work_log

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds substantial behavioral detail: newest-first ordering, inclusion of both user and human entries, short-summary format, limit defaults and maximum, has_more for older items, and the fact that an id query returns a full entry. This goes well beyond the annotations without contradicting them.

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 core behavior is front-loaded in the first sentence, and each paragraph adds distinct value: usage, parameter semantics, and search keywords. The keyword list is slightly long but serves multilingual and paraphrase matching, so it earns its place. Minor redundancy such as restating 'look up L-' in the keywords is acceptable given the concise structure.

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 no output schema, the description does a good job describing return shape: entries have ids, are short summaries, newest first, and has_more indicates older results. It does not spell out every field of a full entry or the exact JSON shape, but for a list/query tool with no required parameters and clear behavior, what is provided is sufficient for correct invocation.

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 0%, so the description must carry the full parameter burden, and it does. It explains limit (default 10, max 50), query (searches operation and input text; an id like L-000042 returns the full entry), and engine (filters by calc|math|units|stats|dates|data). This gives an agent everything needed to use each parameter correctly.

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 and resource: 'Recent computations from the work log (yours and the human's), newest first, each with its id.' It clearly frames the tool as a read-only history/reuse tool, which distinguishes it from sibling calculators like calc or math and from data_list, which handles registered data rather than computation history.

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 gives explicit use cases: 'reuse a number computed earlier instead of recomputing or remembering it, or to look one up by id.' It also explains filtering behavior with query and engine. It does not explicitly name sibling alternatives for new calculations, but the 'instead of recomputing' phrasing makes the intended context clear.

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