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Glama

WaveGuard

by io.github.gpartin

waveguard_instability

Read-onlyIdempotent

Estimate instability under controlled perturb-and-resolve trials.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
testYes1+ candidate samples to stress-test with perturbation trials.
trialsNoNumber of perturbation trials per sample.
trainingYes2+ baseline normal samples for reference dynamics.
field_levelNo0 = real scalar field, 1 = complex field.
sensitivityNoAnomaly sensitivity multiplier (default: 1.0).
encoder_typeNoOptional encoder override. Omit to auto-detect.
perturbation_strengthNoRelative perturbation amplitude applied during instability assay.

Schema Changelog

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

  1. First observed

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, indicating safe, non-destructive behavior. The description adds 'controlled perturb-and-resolve trials,' which hints at the process but does not expand on side effects, output nature, or state implications. With annotations covering safety, the description provides marginal added value.

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 concise sentence (8 words) that front-loads the core purpose. It is efficient with no redundant language, but could benefit from a brief structual note (e.g., returning scores) without losing conciseness.

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?

Given the absence of an output schema and the presence of 7 parameters (with only 2 required), the description does not explain return values, expected output format, or how the results integrate with other waveguard tools. It is too short to be fully informative for a moderately complex tool with many siblings.

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 each parameter already has a clear description (e.g., test: '1+ candidate samples to stress-test with perturbation trials'). The tool description adds no additional meaning beyond the schema; thus, it meets the baseline of 3.

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 estimates instability under controlled perturb-and-resolve trials, using a specific verb and resource. This distinguishes it from sibling tools like waveguard_health or waveguard_scan. However, it could be more explicit about what 'instability' means in context.

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?

No guidance on when to use this tool versus alternatives like waveguard_cascade_risk or waveguard_phase_coherence. The description lacks when-to-use, when-not-to-use, or prerequisite information, leaving the agent to infer context from the name and siblings.

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

A3.9/5.0
Disambiguation5/5

Each tool has a clear, distinct purpose. While tools like waveguard_scan and waveguard_scan_timeseries both detect anomalies, their descriptions clearly differentiate structured data from time-series data. Similarly, token risk, volume check, and price manipulation tools address separate aspects of token analysis, avoiding overlap.

Naming Consistency5/5

All tools follow the consistent pattern 'waveguard_<descriptive_name>' in snake_case. The names are descriptive and predictable, making it easy to infer functionality from the name alone. No mixed conventions or vague names are present.

Tool Count4/5

19 tools is on the higher side but still appropriate given the broad domain of crypto analytics, anomaly detection, and market data. Each tool serves a specific purpose, and the count is justified by the comprehensive feature set. However, a few tools could potentially be merged without loss of clarity.

Completeness4/5

The tool set covers a wide range of functionalities: health check, market data fetching, fingerprinting, similarity comparison, anomaly detection (structured and time-series), risk assessment (token, price manipulation, volume, wallet), counterfactuals, and interaction matrices. Some minor gaps exist, such as missing data export or visualization tools, but core workflows are well-supported.

Resources