suggest_variable_names

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

No annotations are supplied, so the description carries the full burden. It discloses one useful trait — that source files are not modified — but says nothing about the ranking criteria for 'evidence', determinism, side effects, or what the caller receives back (there is no output schema).

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 front-loaded sentence with no filler and the non-destructive guarantee stated up front. It is efficient, though the extreme brevity starts to work against a tool with a deeply nested input.

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?

The input is an array of objects with nine required fields each, none described anywhere, and there is no output schema and no annotations. Against that complexity, one sentence leaves the agent guessing about both what to supply and what it gets back.

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 description coverage is 0% and the two parameters (variables, context) are undocumented, so the description should compensate. It hints that inputs carry evidence and ranking (matching the nested 'evidence', 'confidence', and 'suggestions' fields) but never explains what a variable record must contain or what 'context' is for.

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 names a specific operation ('Return evidence-ranked names for inferred variables'), which distinguishes it reasonably from infer_variables (inference) and validate_variable_map (validation). However, it never explicitly names those siblings, so an agent must infer the division of labor from the naming.

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?

There is no explicit when-to-use or when-not-to-use guidance, and no mention of infer_variables or split_rom as upstream steps. The only usage-adjacent signal is 'without modifying source files', which is a behavioral note rather than routing guidance.

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