load_category

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

With no annotations, the description carries full burden for behavioral transparency. It reveals that the tool activates tools, can be called early, and supports multiple categories. However, it does not disclose whether the operation is idempotent, what side effects occur (e.g., resetting previous loads), or expected return behavior (e.g., success confirmation).

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 concise at 3 sentences. It front-loads the primary action, then usage timing, then category list, and ends with multi-load capability. No unnecessary words.

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 annotations and output schema, the description covers core purpose, usage, and categories but omits expected return value or permission requirements. For a simple 1-parameter tool, this is adequate but not fully complete.

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 coverage is 100% (parameter described). The description adds semantic context by listing each category and its associated Microsoft services (e.g., 'users' for Azure AD/Entra ID). This enriches the bare schema description beyond the baseline of 3.

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: 'Activate Graph API tools for a resource category.' This specific verb+resource combination is distinct from sibling tools like list_categories or graph_explain_*, making it easy for an AI agent to select correctly.

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 explicit usage guidance: 'Call this as soon as the user's intent is clear — do not wait for confirmation.' It also notes that multiple categories can be loaded for tasks spanning areas. However, it does not explicitly contrast with list_categories, though the purpose is distinct.

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