Update Rows

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

Annotations already flag destructiveHint=true, but the description adds substantial context: updates are 'Recorded in tanOS audit_log,' empty filters are rejected, and unknown columns are reported by name. This goes beyond the binary annotations to explain real behavioral safeguards.

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 well-structured with Summary, Args, Returns, Examples, and Error Handling sections, front-loaded with the core purpose. It is lengthier than minimal, but every section provides useful information relative to the tool's complexity.

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?

Given nested filters, two systems, and no output schema, the description compensates by documenting the return format and error behaviors. It leaves no major gaps for invocation, though exact output semantics (e.g., 'affected' meaning) are left to the schema-less return description.

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 covers 100% of parameters, but the description adds value with examples of filter structures, a clarification that 'filters must not be empty,' and an explanation of the project enum. While the Args list largely repeats schema descriptions, the examples and additional constraints improve semantic clarity.

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 opens with 'Update rows matching a filter, in any table in either system,' which specifies the verb (update), resource (rows in any table), and scope (two systems). This differentiates it from specialized siblings like baatjie_update_todo, making the purpose unambiguous.

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?

It clearly implies general-purpose use ('in any table in either system') and includes a critical safety guideline: 'an unfiltered update is refused rather than rewriting the whole table.' However, it does not explicitly name alternatives or when-not-to-use scenarios, so it stops short of a 5.

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