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Glama

WaveGuard

by com.emergentphysicslab

waveguard_trajectory_scan

Read-onlyIdempotent

Analyze sequence drift and regime shifts over ordered samples.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sequenceYesOrdered samples (time sequence) to scan for drift and regime shifts.
trainingYes2+ baseline normal samples used to establish the reference regime.
field_levelNo0 = real scalar field, 1 = complex field.
sensitivityNoAnomaly sensitivity multiplier (default: 1.0).
encoder_typeNoOptional encoder override. Omit to auto-detect.

Schema Changelog

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

  1. Changed5 schema fields changed
    • addedInput schema / properties / encoder_type / description
      Added value: +"Optional encoder override. Omit to auto-detect."
    • addedInput schema / properties / field_level / description
      Added value: +"0 = real scalar field, 1 = complex field."
    • addedInput schema / properties / sensitivity / description
      Added value: +"Anomaly sensitivity multiplier (default: 1.0)."
    • addedInput schema / properties / sequence / description
      Added value: +"Ordered samples (time sequence) to scan for drift and regime shifts."
    • addedInput schema / properties / training / description
      Added value: +"2+ baseline normal samples used to establish the reference regime."
  2. Added

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is clear. However, the description adds no extra behavioral context beyond its purpose. It does not disclose output format, edge cases, or what happens with invalid inputs. With no output schema, this is a significant gap.

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 a single, grammatically correct sentence with no wasted words. It is appropriately concise for a simple read-only analysis tool, though it is slightly under-specified.

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?

There is no output schema, so the description should explain what the tool returns, but it does not. It also lacks differentiation from similar sibling tools and fails to mention how the analysis works or what the result means. Given the 5 parameters and no output schema, the description is incomplete.

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 descriptions cover 100% of parameters, so the baseline is 3. The description adds no additional parameter semantics; it merely restates 'ordered samples' which is already in the schema for 'sequence.' No extra clarity on field_level, sensitivity, or encoder_type is provided.

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 uses a clear verb 'analyze' and specifies targets 'sequence drift and regime shifts' over 'ordered samples.' It is specific and distinguishes this as a trajectory/sequence analysis tool, but it does not explicitly differentiate from sibling tools like waveguard_scan_timeseries or waveguard_instability.

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?

The description provides no guidance on when to use this tool versus alternatives. It implies usage for ordered/time-sequence data via 'ordered samples,' but there are no exclusions, prerequisites, or mentions of sibling tools. An agent would not know when to pick this over comparable scans.

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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TDQS

B3.4/5.0
Disambiguation3/5

Several tools occupy overlapping anomaly-detection territory (scan, scan_timeseries, price_manipulation, volume_check, token_risk, wallet_profile), which could cause misselection when an agent needs generic vs. specialized analysis. However, descriptions clarify data types and use cases, so the overlap is manageable.

Naming Consistency5/5

All tools share the consistent 'waveguard_' prefix with descriptive underscore-separated names (e.g., waveguard_cascade_risk, waveguard_volume_check). The occasional verb like 'scan' or 'compare' fits the overall pattern, making the set highly predictable.

Tool Count3/5

With 19 tools, the server is on the heavy side for a typical MCP but not extreme. The breadth reflects a comprehensive risk-analysis platform, though some specialized detectors (e.g., waveguard_price_manipulation vs. waveguard_scan_timeseries) could potentially be consolidated without losing functionality.

Completeness4/5

The tool surface covers the full analytical workflow: data ingestion (market_data), generic anomaly detection (scan, scan_timeseries), specialized crypto risk (token_risk, volume_check, wallet_profile), structural similarity (fingerprint, compare), and scenario/impact analysis (counterfactual, cascade_risk, mechanism_probe). Minor gaps like direct report generation exist but are not critical for the core purpose.

Resources