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apsolut

dbeaver-mcp

by apsolut

inspect_sequences

Compare database sequences against table column maxima to detect when sequences need resetting after bulk imports or manual inserts.

Instructions

Compare serial/identity sequences to MAX(column). needs_reset is true when the table is ahead of the sequence (typical after a dump or manual INSERT).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesConnection name or id
tableNoOnly this table
schemaNoSchema (default: connection schema or public)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.6.1

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It does add meaningful context by explaining what needs_reset indicates, which is a key output behavior. Yet it does not explicitly state that the operation is read-only or side-effect-free, which an agent would need to assume from 'Compare' rather than be told.

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?

The description is two sentences with no filler, front-loading the primary action. It is concise and to the point, though it could arguably be more structured (e.g., separate output semantics), but the efficiency merits a high score.

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?

The description explains the core behavior (needs_reset flag) but does not specify the full return format—e.g., whether it returns a list of sequences, columns included, or only problematic ones. Since there is no output schema, the description should be more explicit about the result shape, leaving a gap for the agent.

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?

The input schema is fully documented (100% coverage), with each parameter described. The description does not add any extra meaning about the parameters beyond what the schema already provides, so it earns the baseline score for a well-covered schema.

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 states a specific action ('Compare serial/identity sequences to MAX(column)') with a clear resource and distinguishes it from sibling fix_sequences by its diagnostic nature. The added explanation of needs_reset reinforces the tool's purpose, leaving no ambiguity about what it does.

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?

The description provides a concrete scenario ('typical after a dump or manual INSERT') that tells an agent when this tool is useful. However, it does not explicitly mention alternatives or when not to use it, such as pointing to fix_sequences for resetting, so it falls short of the top tier.

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