can-engineering-mcp

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query_decoded_signals

Decode selected CAN signals from trace logs using a DBC file; return summary statistics, anomalies, and downsampled time series or raw decoded rows.

Instructions

Decode requested signals across a trace; aggregation='summary' returns min/max/mean/std/anomalies plus a downsampled time series, otherwise up to max_rows raw decoded rows.

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": {
      "log_path": "<log_path>",
      "dbc_path": "<dbc_path>",
      "signal_names": "<signal_names>"
    },
    "name": "query_decoded_signals"
  }
}

Input Schema

Name	Required	Default
`dbc_path`	Yes
`end_time`	No
`log_path`	Yes
`max_rows`	No
`start_time`	No
`aggregation`	No	summary
`signal_names`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 3, 2026

TDQS

B3.3/5.0

Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It does disclose the mode-dependent return shape well (min/max/mean/std/anomalies plus a downsampled series versus up to max_rows raw rows), but it omits time units for start_time/end_time, what happens when a signal is absent from the DBC, and any performance or error behavior.

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?

A single tight sentence with the core action front-loaded and the two output branches presented as a clear either/or. Nothing is wasted.

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 7-parameter tool with 0% schema coverage, no annotations, and no output schema, the description is under-specified on inputs even though the return-shape disclosure is solid. The five undocumented parameters leave real gaps an agent would have to guess at.

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% across 7 parameters, and the description only adds meaning for two of them: aggregation's summary-versus-raw switch and max_rows as a cap on raw rows. log_path, dbc_path, signal_names, start_time, and end_time receive no explanation of format, units, or expected values anywhere.

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 gives a specific verb and resource: 'Decode requested signals across a trace.' It also names the two operating modes via the aggregation parameter, which separates it from siblings like summarize_trace_log and filter_and_export_trace without naming them directly.

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?

It implicitly tells the agent how to choose between summary and raw-row output through the aggregation value, but it never states when to prefer this tool over summarize_trace_log or filter_and_export_trace, and it gives no prerequisites such as the DBC needing to match the log.

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