elog_search

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

With no annotations provided, the description carries full burden of behavioral disclosure. It explains key semantics: text and attributes are treated as regular expressions, date_to defaults to 23:59:59, reverse controls sort order, max_results has a server cap of 100000, and logbook defaults to '*'. It also details the exact return structure. These are non-obvious behaviors an agent needs to invoke correctly.

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 efficient: a one-sentence purpose, then a structured Arg list covering all parameters without redundancy, and a concise Returns line. Every sentence adds information – no padding. The main purpose is front-loaded, and parameter details are logically grouped.

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 8 parameters and an output schema, the description covers every parameter's semantics and the return format explicitly. It even includes defaults and edge-case behaviors (e.g., date_to time default). Nothing an agent needs to call this tool correctly is missing, and the provided output schema complements rather than replaces the 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?

Schema description coverage is 0%, so the description must supply meaning for all 8 parameters. It does so comprehensively: each parameter gets a clear explanation with examples (e.g., attribute regex syntax, date formats, use of '^…$' for exact text match, and the logic of last_days vs. explicit range). This adds value far beyond the bare schema.

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 'Search logbook entries by full text, attributes, and/or date' – a specific verb, resource, and filtering criteria. This clearly distinguishes it from sibling tools like elog_get_entry (single entry) and elog_list_logbooks (list logbooks). An agent immediately understands the tool's role and scope without needing to inspect 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?

No explicit guidance is given for when to choose this tool over alternatives. While the description implies it is for flexible searching, it does not mention that elog_get_entry should be used when an entry ID is known, or elog_get_recent_entries for recent entries. The agent must infer these distinctions from the tool names and parameters.

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