Skip to main content
Glama
hpractv

ralph-loop-mcp

by hpractv

ralph.write_epic_plan

Write or update the canonical epic plan file to capture the current plan, providing the authoritative reference for spec generation and iterative task execution.

Instructions

Write/update the canonical .ralph/epic_plan.md file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It reveals that the tool mutates a file at a specific path, but it does not say whether existing content is fully overwritten or merged, whether the file/directory is created if missing, or what constraints apply to the content. For a write operation with no annotation coverage, this is a significant gap.

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 zero filler. Every word contributes meaning, and for a tool with one parameter, this level of brevity is appropriate.

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 is simple (single string parameter, no output schema, no annotations), so the description is minimally adequate: an agent can infer that it should pass epic plan markdown as `content`. However, it omits content format details, overwrite semantics, and any relationship to sibling planning tools, which would be needed for fully confident invocation.

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 never mentions the `content` parameter at all. While the parameter name is somewhat self-explanatory, the description does not clarify expected format (e.g., markdown), structure, or constraints, leaving the agent to guess what a valid epic plan document looks like.

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 verb-resource pairing: 'Write/update the canonical .ralph/epic_plan.md file.' This clearly identifies the target artifact and distinguishes it from siblings like write_prd or upsert_spec by name and file path. However, the presence of a sibling named write_plan creates some ambiguity that the description does not explicitly resolve.

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 tool's purpose is evident from the description—it is for writing or updating the epic plan file—so when to use it is implied. But there is no explicit guidance about when to prefer this over siblings like write_plan, replace_fix_plan, or upsert_spec, and no exclusions or prerequisites are stated.

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

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/hpractv/ralph-loop-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server