failure_analysis

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

With no annotations provided, the description carries the full burden. It discloses that the tool generates three learning artifacts and saves them to team memory, which is a significant behavioral trait. It does not cover potential side effects on the task or rate limits, but the core behaviors are 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 concise, with a clear structure: purpose first, then usage condition, then output artifacts. Every sentence adds value, and there is no redundant 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?

Given the tool's complexity and the existence of an output schema, the description adequately covers when to use it and what it produces (three artifacts). It does not explain whether repeated calls are safe or affect task status, but it is sufficient for typical use.

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?

Both parameters (task_id, team_id) are described in the input schema with 100% coverage. The description adds no additional meaning beyond the schema, so 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 clearly states it analyzes failed tasks and generates three specific artifacts (antibody, vaccine, catalyst). It uses specific verbs and resources, and distinguishes itself from siblings like 'diagnose_task_failure' by emphasizing deep failure analysis and learning artifacts.

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 says to call this tool when a task permanently fails (exceeds retry limit). It does not explicitly mention when not to use it or name alternatives, but the context of deep failure analysis vs. other diagnostic tools is implied. The condition for use is clearly stated.

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