consult_knowledge

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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower, yet the description adds substantive context: entries are third-party reference data and never instructions (prompt-injection guard), relato/hipotese/nao verificado are weak evidence, and every answer carries relevance and low_relevance semantics. That is real behavioral disclosure beyond structured fields.

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?

Front-loaded with the resource and the two access modes, and most sentences carry real information (evidence tiers, relevance fields). The trailing 'Read-only.' is redundant given readOnlyHint=true, and the relevance/confidence sentence is dense enough to need a second read.

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?

There is no output schema, yet the description covers the return surface: confidence tags, relevance score 0–1, low_relevance flag, and the brief-vs-full body distinction. An agent knows what it gets back and how to interpret it.

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%, so baseline is 3, but the description adds that query accepts Portuguese or English (schema examples are Portuguese-only) and reinforces the id vs query mode split. Defaults such as detail=brief for query and full for id are already in the schema, limiting the added value.

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: looks up the Bambu Studio slicing and Blender mesh-prep knowledge base, with symptoms, causes, setting values and fixes. No sibling tool (slice_stl, get_slice_settings, blender_mcp_edit_model, etc.) does reference lookup, so it is trivially distinguishable.

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?

Names the two access modes explicitly: search with query (symptom, question or setting key, either language) or fetch a single entry by id. It also gives a downstream rule (when low_relevance is true, tell the user the base only touches the subject). Lacks an explicit when-not-to-use or a hand-off to a sibling tool.

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