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dave1362

RCA-MCP Connector

rca_analysis_batch

Analyze multiple incidents in batch using a single RCA model to identify per-incident root causes and rank common root causes across incidents.

Instructions

Run RCA analysis over a batch of incidents using the same model. Returns a summary with per-incident results and cross-incident root cause ranking.

Args: params (BatchAnalysisInput): model_id, incidents (list of payload dicts, max 20)

Returns: str: JSON with per_incident results, cross_incident_ranking

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Description states it returns a summary, which adds context beyond annotations. 'Run' implies mutation, consistent with readOnlyHint=false. But it does not disclose auth requirements (token param not explained), error behavior, or side effects. Annotations already cover basic safety profile.

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

Conciseness4/5

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

Four sentences front-loading purpose and return type, with an Args/Returns block. Efficient but the block could be integrated into prose. No redundancy.

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

Completeness3/5

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

Covers max incidents, return JSON structure, and model usage. Lacks prerequisites (auth token), when to batch vs single, and error handling. Output schema exists but not described. Adequate but not comprehensive given tool complexity.

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

Parameters2/5

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

Schema description coverage is 0%, so description must compensate. It lists 'model_id, incidents (list of payload dicts, max 20)' but omits token and client_id. The Args block adds minimal meaning beyond schema field descriptions. Insufficient to make parameters fully understandable.

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?

Description clearly states 'Run RCA analysis over a batch of incidents using the same model' with specific verb and resource, and distinguishes from siblings like rca_analysis_run (single incident) and rca_analysis_compare.

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

Usage Guidelines2/5

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

Description provides no guidance on when to use batch vs single analysis, no exclusions, and no mention of alternatives among the many sibling tools. The max incidents constraint (20) is mentioned but not framed as usage guidance.

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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