get_coupling

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

Annotations already declare readOnlyHint=true, destructiveHint=false, etc. The description adds 'Read-only' (consistent) and describes return format as JSON with specific fields, plus the TOON encoding option. No contradictions.

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 focused sentences: first states metrics and outcome, second gives use case, third provides alternative. Then additional info on read-only, return structure, and encoding option. No unnecessary words.

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?

Given no output schema, the description perfectly fills the gap by listing returned fields. It covers purpose, usage, alternative, parameter options, and encoding format. Everything an agent needs is present.

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 100% so all parameters are described. The description adds value by explaining the 'output_format' parameter's 'toon' option and its token-saving benefit, and implicitly ties 'assessment' parameter to stability filter.

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?

The description clearly states the tool computes coupling metrics (Ca, Ce, instability) per file and identifies stable vs unstable modules. It explicitly distinguishes from sibling tool get_coupling_trend by stating 'For coupling changes over time use get_coupling_trend instead.'

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?

It provides explicit usage context: 'Use to identify fragile or overly-depended-on modules.' and gives a clear when-not-to-use with an alternative tool named (get_coupling_trend).

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