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get_token_dump_risk

Assess token unlock and vesting schedules by calculating D-Day, unlock supply ratio, and sell-pressure score against real-time volume, identifying VC/team dump risk before taking positions.

Instructions

Calculate a token's vesting/unlock D-Day, unlock ratio relative to
circulating supply, and a sell-pressure score against real-time volume,
returned as a concise summary report.

Use this to evaluate token unlock schedules, vesting cliffs, and upcoming
VC/team dump pressure relative to circulating supply before taking mid-to-
long term positions. Do NOT use it for intra-day slippage or real-time
transaction simulation - use dex.liquidity_slippage for that instead. This
tool is free (no payment) as an onboarding check; every other tool here is
a normal read-only call against app/logic.py.

Args:
    symbol: Token ticker symbol (e.g. "ATH", "AO", "CPOOL"). Case-insensitive.

Returns:
    Success & data available: {"success": true, "available": true, "symbol",
        "unlock_date_utc", "days_until_unlock", "unlock_supply_pct",
        "volume_impact_pct", "sell_pressure_risk_level", ...}
    Success but not yet available:
        {"success": true, "available": false, "reason", "message"}
        (e.g. the paid data source isn't connected yet, by business decision)
    Failure: {"success": false, "error": {"type", "message"}}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYes

Schema Changelog

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

  1. First observedv1.0.0

TDQS

A5/5.0
Behavior5/5

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

No annotations are provided, so the description carries the full burden. It discloses return behavior across three cases: success with data, success but data unavailable, and failure with error. It also explains the paid data-source caveat and the free onboarding-check nature of the tool. This is strong behavioral transparency for a calculation-style tool.

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 well-structured, front-loading purpose and usage before organized Args/Returns sections. Each sentence adds useful context: selection guidance, exclusions, parameter semantics, and return shapes. The extra pricing/read-only note is relevant contextual information rather than padding.

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?

With one parameter, no output schema, and no annotations, the description is complete enough for an agent to select and invoke the tool correctly. It explains what the tool returns in all major outcome states, including the unavailable case and error format, so no critical invocation or interpretation detail is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. The Args section defines the symbol parameter with semantic meaning, examples ('ATH', 'AO', 'CPOOL'), and explicitly states 'Case-insensitive.' This adds real meaning beyond the bare schema and fully covers the only parameter.

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 opens with a specific verb and resource: 'Calculate a token's vesting/unlock D-Day, unlock ratio relative to circulating supply, and a sell-pressure score...' It clearly states what the tool does and its key outputs, which distinguishes it from related siblings like security.token_diagnostic and dex.liquidity_slippage.

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?

The description explicitly says when to use the tool: 'Use this to evaluate token unlock schedules, vesting cliffs, and upcoming VC/team dump pressure relative to circulating supply before taking mid-to-long term positions.' It also gives an explicit exclusion and alternative: 'Do NOT use it for intra-day slippage or real-time transaction simulation - use dex.liquidity_slippage for that instead.'

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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