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metro_logs

Reads console logs from a React Native app via Metro CDP debugger. Auto-discovers the debugger URL or accepts a given one. Optionally saves logs to a file for bug evidence.

Instructions

Reads console logs from a React Native app via the Metro CDP debugger. If webSocketDebuggerUrl is omitted, auto-discovers via metro_apps and uses the first connected app. Reports which app was chosen. Pass saveTo to also write the console timeline to a file for evidence (e.g. attach to a bug).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
webSocketDebuggerUrlNoCDP WebSocket URL from metro_apps. Omit to auto-discover.
portNoMetro port for auto-discovery (default 8081)
durationMsNoHow long to collect logs in milliseconds (default 3000)
maxLogsNoMaximum number of log entries to return (default 100, keeps most recent)
saveToNoOptional file path; writes the console timeline (one line per entry: [level ts] text) for evidence.
Behavior3/5

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

With no annotations, the description must bear the transparency burden. It discloses auto-discovery behavior, app selection reporting, and file saving. However, it omits prerequisites (e.g., app must be connected) and side effects, and does not detail output format.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with three sentences, front-loading the core purpose. Every sentence adds value without redundancy, making it efficient for agent consumption.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 5 optional parameters and no output schema, the description covers main functionality, auto-discovery, and save option. However, it lacks details on output format, error handling, and prerequisites, leaving some gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds value by explaining that omitting webSocketDebuggerUrl triggers auto-discovery and that saveTo writes a timeline file for evidence, which goes beyond the schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool reads console logs from a React Native app via Metro CDP debugger. It specifies the verb 'reads' and the resource 'console logs', distinguishing it from sibling tools like metro_network and metro_state.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides guidance on using auto-discovery vs. providing a URL, and mentions the optional saveTo parameter for evidence. However, it does not explicitly compare this tool to siblings or state 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.

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