update_kc_instructions

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

With no annotations provided, the description carries the burden and explicitly discloses the destructive/replacing behavior ('Replaces, does not append') and the observable effect ('Verified to change the output'). This is strong behavioral disclosure, though it omits permission requirements or error scenarios.

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?

Two tight sentences in the first paragraph state the purpose and key behavioral distinction; the second paragraph adds valuable domain context. No filler or repetition, making it highly efficient.

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?

For a simple two-parameter update tool, the description covers what is overwritten, that it replaces rather than appends, and why it matters. Since an output schema exists, return value details are not required. A mention of idempotency or prerequisites would round it out, but the current content is largely sufficient.

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 0%, but the description adds meaning to 'instructions' by explaining they control SQL generation (grain, dedup keys, etc.), which goes beyond the bare field name. However, it provides no additional detail about the format or constraints of either parameter, and knowledge_cluster_id is only implicitly identified.

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 uses a specific verb ('Overwrite') and resource ('knowledge cluster's active instructions'), and clearly states 'Replaces, does not append' to distinguish from append-style updates. It differentiates from sibling tools like update_kb_instructions by targeting a knowledge cluster rather than a knowledge base.

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?

Provides clear context for when to use: it is 'high leverage' and steers the SQL generated by the Data Engineering agent, with concrete impact areas (grain, dedup keys, null handling, dialect, idempotency). It does not explicitly name alternatives or exclusions, but the context strongly implies its purpose.

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