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

Annotations declare readOnlyHint=true and openWorldHint=true, and the description is consistent with these, describing analysis and reporting rather than mutation. It adds useful context beyond annotations: mentions 'Inputs are validated server-side' and describes the deliverable as 'structured, audited,' giving a sense of what the agent can expect. It does not disclose rate limits or pagination, but that is less critical given read-only behavior and the presence of 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?

The description is verbose and marketing-oriented, including a French subtitle, a reference case, and multiple example questions. Every sentence does not earn its place; the 'Reference case: Acme SaaS' and the marketing phrase 'Gapup agent-payable C-suite expertise (CFO)' add noise. While it is front-loaded with a clear title, the bulk is unnecessarily long and repetitive.

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 nested parameters (entity, ledgerContext) and no output schema, so the description should compensate by explaining how to construct inputs and what the deliverable contains. It gives some idea of output ('structured, audited deliverable') but leaves parameter semantics unaddressed and does not mention output format or fields. Given the complexity and low schema coverage, this is insufficient.

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 only 25% (only 'async' has a description). The description does not explain the meaning of 'entity', 'ledgerContext', or 'focus' beyond saying 'send the documented case fields,' which is vague. It does not compensate for the poor schema coverage, leaving the agent to infer parameter semantics from field names and nesting. This is a significant gap.

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 it is a GL recon reconciler that returns a structured, audited deliverable, and provides specific examples of what it can do (root cause analysis, ranking by materiality, month-end close reports). This distinguishes it from sibling finance tools like budget_variance_ai or working_capital, though the multiple verbs (identify, run, generate) make the core action slightly diffuse. Still, it is specific and focused on GL reconciliation.

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 gives strong contextual usage via example questions ('Identify the root causes...', 'Generate a month-end close reconciliation report...'), implying when to use the tool. However, it does not explicitly name alternatives or state when not to use it, so it falls short of a 5. The use cases are clear enough for an agent to recognize relevant scenarios.

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