abstract_stream

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

With no annotations, the description must fully disclose behavior. It states the tool returns a reverse-chronological event tail and is a wrapper, but omits details like authorization, side effects, or rate limits. The output schema may cover return structure, but behavioral traits remain unclear.

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 short and to the point, using only two sentences. However, it sacrifices parameter explanations for brevity, making it less effective.

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 output schema exists (not shown), the description clarifies the core purpose but lacks parameter details and usage context. For a simple 'tail' tool, it is nearly adequate, but the missing parameter semantics leave 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 0%, so the description should explain parameters. It does not mention log_id or max_len, leaving their semantics and impact ambiguous. The default for max_len hints at tail length, but no explicit guidance is provided.

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 returns a tail of events in reverse-chronological order, answering 'what happened recently in this log?'. This specific verb-resource-purpose distinguishes it from sibling tools like abstract_variants or abstract_dfg, which compute different representations.

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 usage for quickly viewing recent events without computing variants or models, offering a lightweight alternative. However, it lacks explicit when-to-use or when-not-to-use guidance compared to other abstract tools.

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