aflpp.status

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

With no annotations provided, the description carries the burden of disclosure. It does reveal the mechanism (parsing fuzzer_stats and counts) and a behavioral trait (deltas since last call), suggesting a stateful operation. However, it does not disclose potential side effects, error conditions, or whether the operation is read-only, leaving some ambiguity.

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 a single sentence (16 words) that is front-loaded with the core purpose ('Get job status') and efficiently conveys the method and salient feature. No filler or redundant wording.

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?

For a simple status tool with two parameters and no output schema, the description covers the main action and the kind of data observed. However, it lacks guidance on usage in the broader workflow, expected output structure, and prerequisites (e.g., job must exist). The lack of annotations and zero schema coverage leave notable 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?

The input schema provides no descriptions for job_name or workspace, and the description only refers to 'job status' without explaining parameter formats, constraints, or how they relate to the underlying filesystem. Since schema coverage is 0%, the description needed to compensate but does not; the agent must infer meaning from parameter names alone.

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 function with a specific verb ('Get'), a defined resource ('job status'), and the method of extraction ('by parsing fuzzer_stats and queue/crashes/hangs counts'). It also highlights a unique feature (deltas since last call) that distinguishes it from siblings like `aflpp.whatsup` or `aflpp.campaign_summary`.

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 querying the status of a specific job (given job_name and workspace) and mentions that it reports deltas since last call, indicating usefulness for monitoring changes. However, it does not explicitly state when to use this tool over alternatives such as `aflpp.whatsup` (likely a broader status view) or `aflpp.campaign_summary` (overall summary). There are no exclusions or alternative recommendations.

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