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Amodh2022

flutter-bridge-mcp

by Amodh2022

capture_read

Retrieve filtered logs from the background capture buffer with options for tag, package, level, and content filters, and optionally stop the capture after reading.

Instructions

Query the background capture buffer with the same filters as read_logs.

Args: stop: also end the capture after reading.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagNo
stopNo
limitNo
packageNo
containsNo
min_levelNoV

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

B3/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only mentions the 'stop' argument's side effect of ending capture, but does not disclose whether reading is destructive, whether a capture must be active, or what happens if the buffer is empty. This is minimal transparency for a tool with no annotation safety hints.

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 very concise, with a clear purpose sentence and a single argument note. It is front-loaded with the core action and contains no fluff. Every word adds value, making it an excellent example of conciseness.

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

Completeness2/5

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

For a tool with six parameters, no annotations, and an output schema present, the description is far too brief. It omits preconditions (e.g., capture must be started), parameter semantics for most fields, and any behavioral details beyond the stop flag. This makes it incomplete for reliable invocation.

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

Parameters2/5

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

Schema coverage is 0%, so the description must explain parameters. It explicitly covers only 'stop', while 'tag', 'limit', 'package', 'contains', and 'min_level' are implied via 'same filters as read_logs'. This indirect reference is not sufficient for an agent that may not know read_logs' schema, leaving most parameters underdocumented.

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

Purpose4/5

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

The description states a specific action ('Query') and resource ('background capture buffer'), making the purpose clear. Referencing read_logs for filters helps distinguish it from reading live logs, though it doesn't explicitly contrast with read_logs or other siblings. This is a clear but not fully differentiated description.

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

Usage Guidelines3/5

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

The description implies that the tool is used when you want to read from a capture buffer, but it doesn't explicitly state when to choose this over read_logs or capture_start. No alternatives are mentioned, and the 'same filters as read_logs' comment only suggests similarity. The usage context is implied rather than explicit.

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