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Argus Launch Scout

argus_launches
Read-onlyIdempotent

Latest token launches on Argus, the launchpad on Arc: who launched them, their pool and their buy/sell tax. Price: $0.001 USDC (x402).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many launches to return, newest first (1–20, default 8)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL to call; it answers 402 with the price, then the data once paid
bodyNoJSON body for POST tools
methodYesHTTP method to call with an x402 client

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / limit
      Added value: +{
+  "description": "How many launches to return, newest first (1–20, default 8)",
+  "type": "integer"
+}
  2. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already establish this as a read-only, non-destructive call. The description adds a key behavioral detail beyond annotations: 'Price: $0.001 USDC (x402)' indicates the call incurs a payment. It also specifies the data content (pool, taxes), enriching the behavioral picture. No contradiction with annotations.

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 filler. The first sentence front-loads the core purpose and returned fields; the second adds pricing. Every word earns its place, and the structure is efficient and scannable.

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?

For a simple one-parameter tool with a full input schema and an output schema, the description covers the essential: what data is returned and the cost implication. It doesn't explain the ordering of results (newest first) but that's already in the parameter schema. The presence of an output schema means return format details are handled elsewhere, so completeness is adequate.

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?

Schema description coverage is 100% – the only parameter 'limit' is fully documented in the schema with range and default. The tool description adds nothing about the parameter beyond what the schema already states. Per rubric, a high coverage baseline is 3, and the description does not compensate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the resource: 'Latest token launches on Argus' and the specific data returned (who launched, pool, buy/sell tax). It lacks an explicit verb like 'fetch' or 'list', but the intent is unambiguous. It distinguishes from siblings by naming a unique platform (Argus) and scope (launches), though it doesn't explicitly contrast with alternatives.

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?

The context for use is implied: if you need recent token launches on Argus, this is the tool. However, there's no explicit guidance on when NOT to use it or which sibling tool might be a better fit for related queries (e.g., argus_bonding for bonding curves). No alternatives are mentioned, so the usage guidance is minimal.

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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