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by io.shingou
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Point-in-time sentiment history

get_sentiment_history
Read-onlyIdempotent

Point-in-time sentiment series for backtesting: bucket is the as-of time, no lookahead. from/to are clamped to your plan's history window and to its per-request span, then echoed back — check them rather than assuming. reconstructed: true buckets were rebuilt from archival news, not live-collected; disclose the mix in any backtest.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "symbol": "<symbol>",
      "from": "<from>",
      "to": "<to>"
    },
    "name": "get_sentiment_history"
  }
}

Input Schema

NameRequiredDescriptionDefault
toYesRange end, ISO 8601
fromYesRange start, ISO 8601, e.g. 2026-06-27T00:00:00Z
symbolYesOne Shingou symbol, e.g. BTC-USD
intervalNoBucket size (default 1h)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

The description goes well beyond the annotations (readOnly, openWorld, idempotent). It discloses three behavioral traits: no lookahead, clamping of from/to to plan limits, and the reconstructed flag meaning archival vs live-collected data. This adds critical context for backtesting integrity that annotations alone do not provide.

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 dense sentences, each earning its place: purpose + no-lookahead, clamping behavior, and reconstructed flag. Front-loaded and focused. No filler words or repetition of schema details.

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 tells the user the key return semantics (bucket as-of time, reconstructed flag) and range clamping. It addresses the main risks (lookahead bias, range truncation, data provenance) for a backtesting tool. Sibling context and annotations complement it, making the description sufficient.

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?

Schema already covers all 4 parameters with descriptions (100% coverage), so baseline is 3. The description adds meaningful context for 'from'/'to' by explaining they are clamped and echoed back, and clarifies the output field 'bucket' as the as-of time. This extra value justifies a 4.

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 the tool provides a 'point-in-time sentiment series for backtesting', specifying both the resource (sentiment history) and its distinct purpose (backtesting) with the critical no-lookahead guarantee. This distinguishes it from sibling tools like get_sentiment (likely current sentiment) and get_events.

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 explicitly frames this tool for backtesting, giving a clear context for when to use it. It does not explicitly name alternatives or state when not to use it, but the backtesting context implies this is the historical counterpart to real-time sentiment tools. Minor deduction for lack of explicit exclusionary guidance.

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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