Audit receipt chain

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

No annotations are provided, so the description must carry the behavioral disclosure burden. It does disclose the main checks performed (presence, integrity, Merkle continuity), which is helpful. However, it does not mention whether the operation is read-only, how errors or failures are reported, or what the output format looks like, leaving notable gaps for a tool with no annotation support.

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 consists of two concise sentences that front-load the main purpose and then add relevant behavioral detail. Every sentence contributes meaningful information, with no redundancy or filler.

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?

With one parameter, no output schema, and no annotations, the description gives a good overview but lacks critical information about the return value or how audit results are reported. It says 'reports Merkle chain continuity' but does not specify the structure or success/failure semantics, making it incomplete for a tool that produces a non-obvious report.

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?

The input schema already provides 100% coverage for the single 'receipts' parameter, including that it is an array of receipt objects in order. The description adds context about the audit being a chain and checking hashes, but does not provide additional parameter-level details beyond what the schema already states, so the baseline of 3 applies.

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's function with a specific verb ('Audit') and resource ('chain of receipts against the APEX PSI ledger'), and elaborates on the scope by mentioning hash presence, integrity, and Merkle chain continuity. This distinguishes it from sibling tools like 'verify' and 'seal' by focusing on a multi-receipt chain audit rather than single operations.

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 when to use the tool (auditing receipt chains against the ledger) but does not explicitly state when to prefer it over alternatives like 'verify' or 'seal'. It lacks explicit exclusions or alternative tool references, so usage guidance is only implied through the described purpose.

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