Captured network payloads

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

Annotations already declare readOnlyHint=true, and the description adds useful behavioral context beyond that: payloads are captured 'while we browsed' and bodies are clipped to 2000 characters. This tells the agent what to expect and prevents surprise from truncated output.

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?

Three short sentences, no filler, with the main action and resource front-loaded. The body truncation note is placed early and earns its place because it materially affects how the agent interprets results.

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 description gives a clear purpose, a usage cue, and one important output trait (truncation), but it leaves parameter semantics and return structure unexplained. For a no-output-schema tool with 0% parameter coverage, this is usable but not fully complete.

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 description coverage is 0%, so the description needed to compensate by explaining kind, limit, and urlContains, but it does not name or define any of them. The enum values are partially self-explanatory and the phrase 'Bodies clipped to 2000 chars' relates to output, not parameters.

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 uses a specific verb ('List') with a concrete resource ('JSON / RSC responses LinkedIn's own web app fetched') and names the relevant endpoint families (Voyager REST, GraphQL, flagship-web). This clearly distinguishes it from sibling tools like debug_page_text or debug_find, which operate on page text rather than captured network payloads.

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 phrase 'This is how you discover the endpoints and shapes behind the hiring dashboard' gives a clear, actionable use case. It does not explicitly state when not to use it or name alternative tools, but the intended discovery workflow is strongly implied.

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