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Glama

AgentData — crypto market data with a checkable record

by io.github.speteai

watch_condition

Register a standing condition and let the always-on server watch it for you ($0.010 USDC, up to 168h). An agent only exists while it runs and cannot wait; this is that missing faculty. Poll watch_status free instead of paying for repeated data calls.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
opYes
hoursNolifetime, 1-168, default 24
signalYes
paymentNoOptional. Base64 x402 payment payload you signed yourself (ERC-3009 TransferWithAuthorization, USDC on Base). Call without it once to receive the payment requirements, sign those, then call again with this argument. This server forwards the payload and never holds a key.
subjectNoe.g. BTC_USDT
thresholdYes

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / properties / payment
      Added value: +{
+  "description": "Optional. Base64 x402 payment payload you signed yourself (ERC-3009 TransferWithAuthorization, USDC on Base). Call without it once to receive the payment requirements, sign those, then call again with this argument. This server forwards the payload and never holds a key.",
+  "type": "string"
+}
  2. Added

TDQS

A4/5.0
Behavior4/5

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

Even though no annotations exist, the description discloses key behavioral traits: it costs $0.010 USDC, has a 168-hour lifetime, and creates a server-side standing condition. It stops short of explaining cancellation, error handling, or the exact effect of payment failure, but the cost and persistent side effect are usefully revealed.

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 three sentences and front-loaded with the most critical info: purpose, cost, and duration. Each sentence earns its place, including the alternative polling mechanism. No redundant content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no annotations and no output schema, the description gives a good high-level context but leaves out important operational details such as what the response looks like, whether a condition ID is returned, or how to know the registration was successful. It also leaves the undocumented params ambiguous. This is not fully complete for a paid, state-changing registration tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 50%, and the description does not compensate for the missing fields. It does not explain what 'signal', 'op', or 'threshold' mean or how they map to a condition. The generic phrase 'standing condition' does not make the parameter semantics clear.

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 action ('Register a standing condition') and the resource (the always-on server watching it), making the tool's purpose obvious. It also distinguishes itself from sibling getters and try_* tools, which are data-fetching operations.

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?

It explicitly describes when to use the tool (when an agent needs to wait without running) and points to watch_status as a free alternative to poll status. It does not enumerate all sibling alternatives, but the getter vs. registration distinction is clear from context.

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

All AgentData — crypto market data with a checkable record toolsInspect
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TDQS

B3.2/5.0
Disambiguation3/5

Most tools target clearly distinct metrics, but the paid/free sample pairs (get_crypto_prices/try_crypto_prices, etc.) and overlapping summary tools (get_market_overview, get_market_pulse, get_overnight_risk_brief) create some selection ambiguity. Descriptions list components, so an agent can disambiguate with effort, but the boundaries between bundles and single-purpose tools are not always obvious.

Naming Consistency5/5

Tool names consistently follow a verb_noun pattern: get_ for data retrieval, try_ for free samples, and watch_condition for persistent monitoring. All names use lowercase snake_case with no mixed conventions, making the naming predictable and easy to navigate.

Tool Count2/5

34 tools is well above the comfortable range for a typical MCP server and feels heavy even for a broad crypto data domain. The count is inflated by paid/free sample duplicates and multiple bundle variants that could have been consolidated.

Completeness4/5

The surface covers a wide range of crypto data: prices, funding, sentiment, arbitrage, derivatives, on-chain metrics, signal history, and monitoring. Minor gaps exist—such as no obvious generic signal discovery tool or order-book/trade-level data—but the core domain of market data with checkable records is thoroughly served.

Resources