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

Annotations already declare it is a mutation (readOnlyHint=false) that is neither idempotent nor destructive, so the safety profile is covered. The description adds real behavioral context beyond that: approval produces a live article with optional tags, and the decision is attributed to the connected user or, for key-only connections, the organization's primary manager. It does not say whether a dismissal is recoverable or what permissions are required, which keeps it below a 5.

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 sentences, front-loaded with the scope disambiguation before the action and outcome. The parenthetical aside is a bit dense but earns its place by preventing a common misfire; no redundant restatement of the tool name.

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?

With three fully described parameters, an output schema, and annotations covering the mutation profile, the description supplies what structured fields cannot: the effect of each decision, tag applicability, and decision attribution. Permission requirements and post-dismissal recoverability are the only notable gaps, and neither blocks a correct 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 enum values, the tag constraints, and the suggestion_id pattern are all already documented. The description echoes 'optionally tagged' (approve only) but adds no format, ordering, or edge-case detail beyond the schema. Baseline 3 is appropriate when the schema does the heavy lifting.

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?

States a specific verb and resource ('Decide on one pending knowledge suggestion') and spells out both branches: approve turns it into a live article, dismiss discards it. It also disambiguates the ambiguous phrase 'knowledge base' from Spun's product documentation and routes that case to search_knowledge, so an agent can distinguish this from kb_list_suggestions and kb_search without opening a schema.

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?

Gives clear context: use this to act on a *pending* suggestion, and use search_knowledge instead when the user wants product documentation. The schema reinforces the entry point by tying suggestion_id to kb_list_suggestions. It stops short of explicit when-not guidance for this tool itself (e.g., don't use it to edit an existing article — use kb_upsert_article or kb_retag_article).

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