Andru Revenue Intelligence

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

Annotations already declare readOnlyHint=true and openWorldHint=true, indicating safe read operations with potentially incomplete data. The description adds valuable context about what types of memories are available (episodic facts, semantic patterns, procedural habits) and the business domains covered, which goes beyond the annotations. No contradictions with annotations exist.

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 appropriately sized and front-loaded with the core purpose in the first clause. The second sentence adds useful filtering context without redundancy. While efficient, it could be slightly more structured for optimal clarity.

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 the tool's complexity (querying accumulated insights with filtering), annotations cover safety and data completeness, and the schema fully documents parameters. The description provides good context about memory types and content, though without an output schema, it doesn't detail return values. It's mostly complete but could benefit from more explicit behavioral context.

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%, with all parameters well-documented in the schema. The description mentions filtering by memory type and business domain, which aligns with the schema but doesn't add significant meaning beyond it. The baseline of 3 is appropriate given the comprehensive schema coverage.

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 queries accumulated stakeholder understanding with specific content types (metrics, deal patterns, account history, decisions, behavioral insights) and mentions filtering capabilities. It distinguishes from siblings by focusing on 'revenue memory' rather than other tools like get_account_plan or get_capability_profile.

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 implies usage for querying learned insights about a founder, but doesn't explicitly state when to use this tool versus alternatives like get_memory_history or get_founder_context. No exclusions or clear alternatives are provided, leaving usage context somewhat implied rather than explicit.

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