get_standup_data

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

With no annotations provided, the description carries the full behavioral disclosure burden. It clearly states what data is returned, how activity is scoped (previous working day), how open items are bucketed, and that credentials come from the environment or logged-in gh/glab sessions rather than arguments. It does not mention failure modes or rate limits, but the key operational behavior is transparent.

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 three sentences, front-loads the core purpose and return contents, and closes with an important credential-safety note. No sentence is wasted, and the structure is easy to scan.

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 explains both what the tool returns and where credentials come from, which is essential given no output schema and no annotations. It does not document exact output formatting or failure behavior, but the return contents are described in enough detail for an agent to know what to expect. The optional parameters are fully covered by the schema.

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 schema already documents all three parameters well. The description adds useful context about credential sourcing, which relates to host and provider behavior, but it does not add significant parameter-level semantics beyond what the schema provides. Baseline 3 is appropriate.

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 states a specific verb ('Collect') and resource ('merge-request-based standup data from GitLab or GitHub'), and enumerates the exact returned content: previous working day activity, open MRs/PRs bucketed by state, pending reviews, and failed pipeline error lines. This is unambiguous and fully distinguishes the tool's purpose even without sibling tools to compare against.

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 description implies the tool is for collecting standup-related data from GitLab or GitHub, but it does not explicitly state when to use it versus alternatives or when not to use it. There are no sibling tools and no direct usage conditions, so the usage context is only implied by the tool's name and return-value description.

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