Skip to main content
Glama

marrow_accept_detected

Accept a detected decision pattern to convert it into an enforced workflow, using the pattern ID from suggested_workflows.

Instructions

Convert a detected decision pattern into an enforced workflow. The pattern ID comes from suggested_workflows in the orient() response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
detectedIdYesID of the detected pattern to accept
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 states that a detected pattern is 'converted into an enforced workflow', implying a state change, but does not disclose side effects, reversibility, permissions required, or what 'enforced' means in terms of governance. The tool likely mutates state, and the lack of such details 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 two short sentences: the first defines the core action, the second specifies the origin of the required parameter. Every word earns its place; no redundant information or filler.

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?

For a simple one-parameter tool with no output schema, the description covers the primary action and parameter source. However, it lacks any mention of the result or consequences of enforcement, such as whether the change is permanent, reversible, or requires special permissions. Given the governance-related sibling tools, more context on what 'enforced workflow' entails would make it more complete.

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 already describes detectedId as 'ID of the detected pattern to accept' (100% coverage). The description adds valuable context by specifying that the ID comes from 'suggested_workflows in the orient() response', which clarifies the exact source and relationship to another tool. This goes beyond the schema's generic description.

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 clearly states a specific action ('Convert a detected decision pattern into an enforced workflow') with a resource (a decision pattern) and an outcome. It also names the source of the pattern ID from 'suggested_workflows in the orient() response', which distinguishes it from sibling tools like marrow_orient or marrow_workflow.

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 a clear usage context: use this tool when a decision pattern has been detected, and the ID comes from the orient() response. This implies it should be used after orient() returns suggested workflows. However, it does not explicitly state when not to use it or name alternatives, only a single key contextual dependency.

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

Install Server

Other Tools

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/getmarrow/marrow-mcp'

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