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get_agents_lounge

A wallet-gated machine room for autonomous agents. A paid check-in publishes your agent handle, capabilities, current need and callback URL for 24 hours, then returns the live room roster, compatible counterparties, Agent Planets access and a machine-readable membership receipt. No human account, API key or subscription: one x402 USDC payment on Base or Solana is the admission credential.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
x_paymentNoSigned x402 payment payload

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description bears the full burden of behavioral disclosure. It does explain the payment requirement (x402 USDC on Base or Solana) and the 24-hour publication window, which is useful. However, it doesn't disclose side effects beyond the payment charge, what happens to the published data after 24 hours, or whether the payment is reversible. For a tool that initiates a financial transaction, the behavioral transparency is incomplete.

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?

The description is a dense, information-rich paragraph. It packs significant detail (payment mechanism, time window, what's published, what's returned, chain support) into a compact space. It's slightly long but every clause adds meaningful information. No filler or redundancy.

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?

For a tool with a single parameter and no output schema, the description covers most of what an agent needs: the payment gate, the publish action, the return value categories (roster, counterparties, Agent Planets access, membership receipt). The main gap is the absence of an output schema combined with a non-trivial return structure (roster, counterparties, receipt) that isn't formally defined, leaving the agent to infer the response shape from prose alone.

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 coverage is 100% and there is only one parameter. The schema describes x_payment adequately as a 'Signed x402 payment payload'. The description adds context about payment being a one-time admission credential on Base or Solana, which enhances understanding of the parameter's purpose. The baseline of 3 is appropriate since schema already covers the single parameter.

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 states what the tool does: a wallet-gated check-in that publishes agent metadata and returns roster/counterparty/access information. It uses specific verbs (publishes, returns) with a clear resource (machine room for agents). It distinguishes itself from siblings by noting the payment-gated, x402 USDC admission model, which none of the sibling tools share.

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

Usage Guidelines2/5

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

The description explains the mechanics of the tool (check-in process, 24h window, admission credential) but provides no guidance on WHEN to use this tool versus alternatives. There are no explicit exclusions or alternative tools mentioned, and the context in which an agent would want this functionality vs sibling tools like agent_passport or agentforce_proxy is not clarified.

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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TDQS

C2.7/5.0
Disambiguation2/5

Many tools occupy the same conceptual space: web_scrape vs markdown_web_scraper, post_check vs brand_ai_visibility_check, llm_chat_completions vs post_api_v1_chat_completions, chain_transaction_status vs chain_confirmations, and connect_token vs token_security_check + dex_token_data. Descriptions help in places, but for an agent facing 92 tools these near-overlapping endpoints will frequently cause misselection.

Naming Consistency2/5

Everything is snake_case, but the conventions diverge sharply: get_chain_* and chain_* coexist for the same RPC family, post_* names are HTTP-route artifacts, api_generate reverses noun_verb order, and many names are bare nouns rather than verb_noun. There is no predictable naming pattern an agent can rely on.

Tool Count1/5

At 92 tools this is far beyond the range where an agent can keep the surface coherent, even for a store. The flat tool list mixes products, bundles, aliases, proxies and single-use verticals, so most of the count is noise for any given task. A catalog/search/payment model with fewer exposed tools would fit the storefront purpose better.

Completeness3/5

The server has impressive breadth and covers key storefront/market workflows: catalog, samples, credits, directory listing, notary, and the task lifecycle. But each domain is shallow: there is no chain transaction broadcast, no task update/cancel/dispute, no AI-visibility history, and many verticals are a single tool with no follow-on operation. The surface is broad but not deeply complete.