mimic_ai_knowledge_read

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

Annotations already declare readOnlyHint and idempotentHint. Description adds detail on exactly what the knowledge store contains and how the format parameter affects output ('structured data' vs 'DESIGN.md markdown string'). No contradictions with annotations.

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-loading the main purpose, followed by parameter detail. No unnecessary words; every sentence is informative.

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?

Given no output schema, the description fully explains return contents (named categories) and the alternative format outcome. Tool is simple (1 optional param), so description is complete.

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%, baseline 3. Description adds value by explaining the purpose of each enum value: 'json' returns structured data, 'design_md' returns a markdown string for documentation/handoff. This goes beyond the schema description.

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 the tool loads the knowledge store and enumerates its contents (component recipes, layout data, DS gaps, rules, meta stats). It distinguishes from sibling tools like mimic_ai_knowledge_write and provides a usage recommendation ('Call at the start of a session').

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 advises when to call ('at the start of a session') and why (to see what has been learned). Does not list exclusions or alternatives, but the sibling context (e.g., write tool) implies when not to use it.

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