Log Tax Research

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

With no annotations provided, the description carries the full burden. It discloses the primary behavioral outcome: 'Builds a searchable knowledge base of everything the agent has researched,' indicating the persistent, cumulative nature of the log. It does not discuss edge cases like overwriting or editing, but for a record-keeping tool, the stated behavior is adequate.

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 exactly four sentences, each earning its place: the primary action, the trigger condition, the outcome, and concrete examples. It is front-loaded with the purpose and contains zero 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?

The description covers purpose, usage, outcome, and examples, which is sufficient for a logging tool with 100% schema coverage. It does not mention return values or error handling, but that is acceptable since the tool's primary function is to record data, not to return complex results.

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 100%, so the baseline is 3. The description itself does not add parameter-level meaning, but the schema already documents each parameter thoroughly (e.g., 'What was learned', 'Brief topic name'), so no compensation is needed.

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 a specific verb 'Record' and resource 'findings from tax research,' immediately distinguishing this from calculation tools. It also provides three concrete examples (SR&ED eligibility, treaty rates, CCA class) that clearly scope the tool as a research-logging tool among many calculation and knowledge-management 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 sentence 'Use this whenever you investigate a tax topic, look up a rule, or explore how something works' explicitly states when to use the tool. It does not mention when not to use it or name alternatives, but the trigger condition is clear and differentiates it from calculation-oriented siblings.

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