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validate_database_integrity

Check a DBC file for bit overlaps, DLC violations, invalid DLC sizes, duplicate names, and bad min/max/scale values before using the database.

Instructions

Detect bit overlaps, DLC violations, invalid DLC sizes, duplicate names, and bad min/max/scale.

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": {
      "dbc_path": "<dbc_path>"
    },
    "name": "validate_database_integrity"
  }
}

Input Schema

NameRequiredDescriptionDefault
dbc_pathYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full burden. It never says whether the tool is read-only or repairs the problems it finds, whether it requires an existing file, or what the check output looks like — the most consequential unknowns for a validation tool. Naming the check categories is useful but does not resolve the mutate-vs-report ambiguity.

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?

One compact sentence with the enumeration front-loaded and no filler. It is efficient, though the flat list of check names gives no ordering or grouping of what matters most.

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 low-complexity one-parameter tool with no output schema, the description covers what is checked, which is the core need. It still leaves out read-only vs fixing behavior and the shape of the result, which matters for deciding whether it is safe to invoke repeatedly.

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% and the single parameter dbc_path is never mentioned in the description, so nothing clarifies that it is a filesystem path to a DBC file rather than a name or ID. The DBC-specific check vocabulary implies the domain but adds no meaning to the argument itself.

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?

A specific verb (detect) applied to an enumerated set of integrity checks (bit overlaps, DLC violations, duplicate names, bad min/max/scale), which is far more concrete than the bare name. It does not, however, distinguish itself from near-neighbors like diff_databases or inspect_database_summary, which an agent could easily confuse with a validation pass.

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 statement of when to run validation versus diffing or inspecting, no prerequisites, and no mention of what to do with the results. The agent must infer that this is a pre-commit or post-edit sanity check.

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