list_projects

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It goes beyond a simple 'list' by thoroughly explaining the workspace selection logic, including fallback precedence and special values. This is significant behavioral nuance. It does not explicitly state that the operation is read-only, but the nature of 'listing' and the absence of any side-effect language imply safety. The description is transparent about the parameter behavior, which is the main variable in this tool.

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 efficiently structured: a one-line purpose statement followed by a bulleted list for the parameter. Each bullet is necessary and adds value, particularly the default resolution order. It avoids redundancy and front-loads the core action. The length is justified by the complexity of the parameter semantics. No unnecessary words are present.

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 that an output schema exists, return values are already covered. The description fully addresses the only parameter and its behaviors, leaving no ambiguity for an agent. It also accounts for the orchestrator's expectation by explaining the default workspace resolution, which is critical context for this tool. There are no missing pieces for an agent to correctly invoke it.

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 provides minimal information: a nullable string parameter named 'workspace' with a default of null and no descriptions. The description compensates fully by explaining three distinct cases: null (current workspace with detailed fallback order), '__all__'/'*' (all workspaces), and any other string (specific workspace). This transforms a generic parameter into a well-documented, actionable one. Schema description coverage is 0%, so this high-quality compensation is essential and well-executed.

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 opens with a clear, specific statement: 'List registered projects.' This identifies the verb (list) and resource (registered projects), which unambiguously distinguishes it from sibling tools like list_project_sessions. The additional explanation of workspace behavior reinforces the tool's scope without muddling its core purpose.

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 provides detailed guidance on the workspace parameter, including default resolution order and special values like '__all__'. However, it does not explicitly address when to use this tool versus alternatives such as list_project_sessions or portfolio_digest. The context implies usage through the purpose, but there is no explicit 'use this when...' or 'instead of...' guidance, leaving selection partly to inference.

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