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Manthan

Manthan

by kidakaka
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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propose_constitution_rule

Proposes a new architectural rule or ADR as a draft in constitution memory for human developer review before promotion to project law.

Instructions

Guardrail Promotion: proposes a new architectural law or ADR inside constitution memory with status: "draft" for human developer review.

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": {
      "title": "<title>",
      "content": "<content>",
      "namespace": "<namespace>",
      "rationale": "<rationale>",
      "author_agent": "<author_agent>"
    },
    "name": "propose_constitution_rule"
  }
}

Input Schema

NameRequiredDescriptionDefault
titleYesTitle of the proposed constitutional rule or architectural guardrail
contentYesThe rule specification in Markdown format
namespaceYesCategory namespace for the rule (e.g. "architecture/adr", "security/auth")
rationaleYesDetailed engineering justification explaining why this should become an unalterable project law
author_agentYesName or identifier of the AI agent proposing the rule
create_branchNoWhether to create and isolate the proposal in a dedicated Git branch (e.g. manthan/rule-<id>)
source_memory_idNoOptional ID of an existing working memory being promoted to constitutional law

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
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 behavioral burden. It usefully discloses that the proposal is created with status 'draft' and is intended for human developer review, but it omits permissions, side effects, lifecycle after review, and whether existing rules are affected.

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, front-loaded sentence with no redundant wording. It conveys the purpose and key state immediately.

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 and draft/human-review state are present. For a seven-parameter mutation tool with no annotations and no output schema, however, the description should clarify lifecycle, permissions, and how it relates to sibling commit tools; those gaps keep completeness at a minimum-viable level.

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

Parameters3/5

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

Schema description coverage is 100%, so all seven parameters are already documented in the input schema. The description adds contextual framing around constitution memory and draft status but does not add parameter-specific meaning beyond what the schema provides.

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 gives a specific verb ('proposes'), resource ('new architectural law or ADR inside constitution memory'), and state ('draft for human developer review'), which clearly separates it from directly committing memory. It does not explicitly name sibling tools such as commit_memory, so it falls short of full sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit when-to-use or when-not-to-use guidance, and no alternative sibling is named. The label 'Guardrail Promotion' implies the tool is for proposing rules, but the description does not tell an agent when to choose this over commit_memory or another memory tool.

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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