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Ranoes

Academic Proposal MCP Server

by Ranoes

increment_proposal_version

Increment a thesis proposal version by duplicating the active version into a new version and recording the changelog to version history.

Instructions

Menduplikasi versi aktif proposal skripsi ke versi baru dan mencatat riwayat perubahan ke version_history.json. Contoh: current_version='v1.0', new_version='v1.1', changelog='Penyelarasan rumusan masalah tunggal'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
changelogYes
new_versionYes
current_versionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.1/5.0
Behavior3/5

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 discloses the core mutation: it duplicates a version and writes to version_history.json. However, it does not mention potential side effects like overwriting, validation of version format, idempotency, or what happens if the new_version already exists. While the example implies version format, it lacks depth on error conditions or return behavior.

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 followed by an illustrative example. It is concise, front-loads the primary action, and includes a useful example that adds clarity without bloat. There is no redundant or filler content.

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 tool has no output schema, so the description should explain what the tool returns or indicates success. It does not. It also doesn't mention prerequisites like the existence of the current version or the file. While the core operation is clear, an agent may wonder about the response format or error handling. For a simple mutation tool, this is a moderate gap.

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. It does so by providing an example with concrete values (current_version='v1.0', new_version='v1.1', changelog='...'), which clarifies the role of each parameter. However, it does not formally describe each parameter's constraints (e.g., version format rules), leaving some interpretation to the agent.

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 states a specific action: duplicating the active thesis proposal version to a new version, and recording change history to a file. It clearly distinguishes from the sibling increment_praproposal_version by explicitly naming 'proposal skripsi' versus the praproposal counterpart. The example further clarifies the versioning pattern.

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 context on when to use this tool (for thesis proposal versioning) but does not explicitly exclude the sibling tool for praproposals. It gives a concrete example but no direct 'when not to use' guidance. The sibling name offers implicit differentiation, but the description itself doesn't route explicitly.

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