Skip to main content
Glama

cryptoguard_scan_token

Read-onlyIdempotent

Scan cryptocurrency tokens for anomalous market behavior using physics-based detection. Compares tokens to tier-matched peers to identify unusual metrics and assess risk levels.

Instructions

Scan a single token for anomalous market behavior using WaveGuard physics-based anomaly detection. Compares the token to TIER-MATCHED peers (microcaps vs microcaps, large-caps vs large-caps). Returns anomaly scores, risk level, and explanations.

Example: scan 'solana' to check if its metrics are unusual.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
coin_idYesCoinGecko coin ID (e.g., 'bitcoin', 'solana', 'pepe').
sensitivityNoAnomaly sensitivity multiplier (default: 1.0). Higher = more sensitive.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

A4.4/5.0
Behavior4/5

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

Beyond the readOnlyHint and destructiveHint annotations, the description adds meaningful behavioral context: it performs peer-tier comparison and returns anomaly scores, risk level, and explanations. This goes beyond the safety profile already declared by annotations, giving the agent a clearer picture of the tool's operation and output.

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 highly concise, consisting of two sentences plus an example. Every sentence contributes meaningful information: the core functionality, the tier-matching behavior, and the output summary. No fluff or redundancy.

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?

Given there is no output schema, the description compensates by listing the return types (anomaly scores, risk level, explanations). It adequately explains the input and the comparison logic, making the tool understandable for a read-only scan operation. It lacks details on rate limits or edge cases, but for this complexity level, it is 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?

The input schema already covers both parameters with clear descriptions (coin_id and sensitivity). The description enhances this by providing a concrete example ('scan solana') that demonstrates parameter usage in context, adding value beyond the schema definitions.

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 scans a single token for anomalous market behavior using a specific method (WaveGuard physics-based anomaly detection). It also distinguishes itself from sibling tools by specifying tier-matched peer comparison, making it unique among the listed siblings.

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 example 'scan solana' provides a concrete use case, making it clear when to use the tool. It implies the tool is for checking anomaly metrics on a single token, but it does not explicitly contrast with alternatives like rug_check or validate_trade, so it lacks explicit exclusions.

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