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

With no annotations, the description carries the full behavioral burden. It adds useful context about what each dependency is for (Node as official spine-core runtime for validation and previews, CLI for editable .spine export), but does not disclose whether it executes commands, what output format to expect, how failures are reported, or whether it is safe to run repeatedly.

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?

A single sentence front-loads the verb and object, with parentheticals that add meaningful context about each checked component. No filler or redundant phrasing.

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?

For a simple 0-parameter diagnostic tool with no output schema, the description identifies what is checked but says nothing about the expected result (e.g., pass/fail per dependency, report format, or next steps). An agent lacks a sense of what a successful or failed invocation returns.

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?

The tool takes zero parameters, so the baseline is 4. There are no parameter meanings to clarify, and the empty schema leaves nothing unaddressed.

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 ('Check') and resource ('toolchain'), then enumerates the components checked (Python deps, Node, Spine editor CLI). None of the sibling tools perform environment or dependency diagnostics, so the purpose is unambiguous and well differentiated.

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 tool diagnoses the environment before running pipeline tools. There are no explicit when-to-use conditions, prerequisites, or alternatives named. An agent can infer the context but gets no guidance on when this check is required versus optional.

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