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sentiment_history

Retrieve daily historical social-sentiment scores for any supported token over the last 30 days (up to 180). Track bullish or bearish shifts in sentiment to inform market analysis.

Instructions

Social sentiment history (daily snapshots) — Returns the daily historical social-sentiment score for a single token over the last N days (default 30, max 180). Data is sourced from CryptoWhaleInsights' own in-house Social Sentiment engine (Stocktwits + CoinGecko + price-momentum — no Twitter API). Each day is recorded once per day from the live 5-min sentiment cycle. Cold-start days with no data are omitted. Use ?symbol=BTC&days=30 (symbol is required; days is optional 1–180). Supported symbols: BTC, ETH, SOL, BNB, XRP, ADA, DOGE, AVAX, MATIC, DOT, LINK, UNI, ATOM, ARB, OP, SUI, SEI, NEAR, APT, PEPE, WIF, BONK, FET, RENDER, TAO, AAVE, MKR, LDO, INJ, TON, STX, TIA, PYTH, BLUR, MINA, and more. Score is 0–100 (≥60 bullish, ≤40 bearish). Cached 5min.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoNumber of recent days to return (1–180, default 30).
symbolYesToken symbol to look up (e.g. BTC, ETH, SOL). Case-insensitive.

Schema Changelog

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

  1. Addedv0.1.2

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well: it discloses the data source, the daily snapshot frequency, that cold-start days are omitted, and that results are cached for 5 minutes. However, it contains an internal inconsistency with the schema (text says max 180 days while schema says maximum 90), which slightly undermines trust in the behavioral information.

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 front-loaded with its core purpose and then provides dense, useful details. It is longer than minimal because of the supported-symbol list, but nearly every sentence adds operational value such as source, caching, thresholds, and query format.

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 two-parameter tool with no output schema, the description explains what is returned, the score scale, the date range behavior, and the data source. It does not specify the exact response shape (e.g., array of date/value objects), but the absence of an output schema makes that more important; the inconsistency around the days maximum is the main completeness gap.

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 the baseline is 3. The description adds value with an example query, supported token names, and score thresholds, but it directly conflicts with the schema on the days maximum (description 'max 180' vs schema 'maximum 90'), which could mislead an agent into supplying an invalid value.

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?

States a specific verb+resource: 'Returns the daily historical social-sentiment score for a single token over the last N days.' This clearly differentiates it from sibling history/summary tools by emphasizing single-token daily sentiment snapshots, so an agent can identify the intended tool without opening schemas.

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?

Provides clear invocation context: 'Use ?symbol=BTC&days=30', states symbol is required and days is optional 1–180, and lists supported symbols. It does not explicitly contrast this with alternatives like social_summary or sentiment_monthly, so exclusions are not covered, but the usage context is otherwise clear.

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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