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Holder structure diff

robinx_structure
Read-only

Analyze a Robinhood Chain token's ~24h holder-structure changes to detect wallet freezes, additions, trims, and exits, then classify rotation, top distribution, or accumulation.

Instructions

Labeled holder-structure diff for a Robinhood Chain token: who FROZE (to the wei), who added, who trimmed, who exited over ~24h — every notable wallet stamped with what RobinX knows (insider-linked extraction record, deployer record, ENS + Farcaster identity with multi-wallet entities collapsed, round-number off-market allocation flags), plus a structure verdict: rotation vs top-distribution vs accumulation. The repricing-or-rug call that price data cannot make. The first GET auto-queues a free scan (HTTP 202 — poll again in ~15-60s); once computed, results cost $0.03 USDC on Base.

Input Schema

NameRequiredDescriptionDefault
tokenYesThe token contract address (0x…) on Robinhood Chain

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Beyond the readOnly/openWorld annotations, the description discloses the async scan-queue behavior, the HTTP 202 and 15-60s polling window, the free-scan-then-paid model, and the exact $0.03 USDC on Base cost. These are exactly the non-obvious traits an agent must know before calling and would otherwise only discover by failing.

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 core resource and scope are front-loaded, and the operational cost/polling details are packed into the final sentence rather than scattered. Some rhetorical padding ('who FROZE (to the wei)', 'The repricing-or-rug call that price data cannot make') slightly dilutes density but still carries signal.

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 only one parameter, the description carries the burden of explaining what comes back — labeled wallets with insider/deployer/ENS-Farcaster/off-market-allocation stamps and a structural verdict — and it does so, alongside the async/payment mechanics. An agent has everything needed to call it and interpret the first response.

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% and there is a single required parameter, so the schema already defines 'token' as a 0x… contract address on Robinhood Chain. The description only restates 'for a Robinhood Chain token' and adds no syntax or format detail beyond the schema, making the 3 baseline correct.

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 states a precise verb+resource: a labeled holder-structure diff over ~24h for a Robinhood Chain token, broken down by froze/added/trimmed/exited, plus a rotation vs top-distribution vs accumulation verdict. This is far more specific than a generic 'get holders' and clearly differs in substance from siblings like robinx_smart_holders or robinx_verdict, though it never names an alternative outright.

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?

It conveys the triggering situation ('The repricing-or-rug call that price data cannot make'), i.e. use it when you need to tell rotation from distribution from accumulation. It also spells out the operational flow — first GET auto-queues a scan, 202, re-poll in ~15-60s, then $0.03 USDC on Base — but gives no explicit exclusions or named sibling alternatives for overlapping needs.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.