mark_important

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the effect on relevance scores (multiply/divide by 10) and implies mutation ('mark'), but doesn't cover permissions, rate limits, side effects (e.g., impact on other entities), or response format. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

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 a single, efficient sentence that front-loads the core action ('mark entity as important') and includes key behavioral detail ('boosting its relevance score'). There is zero waste or redundancy, making it highly concise and well-structured.

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 annotations, no output schema, and a mutation tool with 4 parameters, the description is minimally adequate. It covers the purpose and basic effect but lacks details on usage context, behavioral traits, and return values. The high schema coverage helps, but for a tool that modifies data, more guidance would improve completeness.

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 thoroughly. The description adds no parameter-specific information beyond what's in the schema (e.g., it doesn't explain 'memory_zone' or 'auto_create' further). Baseline 3 is appropriate when the schema does the heavy lifting, though no extra value is added.

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 verb ('mark') and resource ('entity in knowledge graph') with the specific action of 'boosting its relevance score'. It distinguishes from siblings like 'create_entities' or 'update_entities' by focusing on importance marking rather than creation or general updates. However, it doesn't explicitly differentiate from all siblings like 'merge_zones' or 'move_entities' in terms of scope.

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 provides no guidance on when to use this tool versus alternatives like 'update_entities' (which might handle importance) or 'create_entities' (with auto_create parameter). It mentions the effect on relevance scores but doesn't specify use cases, prerequisites, or exclusions, leaving the agent to infer usage context.

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