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Glama

DPX — Institutional Cross-Border Settlement

intelligence.resonance

Read-onlyIdempotent

Resonance Intelligence — detects when multiple independent macro forces are oscillating in phase across 28 signals in 5 domains, amplifying each other rather than cancelling. A single shock is manageable; resonance turns a bad quarter into a systemic crisis. Returns per-signal phase angles, resonance clusters (groups of 3+ aligned signals), amplitude amplification factor, system resonance score (0–100), and historical danger-zone comparison to crisis precedents (2008, 2011, 2020, 1997 EM). No input required — GET.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
synthesisNo
dangerZoneMatchNoSimilarity to historical crisis resonance patterns.
resonanceClustersNoGroups of 3+ signals in mutual resonance.
amplificationFactorNoConstructive interference gain across dominant cluster.
systemResonanceScoreNo0–100. Higher = more dangerous in-phase alignment.

Schema Changelog

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

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful behavioral context beyond this: it specifies 'No input required — GET,' and details the exact return payload (per-signal phase angles, resonance clusters, amplification factor, system resonance score, historical comparison). This goes beyond the minimal annotation coverage.

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 dense and front-loaded with the core purpose, then elaborates with a vivid analogy and a clear enumeration of outputs. While slightly long, every sentence contributes functional or contextual information, and the structure flows logically from purpose to behavior to output. The final GET note is economical.

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?

Given the tool has no parameters and a rich output schema, the description is fully complete: it explains the conceptual trigger, the signal scope (28 signals, 5 domains), the amplification concept, the exact return fields, and the historical comparison references. The description leaves no material questions about when or how to invoke the tool.

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 tool has zero parameters, so the baseline is 4. The description reinforces this with 'No input required — GET,' leaving no ambiguity about invocation. There is no schema-level parameter detail to compensate for, and the description adds sufficient clarity for a parameterless tool.

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-resource pair: 'detects when multiple independent macro forces are oscillating in phase,' clearly identifying what the tool does. It further distinguishes itself by contrasting a single shock with resonance and explicitly listing the output categories, making it distinct from sibling tools like intelligence.contagion or intelligence.aftershock.

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

Usage Guidelines3/5

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

The description implies usage for detecting systemic resonance ('detects when multiple independent macro forces are oscillating in phase'), and the phrase 'A single shock is manageable; resonance turns a bad quarter into a systemic crisis' gives conceptual context. However, it does not explicitly state when to use this tool over alternatives or mention any exclusions, leaving the comparative guidance to inference.

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

A3.6/5.0
Disambiguation2/5

Many tools have overlapping purposes, such as multiple stablecoin routing options (route vs stability.stablecoin_route), several compliance pre-checks (flow_check, policy.check, mercury.ach_authorize), and numerous FX/stability tools (oracle.stability, stability.corridor, market.fx, fx.rate). Even with detailed descriptions, the boundaries are subtle and an agent could easily select the wrong tool.

Naming Consistency3/5

The dot-separated namespace convention is mostly consistent and readable, but verb vs noun usage varies (e.g., settlement.execute vs batch_settle vs route). Subscription tools also mix forms (intelligence.subscribe vs intelligence.subscription.get/delete), showing minor inconsistency.

Tool Count1/5

81 tools is an extreme count for a settlement server. Even accounting for the broad 'institutional' scope, the volume overwhelms the core purpose and creates a heavy cognitive load for agents, far beyond the typical 3-15 well-scoped tool set.

Completeness3/5

The core settlement lifecycle is well-covered (quote, execute, track, receipt, batch), but there are notable gaps such as missing policy update/delete and no receipt retrieval (only create). While many tangential domains are over-covered, certain CRUD operations are absent, creating dead ends.