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Glama

Robyn — Gasless Cross-Chain for AI Agents

by io.github.ox31461

NULL — discover the whole ecosystem in one call

null_ecosystem

The live NULL manifest: every product (messenger, Pay, Vault, Drop, Legacy, Agent Wire, forward secrecy), its status, its page, the wired/proposed integrations between them, the security spine, and the concept pipeline. This is the same single source of truth the owner console and the human Suite read — a new product that ships appears here automatically. Pair it with null_agent_guide for the how-to. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. Added

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden. It explicitly states 'Read-only' and explains the content is live/auto-updating, which is meaningful beyond the schema. It does not go into authentication, rate limits, or response size, but for a zero-parameter read call this is reasonably transparent.

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?

Three sentences, front-loaded with the manifest purpose, then the source-of-truth/auto-update context, and a terse read-only note. Every sentence adds distinct value 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?

For a simple no-parameter read tool, the description covers what the response contains, freshness, and side-effect safety. The only appreciable gap is that it never describes the actual return format or possible size, which is not critical but would round out the completeness.

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 has zero parameters, which earns the baseline 4. There is no parameter semantics to add, and the description correctly focuses on the returned manifest rather than inputs.

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?

The description states a specific purpose: return the live NULL manifest covering all products, statuses, pages, integrations, security spine, and concept pipeline. It also distinguishes from null_agent_guide by noting the guide covers how-to, while this call returns the single source of truth.

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

Usage Guidelines4/5

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

The description makes clear this is the one-call overview/source-of-truth endpoint and suggests pairing with null_agent_guide for how-to details, giving context for choosing it. It does not spell out explicit when-not-to-use conditions or other alternatives, so it stops short of a 5.

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

A3.6/5.0
Disambiguation2/5

Many tools have overlapping purposes, such as robyn_quote, robyn_prepare, robyn_settle, robyn_cross_chain, robyn_plan, robyn_preflight, and robyn_preflight_full, all involving routing or quoting. Although descriptions are detailed, the high number of subtly different tools makes selection error-prone.

Naming Consistency5/5

All tools follow a consistent <prefix>_<verb/noun> pattern, with robyn_ and null_ as clear category prefixes. Verbs like prepare, submit, verify and nouns like quote, plan, mesh are highly predictable throughout.

Tool Count2/5

With 70 tools, the count far exceeds the 25+ heavy threshold. While the service scope is broad (payments, messaging, netting, Plus, yield, etc.), many tools could be merged or tiered, making the set feel overly large and burdensome for an agent.

Completeness4/5

The surface covers the full lifecycle from quoting, planning, submitting, verifying, auditing to messaging, custody, yield, and mandates, plus sandbox, lint, and recipes. A few advanced operations like cancellation or revocation are missing, but no critical gaps remain.

Resources