knowledge_autotag_suggest

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

No annotations are provided, so the description carries full burden. It discloses that only existing tags are suggested to avoid tag proliferation (tag-wildwuchs), and returns suggestions ranked by confidence with matchedTokens. This provides sufficient behavioral insight for a suggestion tool.

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 three sentences long, each serving a clear purpose: stating the algorithm and constraint, giving usage context, and clarifying a parameter's purpose. It is front-loaded with the most important information and contains no filler.

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?

The description covers the input parameters (through schema), usage context, and return format (ranked suggestions with confidence and matchedTokens). It lacks details on edge cases like empty tag pools or low-confidence results, but overall it is sufficient for an AI agent to invoke the tool correctly.

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 schema already documents all parameters. The description adds value by explaining the role of existingTags in excluding already-applied tags, but other parameters (content, projectId, limit) are already well-described in the schema. Thus, it adds moderate value beyond the schema.

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 it suggests project tags using TF-IDF against the existing pool, and explicitly says it never invents new tags. This provides a specific verb and resource, and differentiates it from sibling tools like knowledge_harvest or search.

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 advises using it when writing new doc-pages, ADRs, or flow summaries for consistent tagging. It also explains passing existingTags to exclude already-applied tags, offering clear usage context. It does not explicitly state when not to use it or mention alternatives, but the guidance is adequate.

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