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Holder structure diff

robinx_structure
Read-only

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 rap sheet, ENS + Farcaster identity with multi-wallet entities collapsed, round-number off-market flags) + a structure verdict: rotation vs top-distribution vs accumulation. The repricing-or-rug call price data cannot make. First call queues the scan (free, ~10-60s); call again for results. (paid $0.03 — see instructions)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokenYesToken contract address 0x…

TDQS

A4/5.0
Behavior4/5

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

Annotations indicate readOnly and non-destructive; description adds behavioral details: the scan takes 10-60 seconds, first call is free then paid, it provides enriched wallet stamps and a structure verdict. Adds context beyond annotations about cost, time, and data enrichment.

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 dense and front-loaded with the main purpose. Each sentence adds value, though some phrasing (e.g., 'to the wei') could be trimmed. It is efficient but slightly verbose, earning a 4.

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?

Despite no output schema, the description fully explains what the tool returns (diff, wallet stamps, verdict), the scan process, and limitations. It covers inputs, outputs, and usage flow, making it highly complete for a single-parameter tool.

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?

The sole parameter 'token' is fully described in the input schema (type and description). The description does not add extra parameter-specific details, but schema coverage is 100%, so baseline 3 is appropriate.

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 clearly states it produces a 'labeled holder-structure diff' for a token, detailing specific changes (who froze, added, trimmed, exited). It distinguishes itself from sibling tools like robinx_token and robinx_verdict by focusing on holder structure changes over a 24-hour window.

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 description implies usage: first call queues a free scan, second call retrieves results (paid). It mentions a limitation (cannot make price calls) but does not explicitly state when to use this tool vs alternatives like robinx_smart_holders or robinx_signals. Guidance is present but implicit.

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

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct aspect of Robinhood Chain token analysis: deployer reputation, on-chain stats, social sentiment, wallet history, etc. Even overlapping concepts like verdict and report are clearly differentiated by scope and detail.

Naming Consistency5/5

All tools follow a consistent 'robinx_<single_word_noun>' pattern, making it easy for an LLM to predict tool names and understand their purposes at a glance.

Tool Count5/5

12 tools is optimal for a domain-specific server covering deployer analysis, token stats, social signals, wallet reputation, and composite reports. The count feels neither sparse nor bloated.

Completeness4/5

The tool set covers the core token analysis workflow: search, deployer check, on-chain stats, holder structure, social pulse, and comprehensive reports. Minor gaps like batch operations or historical comparisons exist but do not severely hinder usability.