brand_truth_update

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

With no annotations, the description carries the full burden. It discloses a key behavioral trait: 'it writes the provided fields directly' and 'does NOT re-run the LLM extraction pipeline', which is valuable beyond the schema. However, it doesn't explicitly state that unspecified fields are left unchanged or describe return values, leaving some 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?

Three sentences, front-loaded with the core action and target. Every sentence serves a purpose: scope, key behavior, use cases, and alternative. No wasted 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?

For a 9-parameter mutation tool with no annotations and no output schema, the description gives a solid mental model: targeted edit, direct write, partial update implied, and clear alternative. It could be more explicit about unspecified fields remaining unchanged, but the description is generally sufficient for successful invocation.

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 baseline is 3. The description groups parameters by use case ('correct wording (name/description/content), fix the type/personaScope, adjust tags, or pin/unpin'), which adds a little semantic context, but it doesn't explain anything about parameters that the schema doesn't already cover.

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 'Targeted edit of an existing, known brand truth (by ID)', a specific verb+resource combination. It clearly differentiates from siblings by stating it does NOT re-run the LLM extraction pipeline and pointing to brand_truth_create for new facts.

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?

Explicitly states what to use it for: correcting wording, fixing type/personaScope, adjusting tags, pin/unpin. Provides a clear alternative: 'To capture NEW facts from prose, use brand_truth_create instead.' This gives unambiguous when-to-use vs when-not-to-use guidance.

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