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sevenboom77

ResearchTwin MCP Server

by sevenboom77

Prepare project knowledge

prepare_project_knowledge

Creates a Markdown knowledge artifact from a promoted candidate, capturing project name, knowledge type, content, and user notes for auditable research documentation without external API calls.

Instructions

Prepare an auditable Markdown knowledge artifact from a promoted candidate; does not contact Bailian.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYes
user_noteNo
candidate_idYes
project_nameYes
knowledge_typeYes
knowledge_contentYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
knowledgeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the output format, auditability, and a key negative side-effect (no Bailian contact). It does not clarify whether the artifact is persisted, whether promotion is required, or any permission or error 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 compact sentence with no filler words. The primary action and output are front-loaded, and the critical no-Bailian caveat is clearly appended.

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?

Given six parameters, no annotations, and a likely precondition around what 'promoted candidate' means, the description is too sparse for confident invocation. The output schema covers return values, but parameter semantics and the promotion prerequisite remain gaps.

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 description coverage is 0%, so the description must compensate, but it only hints at candidate_id via 'promoted candidate' and knowledge_content via 'Markdown'. It leaves knowledge_type, user_note, project_name, and title semantics unexplained.

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 names a specific action ('Prepare'), a concrete output ('auditable Markdown knowledge artifact'), and a source ('promoted candidate'). It also distinguishes itself from the Bailian-sync sibling by explicitly stating it does not contact Bailian.

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 clause 'does not contact Bailian' provides an explicit exclusion and clearly separates this tool from sync_project_knowledge_to_bailian. It does not, however, describe positive conditions for when to use this tool over other knowledge-related siblings.

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