maltego_explain_scores

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. The description adds behavioral detail: returns deterministic, human-readable rationale with specific factors (sources, connectivity, type rarity, enriching properties). It does not contradict 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 plus clear args list, no redundancy. Efficient structure with key information front-loaded.

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 single parameter and simple output (Markdown), the description covers purpose, parameters, and return value. Missing edge cases (e.g., invalid entity ID) but complete for typical use.

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 0%, but the input schema's parameter description is minimal ('Entity id to score (e.g. 'n0').'). The tool description repeats this and adds no additional meaning or examples. Baseline is adequate but not enhanced.

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 explains how intelligence-quality scores were derived, using specific verbs and resource ('Explain how an entity's intelligence-quality scores were derived'). It distinguishes from sibling explain tools like 'maltego_explain_entity' and 'maltego_explain_transform' by focusing specifically on scores.

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 understanding score derivation but does not explicitly state when to use this tool over alternatives like 'maltego_explain_why' or 'maltego_score_entity'. No guidance on when not to use or prerequisites.

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