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Argus Console — AI Agent Test Lab

by io.github.igor-vii
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argus_list_agents

List the user's registered Argus agents (name, role, endpoint) and their free-tier state. ALWAYS call this first, before any run — it shows which agents exist and includes freeSimulation { used, limit, resetsAt } (MOCK simulation is FREE: rolling cap 25 runs / 24h, paid quota untouched). New accounts also hold 3 welcome engine runs (+30-run beta pack) for the real engine — visible in the console Billing page. If the target agent is missing, it must be registered in the Argus Console web UI first — tell the user; do not guess agent names or ids.

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": "argus_list_agents"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

No annotations are supplied, so the description carries the full burden and does well: it discloses the freeSimulation payload shape, the rolling 25-run/24h mock cap, that paid quota is untouched, and that new accounts hold welcome engine runs. It stops short of stating explicitly that the call is read-only/side-effect free or whether results are paginated or ordered, which is the only remaining behavioral gap.

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?

Front-loaded with the purpose, then the mandatory-call rule, then the fallback — a sensible order with no wasted opener. The billing/quota prose (beta pack, console Billing page) is somewhat verbose for a listing tool, though it does help interpret the returned freeSimulation object.

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?

With no output schema and no parameters, the description must explain what comes back and it does (name, role, endpoint, freeSimulation { used, limit, resetsAt }), plus what to do when the list is missing the desired agent. Nothing an agent needs to call this correctly and act on the result is missing.

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 tool takes zero parameters, so there is no parameter semantics to explain and the baseline is 4. The description correctly implies no arguments are needed to invoke it.

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 and resource ('List the user's registered Argus agents') and enumerates the returned fields (name, role, endpoint, free-tier state), which cleanly separates it from the sibling run/verify tools. An agent can identify this as the discovery step without opening any 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?

Explicitly mandates 'ALWAYS call this first, before any run' and explains the fallback when the target agent is absent (register in Argus Console, tell the user, never guess names/ids). This is an unambiguous when-to-use plus a when-not-to-improvise rule.

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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