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detect_market_regime

Classify current market state into one of the known market regimes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesTicker symbol
intervalYesTimeframe
token_idNoOptional Manus access token. Paid tools use tokenized service access, not a monthly subscription: when token_id is omitted the server returns payment_required with a Solana Pay invoice, and after payment you retry with the same token while the server uses Manus token/resolve to recover pending access.
timestampNoUnix timestamp for detection
queryLengthYesLength of price vector to analyze

Schema Changelog

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

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It only states the tool's classification purpose and gives no details about read-only nature, required historical data, potential side effects, or edge cases. The absence of any behavioral caveats is a notable gap.

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 a single, front-loaded sentence with no wasted words. It immediately communicates the core function and is appropriately sized for a straightforward classification task.

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?

Despite having a complete input schema, the description omits any information about return values, output format, or required market data length. With no output schema and no behavioral context, the description is insufficient for an agent to fully understand what the tool produces or what conditions affect its results.

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?

The input schema covers all five parameters with descriptions, achieving 100% schema_description_coverage. The tool description adds no extra parameter guidance, but the schema sufficiently documents the inputs, so the baseline score of 3 is appropriate.

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 specific verb ('classify') and resource ('market state into known market regimes'), clearly stating what the tool does. It is distinguishable from sibling tools by its focus on regime detection, though it doesn't explicitly name alternative tools for differentiation.

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 is provided on when to use this tool versus alternatives. There is no mention of prerequisites, ideal scenarios, or exclusions, leaving the agent without context for tool selection or invocation timing.

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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