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AlgoChains MCP Server

AlgoChains MCP Server

Official
by AlgoChains
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

check_propagation_health

Read-onlyIdempotent

Detect signal propagation delays by verifying service reachability and active backlog in copy-trade paper fanout, separating genuine lag from quiet-market idle time.

Instructions

Check if the AlgoChains Django signal propagation service (Roo architecture) is reachable and whether copy-trade paper fanout has active backlog. Separates active_lag_seconds from idle_since_last_signal_seconds so quiet markets do not look stalled.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "check_propagation_health"
  }
}

Input Schema

NameRequiredDescriptionDefault
max_lag_secondsNoSLO threshold for active, unexpired signal backlog.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv22.7.1

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already indicate readOnly, openWorld, idempotent, and non-destructive behavior. The description adds valuable behavioral context: it checks reachability and backlog, and distinguishes between active lag and idle time to avoid false staleness signals in quiet markets. No contradictions.

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 consists of two concise, front-loaded sentences. The first sentence states the purpose and resource. The second adds crucial nuance about metric interpretation. No wasted words.

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?

Given the tool's simplicity and rich annotations, the description covers the core purpose and metric distinction. However, without an output schema, the description could have included what the tool returns (e.g., a health status object with those fields) to be fully self-contained, which is a notable omission.

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?

The input schema has 100% coverage for the single parameter max_lag_seconds, with a clear description in the schema. The tool description does not add any extra meaning beyond what the schema provides, so baseline score of 3 is appropriate.

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 the verb 'Check' and the specific resource: the AlgoChains Django signal propagation service (Roo architecture). It distinguishes this tool from sibling health check tools like get_system_health by focusing on signal propagation and copy-trade paper fanout backlog, including the nuance of separating active_lag_seconds from idle_since_last_signal_seconds.

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 explanation that the tool separates active lag from idle time so 'quiet markets do not look stalled' provides context on when to use it. However, it does not explicitly state when not to use it or mention alternatives among the many sibling health check tools, leaving some guidance implicit.

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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