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four compact sentences, each earning its place: purpose, source list, usage timing, and return behavior. The most decision-relevant constraint ('Use this AFTER getting dump/syslog data') is front-loaded, and the prose contains no filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers what it does, the implied input context (dump/syslog), and the return shape ('ranked results with links to documentation') in the absence of an output schema. It does not specify no-result behavior or failure modes when a source is unavailable, which would make it fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with well-documented parameters (including the sources enum values and the 'ME 003' error_message example), so the baseline is 3. The description reinforces source semantics by listing the same five sources and ties the context parameter to 'dump/syslog data,' but adds no syntax or format detail beyond what the schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb-resource pair ('Analyze a SAP error message') and enumerates the exact knowledge sources (T100, SAP Help Portal, web search, SAP Notes, learned patterns), making the tool's scope concrete. It further distinguishes itself from sibling data-acquisition tools by stating it is used 'AFTER getting dump/syslog data,' separating it from tools like sap_read_dumps and sap_lookup_t100.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit timing guidance ('Use this AFTER getting dump/syslog data to understand root cause'), giving an agent a clear trigger condition for when this tool is the right choice. However, it does not name exclusions or direct the agent to a specific alternative when this tool is not appropriate, stopping just short of fully explicit routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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