auto_detect_workflow

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

No annotations are provided, so the description carries full behavioral disclosure burden. It says 'detect and suggest' but doesn't state whether this triggers side effects, whether autoExecute requires confirmation, or what happens when autoExecute is true. Does not clarify if it writes to any store or just returns suggestions.

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 a single, efficient sentence that communicates the core purpose without excess. While under-specified in other dimensions, conciseness itself is good—no wasted words or irrelevancies.

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?

This is a moderately complex tool with 5 parameters, no annotations, and no output schema, yet the description offers only a single high-level sentence. It doesn't describe the suggestion output format, behavior of autoExecute, or how optional context parameters influence detection. For a tool with zero annotation coverage and no output schema, this is insufficient.

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 100%, so the schema documents all 5 parameters. The description mentions analyzing 'natural language input,' which maps to userInput, but adds minimal value beyond schema text. It implies currentFile/projectPath/projectType are contextual signals but doesn't explain how they influence detection. Baseline 3 is appropriate given full schema coverage.

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 states a clear verb+resource: 'detect and suggest workflows based on natural language input.' It distinguishes the purpose from siblings like manage_workflows and list_workflows, which handle workflow CRUD. However, it lacks specificity on what 'suggest workflows' produces or how it differs from start_workflow, which could cause selection ambiguity.

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?

No explicit guidance on when to use this tool vs alternatives. Given many sibling tools (start_workflow, list_workflows, get_workflow, manage_workflows), the description provides no context on when detection/suggestion is preferred over direct workflow management. No exclusions or alternative references are given.

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