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Nery2004

POS Support MCP Server

by Nery2004

search_similar_incidents

Find past incidents matching a text query using Jaccard similarity, with optional branch or terminal filters to locate relevant support cases.

Instructions

Find incidents using deterministic local Jaccard text similarity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
branch_codeNo
terminal_codeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It usefully reveals that the similarity is deterministic and local, which are meaningful behavioral traits. However, it does not clarify what 'local' means, whether results are sorted, or whether this is a read-only operation, leaving important behavior unexplained.

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?

The description is a single, tight sentence with no filler. It conveys the core mechanism and distinguishes the tool from simple incident listing, making every word earn its place.

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

Completeness2/5

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

For a search tool with four parameters and no annotations, the description is too sparse. It omits how branch_code and terminal_code scope the search, what the default limit means, how results are ranked, and when this tool should be preferred. The output schema may document the return shape, but the behavioral and usage context remains incomplete.

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 the description must compensate, but it only references text similarity and does not explain the query, limit, branch_code, or terminal_code parameters. The parameter names are suggestive but not descriptive, and the description adds no insight into how they affect the search.

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

Purpose4/5

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

The description states a clear verb ('Find incidents') and resource, and adds a distinctive method ('deterministic local Jaccard text similarity') that separates it from typical listing or retrieval tools like list_incidents or get_incident. It could be stronger by explicitly naming the sibling it is not, but the core purpose is unambiguous.

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

Usage Guidelines3/5

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

The description implies this is for finding textually similar incidents rather than exact-match retrieval or listing, but it does not provide explicit guidance on when to choose this tool over list_incidents or get_incident. No alternative tools or exclusion criteria are mentioned.

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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