mimic_ai_knowledge_read

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

Annotations already indicate safe read-only behavior. Description adds value by naming the specific file (ds-knowledge.json), the two return modes (all entries vs single entry), and the semantic difference between VERIFIED and CANDIDATE entries. No contradictions.

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?

Four focused sentences with no redundancy. First sentence states purpose, second gives usage context, third explains result interpretation, fourth describes return options. Every sentence earns its place.

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 simple read operation with one optional parameter and no output schema, the description fully covers usage (start of run, mode handling), return behavior (full object or single entry), and integration hints (direct use vs confirming check). No major gaps.

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%, providing baseline of 3. Description elaborates by explaining that pattern_key returns a single entry and gives an example pattern ('metric/kpi'), adding useful context 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?

Clearly states the action ('Read'), the resource ('Mimic AI knowledge file (ds-knowledge.json)'), and provides context that distinguishes it from siblings like mimic_ai_knowledge_write (write) and mimic_discover_ds (discovery by other means).

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 recommends calling 'at the start of every HTML-to-Figma run' and explains how to handle VERIFIED vs CANDIDATE entries. Does not explicitly name alternatives but context and sibling tools provide indirect guidance.

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