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raw_request

Send raw HTTP requests to a TP-Link router to read or modify settings via arbitrary endpoints, with writes requiring confirmation and secrets automatically masked.

Instructions

任意エンドポイント読取。

  • path例: "admin/nat?form=vs", "admin/upnp?form=service"

  • data例: "operation=load" 等。operation指定時は data に operation= が無ければ自動付与

  • 戻り値の秘密値は常にマスク (reveal不可)

  • operation が read/load 以外の場合は書き込みとみなし confirm=true が必須

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
pathYes
confirmNo
operationNoread

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses that secret values in responses are always masked and cannot be revealed, and that non-read operations are treated as writes requiring confirm=true. It omits auth requirements, error behavior, and rate limits, but the safety-critical behaviors are covered.

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?

Four tight bullets, front-loaded with purpose and immediately followed by the most-needed usage facts (path/data examples, masking, confirm rule). No filler sentences.

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?

For a 4-parameter, zero-schema-coverage, no-annotation tool with no output schema, the description covers parameter meaning and critical behavior well. It stops short of describing how paths map to real endpoints or what errors/failures look like, which an agent exploring a raw API would benefit from.

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 0%, so the description must compensate, and it does: it gives concrete path examples, a data example, explains that operation= is auto-appended to data, describes operation's read/load vs write semantics, and ties confirm to write operations. Only finer data-encoding details are left implicit.

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?

States a specific verb+resource: reading arbitrary endpoints, which inherently contrasts with the typed sibling getters (get_wifi, get_dhcp_leases, etc.). The opening line is terse and the tool also performs writes (operation other than read/load), so the 'read' framing is slightly incomplete, but an agent can still grasp the tool's nature.

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?

Usage is implied rather than stated: it is the raw escape hatch for endpoints not covered by the specific sibling tools, but the description never says 'use this when no dedicated tool exists'. It does provide actionable conditions for the write path (confirm=true required when operation is not read/load), which is partial guidance.

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