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

With no annotations, the description carries the full burden. It clearly implies read-only behavior (audit feed, history) and explains the nature of the data (decisions with reasons, profit, etc.) and the three routing categories. It does not explicitly state 'read-only' or mention any side effects, but for a 'get' tool that is acceptable. It adds meaningful context about what the data contains, though it omits pagination or ordering details beyond what the schema mentions.

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 dense paragraph but is front-loaded with the core purpose and then systematically covers use cases, content, and differentiation. Each sentence contributes, though it could be slightly more concise. The structure is logical, moving from what it is to what it contains to how to use it and how it differs from siblings.

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?

The tool has 3 parameters, no output schema, and no nested objects. The description compensates well by explaining the content of the returned decisions (reason, profit, cost, freshness) and the routing categories. It does not explicitly describe the return format (e.g., array of objects) or error conditions, but the description is sufficiently complete for an agent to understand what data it will receive and how to use it.

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%, so the baseline is 3. The description adds significant semantic value by explaining the meaning of the routing enum values (AUTO_RUN, TEE_UP, REFUSE_AND_SURFACE) with examples, and by describing the context of the decisions (reason, profit, freshness). It also reinforces the default limit and max, which are in the schema, but the overall explanation goes well beyond mere repetition.

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 states a very specific verb ('get') and resource ('decision ledger' / Freedom Engine decision history), and elaborates what it returns: auto-run, teed-up, and refused decisions with reasons, profit, cost, and freshness. It explicitly contrasts with get_command_center_items, making the purpose unmistakable and distinct among siblings.

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 explicit usage scenarios ('Use for "what did the engine do today"...') and names the alternative tool (get_command_center_items) along with what it does NOT provide (the decision audit trail). This gives the agent clear guidance on when to use this tool vs. the sibling.

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