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Ranoes

Academic Proposal MCP Server

by Ranoes

get_canvas_guidelines

Retrieves the complete Research Design Model Canvas v2.0 rubric checklist to guide users and AI assistants in structuring academic proposals.

Instructions

Mengambil rubrik lengkap checklist Research Design Model Canvas v2.0 (LB01-LB06, LR01-LR06, M01-M05) sebagai panduan bagi pengguna atau asisten AI dalam menyusun naskah ilmiah.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior3/5

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

Since no annotations are provided, the description carries the full burden for behavioral disclosure. The verb 'Mengambil' implies a read-only retrieval, but the description does not disclose return format, required permissions, or potential absence of data. For a zero-argument getter this is minimal but acceptable; the behavior is mostly inferred rather than stated.

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 a single sentence that states the action, the resource, and the purpose with no filler or redundancy. It is front-loaded with the verb and resource, making it easy for an agent to parse quickly.

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

Completeness3/5

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

The core purpose is covered, but the description omits the output shape and does not differentiate itself from the sibling generate_rubric_checklist_report. With no output schema and no annotations, the agent may still need to infer whether this tool returns the full checklist or the report format, so completeness is adequate but not strong.

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?

The input schema has zero parameters, so the baseline of 4 applies; there is nothing for the description to add. The description correctly does not invent parameter guidance.

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 ('Mengambil' = retrieves) on a specific resource (Research Design Model Canvas v2.0 rubric with codes LB01-LB06, LR01-LR06, M01-M05), which is clearly a retrieval operation distinct from sibling tools like generate_rubric_checklist_report or validate_canvas_compliance. It does not name an alternative explicitly, which keeps it below a 5.

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 when to use the tool: 'sebagai panduan ... dalam menyusun naskah ilmiah' (as a guide for composing scientific manuscripts). It gives no explicit when-not-to-use guidance and does not contrast with sibling tools such as generate_rubric_checklist_report, leaving some ambiguity for an agent deciding between related tools.

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