generate_worklog

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

With no annotations, the description carries the full burden. It does disclose key behavioral traits: AI enhancement is enabled by default and can be disabled, and it lists accepted date formats. It does not state whether the operation is read-only, whether it makes network calls, or that it does not post the worklog to Povio (a notable distinction given sibling tools). This leaves gaps in the agent's understanding of side effects and workflow.

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: a clear purpose sentence, then AI behavior, then date formats, then examples. It front-loads the core purpose. While the trigger examples are somewhat repetitive (many variations of the same 'wl' / 'generate worklog' phrasing), the overall layout is easy to scan and not excessively verbose.

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 tool has no output schema and no annotations, so the description must compensate. It covers the main functionality and inputs, but misses several contextual elements: it does not describe the return format/type, does not clarify default repository behavior (even though the schema mentions 'defaults to current directory'), and does not explain how this tool fits into the larger workflow (e.g., that after generating, you'd use post_worklog to submit). For an AI agent, these are meaningful gaps.

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 coverage is 100%, so the baseline is 3. The description adds value beyond the schema by expanding on date formats (e.g., '10/28/2024' (MM/dd/YYYY) and '28.10.2024' (dd.MM.YYYY) are not in the schema description) and by providing concrete trigger examples. This extra detail helps the agent construct valid inputs.

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 clear specific verb+resource: 'Generate a worklog from git commits.' It explains the process (analyzes commit messages, extracts ticket numbers, creates AI-enhanced descriptions). However, it does not explicitly differentiate itself from sibling tools like 'post_worklog' or 'generate_and_post_worklog' – it never says 'this only generates, does not post' – so it lacks explicit sibling distinction.

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?

Usage context is implied through trigger examples ('wl', 'generate worklog', 'what did I work on yesterday') and supported date formats, which tells the agent when a user request maps to this tool. However, there is no explicit when-to-use vs. alternatives guidance, such as 'use post_worklog to submit' or 'use generate_and_post_worklog to both generate and post.' The examples are helpful but not selection-oriented.

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