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Kuass

oracle-db-mcp

by Kuass

analyze_db_health

Check Oracle database health by analyzing tablespace usage, session status, wait events, and invalid objects to identify performance and configuration issues.

Instructions

Perform comprehensive database health checks including tablespace usage, session status, wait events, and invalid objects

Args:
    include_all_invalid (bool, optional): If True, return all invalid objects. If False, limit to first 20. Default is False

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
include_all_invalidNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.1

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full disclosure burden. It does reveal the truncation behavior of invalid objects (first 20), but says nothing about whether the checks are read-only, their cost/latency on a live database, required privileges, or whether repeated calls are safe. For a tool that inspects sessions and wait events, that is a meaningful gap.

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?

Front-loaded with the action and scope in one sentence, then a compact args block. The docstring-style Args section is slightly redundant in form but every line carries information, with no filler.

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?

For a one-parameter tool this is close to adequate, and the enumerated check categories give a rough sense of what comes back. However, with no output schema and no annotations, the description should have said more about the shape of the results and the operational cost of running the checks.

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

Parameters5/5

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, and it does: include_all_invalid is explained both directions (True returns all invalid objects, False limits to the first 20) plus the default. This is exactly the semantics an agent needs to set the flag correctly.

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 names a specific verb+resource ('Perform comprehensive database health checks') and enumerates the exact check categories: tablespace usage, session status, wait events, invalid objects. That makes the purpose unambiguous and distinct from query-oriented siblings like read_query or explain_query, though it never explicitly contrasts itself with them.

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?

There is no when-to-use guidance, no prerequisites, and no mention of alternatives. The agent must infer from the name alone that this is a diagnostic entry point rather than a data-access tool, which is exactly the kind of routing information the description should supply.

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