Load CSV or TDMS test runs, automatically picking up nearby reference.csv and limits.json, then return a run_id and channel overview for traceable analysis.
Load a test run (CSV or TDMS). reference.csv / limits.json next to the file are picked up automatically. Returns a run_id and an overview of the channels.
| Name | Required | Description | Default |
|---|---|---|---|
| run_path | Yes | ||
| limits_path | No | ||
| reference_path | No |
Changes observed during successful MCP inspections.
v0.1.3Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and partially meets it: it discloses automatic sidecar discovery and the return payload (run_id + channel overview). It does not cover failure modes, format limitations, or whether the run is cached/held open for later calls.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences, front-loaded with the core action, then sidecar behavior, then return value. Every sentence carries distinct information with no padding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so the description correctly summarizes the return value (run_id and channel overview). Combined with the sidecar auto-discovery note, an agent has enough to invoke it, though error and format edge cases are absent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate, and it largely does: run_path maps to the CSV/TDMS file, while reference.csv and limits.json are named in prose, explaining what limits_path and reference_path are for and that they are auto-detected. Syntax/format details for the paths remain unstated.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('Load') and resource ('test run (CSV or TDMS)'), so an agent immediately knows this ingests run data. It doesn't explicitly distinguish itself from siblings like run_analysis or verify, but the loading semantics are unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is only implied — the sidecar note ('reference.csv / limits.json next to the file are picked up automatically') hints that explicit paths are optional, which is useful context. There is no explicit when-to-use statement or naming of alternatives such as run_analysis.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.