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SweetAI — On-chain AI Agent Intelligence

Agent SLA

get_agent_sla
Read-onlyIdempotent

Liveness SLA for one agent: uptime percent, p50/p95 latency and flap counts, measured by our own synthetic probing (history grows since probing started). Use it before routing work to an agent; the plain liveness verdict is get_agent_liveness.

Input Schema

NameRequiredDescriptionDefault
agent_idYes
window_daysNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the safety profile is covered. The description adds real context beyond that: the metrics come from 'our own synthetic probing' and 'history grows since probing started,' warning that coverage is time-bounded. It stops short of noting auth, rate limits, or caching, keeping it at a 4.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two front-loaded sentences: the first defines the metrics and their provenance, the second states usage and the sibling alternative. The parenthetical is dense but earns its place by flagging history limits; overall lean with no filler.

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

Completeness4/5

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

An output schema exists, so return structure needn't be spelled out, and annotations cover safety; the description adds the metric set and the probing-provenance caveat. The only real gap is the unexplained window_days parameter, which matters for a time-windowed SLA query.

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 carries the full burden, yet it never explains window_days (default 7) or what the window means operationally. The parenthetical 'history grows since probing started' hints at a time window but doesn't map it to the parameter, and agent_id is left unexplained.

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?

States a specific verb+resource ('Liveness SLA for one agent') and enumerates exactly what it returns: uptime percent, p50/p95 latency, and flap counts. It explicitly distinguishes itself from the sibling get_agent_liveness ('the plain liveness verdict is get_agent_liveness') so an agent can route between the two without opening either schema.

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

Usage Guidelines5/5

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

Gives a concrete usage trigger ('Use it before routing work to an agent') and names the alternative tool plus the condition that selects it (get_agent_liveness for a plain liveness verdict). Nothing is left to inference about when to pick this over the sibling.

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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