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Lynn-hh

io.github.Lynn-hh/armguard-mcp

error_recovery

Clear the robot's error state following a collision or reflex response. This action resets the arm's operational status, enabling continued, safe motion.

Instructions

Clear the robot's error/reflex state (e.g. after a collision reflex). May require human approval. Refused while the software e-stop is active (reset it first).

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
okYes
dataNo
messageYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare it is a non-read-only, non-idempotent, non-destructive, open-world operation. The description adds critical behavioral context beyond the annotations: it may require human approval and is refused under an active software e-stop.

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?

Two concise sentences, front-loaded with the primary action and immediately followed by the key approval and e-stop preconditions. No unnecessary repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no parameters, an existing output schema, and annotations covering the mutation safety profile, the description supplies the remaining operational context: purpose, approval possibility, and e-stop interlock. Nothing essential for correct invocation is missing.

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

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so there are no parameter semantics to explain. Per the rubric, a zero-parameter tool has a baseline of 4.

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?

States a specific verb and resource: "Clear the robot's error/reflex state," with a concrete example (collision reflex). It also distinguishes itself from e-stop reset by noting it is refused while the software e-stop is active and that reset must happen first.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says when to use it (after a collision reflex) and when it will not work (while the software e-stop is active), and points to the prerequisite action (reset e-stop first). The human approval caveat further clarifies invocation conditions.

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