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cyberrescue

cyberrescue

by Vivekpatil200320
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Python
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stream_container_logs

Retrieve stdout and stderr logs from a Docker container for debugging. Filter by time, keyword, or number of recent lines.

Instructions

Fetch stdout/stderr logs from a Docker container by ID or name.

Args:
    container_id: Container ID or name.
    tail: Number of lines to fetch from the end of the logs.
    since: Optional ISO 8601 timestamp; only return logs after this time.
    filter_keyword: Optional substring; only return lines containing it.

Returns:
    dict with container_id, log_lines, line_count, truncated.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "container_id": "<container_id>"
    },
    "name": "stream_container_logs"
  }
}

Input Schema

NameRequiredDescriptionDefault
container_idYes
tailNo
sinceNo
filter_keywordNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It clearly explains the parameters and the return value, implying a read-only operation ('fetch'). It could explicitly state that the tool does not modify state, but the information is sufficient for safe usage.

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: a single purpose sentence, followed by well-structured Args and Returns sections. No wasted words, and the most important information (purpose) is front-loaded.

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

Completeness5/5

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

Given that there is no output schema, the description provides a complete return structure (container_id, log_lines, line_count, truncated). All parameters are explained. The tool is simple and the description covers all necessary information for an agent to use it correctly.

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

Parameters5/5

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

Schema description coverage is 0%, meaning the schema alone provides no parameter descriptions. The description fully compensates by explaining each parameter's purpose (container_id as ID or name, tail as number of lines, since as ISO timestamp, filter_keyword as substring). This adds essential meaning.

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 'Fetch stdout/stderr logs from a Docker container by ID or name.' This clearly identifies the verb (fetch), the resource (logs), and the scope (by container ID/name). It is distinct from sibling tools which deal with scripts and memory dumps.

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 clear guidance on when to use the tool (to fetch logs) and explains each parameter's role. However, it does not explicitly state when not to use it or provide alternatives, though siblings are sufficiently different that exclusion is implied.

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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