Longhand

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

No annotations are provided, so the description carries the full burden. It mentions that the tool returns 'compact summaries by default' and allows for 'full detail' with verbose=true, which adds some behavioral context. However, it does not disclose critical traits such as whether this is a read-only operation, potential rate limits, authentication needs, or what 'inferred projects' means in practice, leaving significant gaps.

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 highly concise and front-loaded: two sentences that efficiently convey the tool's purpose, filtering options, and output behavior. Every sentence earns its place by providing essential information without redundancy or fluff.

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 tool has 4 parameters with 50% schema coverage, no annotations, and no output schema, the description is moderately complete. It covers the basic purpose and output modes but lacks details on behavioral traits, parameter semantics for 'keyword' and 'category', and return values. For a browsing tool with no structured support, it should do more to compensate for these gaps.

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 50% (only 'limit' and 'verbose' have descriptions). The description adds meaning by explaining that 'keyword' and 'category' are used for browsing and that 'verbose=true' returns 'full project rows including aliases, keywords, languages JSON', which compensates partially for the low coverage. However, it does not detail the semantics of 'keyword' or 'category' beyond their names, so the value added is moderate.

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: 'Browse inferred projects by keyword, category, or recency' specifies the verb (browse) and resource (inferred projects) with filtering criteria. It distinguishes from siblings like 'match_project' or 'search' by focusing on browsing rather than matching or general searching, though the distinction could be more explicit.

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 implies usage through the mention of filtering options (keyword, category, recency) and output modes (compact vs. verbose), but does not explicitly state when to use this tool versus alternatives like 'match_project' or 'search'. It provides some context but lacks clear guidance on exclusions or specific scenarios.

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