get_decision_stats

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds context by explicitly stating 'Read-only' and detailing the return JSON structure (total, active, invalidated, by_type, by_source, sessions_mined), which adds value beyond 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: first gives high-level purpose, second provides return format and read-only hint. Every word earns its place; no unnecessary information.

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?

Tool has no parameters and no output schema; description fully describes the return JSON structure with specific fields. The read-only nature is clear. For a zero-parameter stats tool, this 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?

No parameters defined (empty input schema). Schema coverage is 100% (no params to cover). Baseline for 0 params is 4; description does not need to explain parameters.

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?

Description clearly states it provides an overview of the decision knowledge graph with specific metrics (total, active, invalidated, etc.). It distinguishes from sibling tools like get_decision_timeline or get_decision_clusters by focusing on aggregate stats.

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?

Description implies usage for getting a high-level view of institutional knowledge via 'Shows how much institutional knowledge is captured.' but does not explicitly state when to use vs alternatives or provide exclusion criteria. Among many read-only sibling tools, this one is specific to stats.

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