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Glama

overshoot_signal

Detect overshoot/fade setups by analyzing a token's recent price jumps, then report if a fade is active and its historical reversion tendency.

Instructions

PREMIUM SIGNAL — overshoot/fade detector. Analyzes a token's recent price series for fresh panic jumps and reports whether a fade setup is active plus this market's historical reversion tendency.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hoursNo
token_idYes
thresholdNo
lookback_sNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

C2.7/5.0
Behavior3/5

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

With no annotations provided, the description carries full behavioral disclosure burden. It states the tool analyzes and reports, implying a read-only operation, but does not explicitly confirm it has no side effects, nor does it disclose potential limitations (e.g., data sufficiency, time windows). The mention of 'fresh panic jumps' and 'historical reversion tendency' adds some context but lacks depth.

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 concise, consisting of a single sentence that front-loads the core purpose. The 'PREMIUM SIGNAL' label is extraneous but does not add bulk. It avoids unnecessary verbosity while conveying the primary function, though it could be tightened further.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Although an output schema exists (so return values need not be described), the description is incomplete for agent usage. It does not explain the parameters, nor does it provide usage context such as when the signal is considered active or how to interpret the reversion tendency. For a tool with four configurable parameters and no schema descriptions, this is a significant gap.

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

Parameters1/5

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

The description provides zero information about the four parameters (hours, token_id, threshold, lookback_s). With schema description coverage at 0%, the description must compensate, but it does not map any parameter to its role or default behavior. The agent is left to guess what 'hours' or 'threshold' mean based solely on the schema property names, which is insufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose as an overshoot/fade detector that analyzes a token's recent price series for panic jumps and reports on fade setups and historical reversion tendencies. It uses a specific verb 'analyzes' and names the resource, distinguishing it from raw data tools like price_history. However, it does not explicitly differentiate from siblings beyond implying signal generation.

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

Usage Guidelines2/5

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

There is no explicit guidance on when to use this tool versus alternatives like price_history or get_market, nor any conditions or exclusions. The description implies it is for fade detection but does not state scenarios where it is appropriate or inappropriate, leaving the agent without clear selection criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.