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tnt-house-risk-data-api

by io.github.menantonio83-hue

Get historical risk trend for a Solana token

get_token_risk_history

Returns hourly historical data points (safety_score, insider_cluster_count, holder_count, price, liquidity, volume) for a mint over the last N days (max 90). Free and unmetered — no quota, works with or without an API key — pure read from stored history, no live upstream call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoHow many days of history to return (default 30, max 90)
mintYesThe Solana token mint address

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations at all, the description carries the full behavioral burden and does so excellently. It discloses that the tool is read-only ('pure read from stored history'), has no quota ('Free and unmetered'), needs no API key ('works with or without an API key'), and makes no live upstream call. This is rich, useful behavioral context.

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?

The description is three tight sentences with no filler. It front-loads the core function and returned fields, then adds the behavioral caveats. Every clause earns its place and the structure is easy to scan.

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?

For a simple two-parameter read-only tool with no annotations and no output schema, the description is remarkably complete. It covers purpose, output shape (listed fields), time window, quota, auth, and upstream behavior. An agent has everything needed to call it correctly.

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%, so both mint and days are already documented. The description reinforces the max-90-day limit and adds hourly granularity, but it does not add meaningful new parameter-level meaning beyond the schema. 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 uses a specific verb ('Returns') with a clear resource ('historical risk trend for a Solana token') and enumerates the exact data fields returned. The word 'historical' plus the time-window framing distinguishes it from siblings check_token_risk and check_token_risk_batch, which sound current-state oriented.

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 clearly implies when to use it: when a historical trend over multiple days is needed, not a current snapshot. It does not explicitly name the sibling alternatives or state when not to use the tool, but the context is unambiguous enough for an agent to make the right choice.

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

A4.4/5.0
Disambiguation5/5

Each tool targets a clearly distinct operation: live single-mint risk check, batched multi-mint risk check, and historical risk data retrieval. The single vs. batch distinction is explicit in the names and descriptions, so there is no meaningful overlap or selection ambiguity.

Naming Consistency5/5

All tools follow a consistent snake_case verb_noun pattern (check_token_risk, check_token_risk_batch, get_token_risk_history). The 'batch' suffix clearly modifies the object, and the switch from 'check' to 'get' appropriately distinguishes live assessment from historical data.

Tool Count5/5

Three tools is lean but well-scoped for a focused token-risk API: a single check, a batch check, and a history lookup. Each tool fills a distinct role with no redundant or filler endpoints.

Completeness4/5

The core workflow—assess one token, assess many tokens, retrieve history—is fully covered. Minor gaps exist, such as no way to query remaining quota/credit before a batch call and no token metadata/lookup endpoint, but agents can work around these.

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