Get Task History

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

Annotations already declare this as a safe, read-only, idempotent operation. The description adds valuable behavioral context beyond annotations: it returns an event timeline, computes derived metrics, triggers risk signals, and explicitly notes the API cost (2–3 requests, more for long streams). It also discloses that include_subtasks does not compute full lifecycles for subtasks due to cost. These are meaningful behavioral disclosures not captured by the structured annotations.

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 highly efficient: the first sentence defines what the tool returns, the second gives concrete use cases, and the third covers input flexibility and cost. Every sentence earns its place, and the content is front-loaded with the most important information.

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 is analytically complex with no output schema, so the description must compensate. It lists the major return components (timeline, section times, cycle time, slip days, ownership churn, risk signals) and covers input variants, disambiguation, and cost. Minor gaps remain, such as explicit error handling for missing tasks or output structure details, but the description is comprehensive enough for an AI agent to select and invoke the tool correctly.

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. However, the description adds extra semantic clarity beyond the schema: it explains how the 'project' parameter disambiguates multi-project tasks and how 'include_subtasks' returns a compact list without full lifecycles. The tool description also clarifies that the task parameter accepts GIDs, URLs, or names, with a disambiguation fallback, enriching the schema's dry specifications.

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 clearly states the tool's purpose with a specific verb and resource: 'Reconstruct a task's full lifecycle from its Asana activity stream.' It enumerates the specific outputs (timeline, section durations, cycle/lead time, reschedule history, ownership churn, risk signals), which distinguishes it from sibling tools like asana_get_task (which fetches current state) or asana_get_task_stories (which fetches stories).

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 explicitly tells when to use this tool: "Use this to answer 'why is this task late?', 'where did it get stuck?' or 'who has touched it?'." This provides clear context for usage, though it does not explicitly name alternative tools or provide when-not-to-use guidance, stopping short of a full 5.

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