Assess a changeset against workspace intelligence

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

Annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false) are fully consistent with the description, which adds valuable context: the tool never certifies a change as safe, and it clarifies that 'none' is not a safety approval. The decision semantics are detailed, disclosing the mechanical enforcement logic. No contradictions found.

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?

The description is fairly long but well-structured using bullet points for decision semantics and a JSON block for the return value. The purpose is front-loaded in the first sentence. While each sentence adds value, some redundancy exists (e.g., the return JSON is described both in text and in a code block). Still, it remains readable and informative.

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 the absence of an output schema, the description provides a detailed return JSON structure with field descriptions, ensuring the agent understands what to expect. The tool's single parameter is fully covered by schema and description additions. The decision semantics are thoroughly explained, leaving no ambiguity about the tool's behavior.

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 input schema has 100% coverage, describing the paths parameter with type, items, minLength, and maxItems. The description adds context beyond the schema, specifying 'repo-relative or absolute paths' and 'in the proposed change (1-200)', which helps the agent understand acceptable input. However, it does not explain how paths are resolved or validated further.

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's purpose: 'Evaluate a SET of file paths…against workspace.json fragility and co-change history, and return a mechanical enforcement decision.' It uses a specific verb ('evaluate') and resource ('changeset'), distinguishing it from sibling tools like workspace_get_file_context (single file context) and workspace_list_fragile_files (listing fragile files).

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?

The description explains decision semantics and when each applies (e.g., deny, warn, annotate, none). It implies usage for proposed changes but does not explicitly state when not to use or mention alternatives like the sibling tools. The context signals and sibling names provide implicit guidance, but the description could be more explicit about exclusions.

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