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Degenscan Intel

by io.github.tradewr333-lgtm
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Impact for asset

impact_for
Read-onlyIdempotent

Net directional pressure on ONE asset over a window: bias (−1..+1), number of events, strongest supportive and negative drivers, and the source events with rationale and graph path. Use it before entering or sizing a position in that asset, or to explain a move ("why is MSTR down today?"). $0.003/call. Use for one asset's scored impacts; for raw events use events_since, for a full asset briefing use brief.

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": {
      "asset_id": "<asset_id>"
    },
    "name": "impact_for"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMax source events returned with the aggregate.
sinceNoLookback window: "1h", "24h", "7d" or ISO-8601. Default 24h.24h
asset_idYesUniverse asset id (case-insensitive), e.g. NVDA, BTC, CL, US10Y, SPX. Call `universe` to list ids.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive, so the safety profile is covered. The description adds genuinely useful context beyond that: the per-call price ($0.003/call) and the exact shape of what is returned. It stops short of noting rate limits or auth requirements, so it is not fully exhaustive.

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?

Front-loads the core definition, then usage, then cost, then sibling routing, in four compact sentences with no filler. Every clause carries distinct information.

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?

There is no output schema, and the description compensates by enumerating the returned fields (bias, event count, drivers, rationale, graph path). Combined with 100% schema coverage on inputs and full annotation coverage, an agent has everything needed to call and interpret it.

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 asset_id, since, and limit are already documented with formats, defaults, and bounds. The description adds only the notion of a 'window' and reinforces single-asset scope, which is marginal beyond the schema — the baseline 3 applies when the schema does the heavy lifting.

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 with scope: 'Net directional pressure on ONE asset over a window', then enumerates the payload (bias −1..+1, event count, strongest drivers, source events with rationale and graph path). It is unmistakably distinct from sibling tools like events_since, brief, and price_for.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit when-to-use ('before entering or sizing a position in that asset, or to explain a move ("why is MSTR down today?")') and names the two alternatives with their selecting conditions: events_since for raw events, brief for a full asset briefing. Nothing is left to inference.

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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