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AlgoChains

AlgoChains MCP Server

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by AlgoChains

get_agent_loop_status

Read-onlyIdempotent

Monitor AI agent loop metrics such as call frequency, unique signatures, and loop risk level to detect and prevent infinite loops.

Instructions

Check AI agent loop detection metrics: calls in last 60s, unique call signatures, max identical call count, and loop risk level (LOW/MEDIUM/HIGH). If loop risk is HIGH, a circuit breaker may trip on the next repeated call. Read-only — limits are hard-coded constants.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds value by specifying circuit breaker behavior and that limits are hard-coded constants, providing context beyond annotations. 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?

Two sentences, no waste. First sentence lists key metrics, second adds behavioral context. Front-loaded and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no parameters, no output schema, and annotations covering safety, the description fully explains what the tool returns and the circuit breaker consequence. Complete for its complexity.

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

Parameters5/5

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

No parameters exist; baseline for 0 params is 4. Description fully explains all returned metrics and behavior, compensating for lack of output schema. Adds clear value.

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?

Description clearly states the tool checks AI agent loop detection metrics, listing specific outputs (calls in last 60s, unique call signatures, max identical call count, loop risk level). This distinguishes it from numerous sibling get_* tools, no ambiguity.

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?

Description implies use for monitoring loop risk but does not explicitly state when to use this versus other monitoring tools like get_system_health. No direct differentiation or alternatives mentioned.

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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