reconcile_data

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

No annotations provided, so description must cover behavioral traits. It explains entity vs grouped reconciliation but omits critical details: authentication is required (auth_user_id, auth_password), data_center parameter, and any side effects or requirements.

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 focused sentences plus a critical line about usage. Every sentence adds value; no fluff.

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?

Despite having an output schema, the description doesn't hint at output structure or what the reconciliation result looks like. With 7 parameters and 14% schema coverage, the description should provide more context on optional parameters like filter_expr and expected_count.

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 14%. Description adds meaning for 'entity' and 'group_by_field' but ignores 5 other parameters (data_center, filter_expr, auth_user_id, auth_password, expected_count). Does not compensate for low schema coverage.

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?

Clear verb 'reconcile' with specific resource 'data after migration' and measurable outcome 'compare expected vs actual record counts'. Distinguishes from siblings like 'generate_reconciliation_report' by focusing on count comparison rather than report generation.

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?

States it's 'Essential for cutover day validation', which implies when to use. But lacks explicit when-not-to-use guidance or comparison to similar tools like 'find_data_anomalies' or 'query_odata'.

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