optimize_context_stream

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

The description discloses the behavior of yielding progress events and returning a list of event dicts. Without annotations, it provides basic transparency but lacks details on side effects, state changes, authorization needs, or rate limits. It does not contradict any annotations since none exist.

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 two sentences, but it omits critical information such as parameter semantics and usage context. While efficient, it sacrifices completeness for brevity.

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 complexity of a streaming pipeline tool with three parameters and no annotation support, the description is incomplete. It fails to explain the parameters, and the output example is partial, lacking full schema details. The agent would have insufficient context to use 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?

With 0% schema description coverage, the description must compensate, but it does not mention any of the three parameters (codebase_path, query, token_budget). No explanation of their meaning or role is provided, leaving the agent without guidance.

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 identifies the tool as a streaming pipeline that yields stage-by-stage progress events and returns a list of event dicts, which is specific. However, it does not explicitly state the overall optimization purpose hinted by the name, nor does it distinguish from siblings like optimize_context_batch or optimize_context_structured.

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 guidance is provided on when to use this tool versus alternatives such as optimize_context_batch or optimize_context_structured. There is no mention of prerequisites, conditions, or when not to use it.

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