Liquid State's premium trading guides — title, one-line description, tags, page count, price (USD), url. Paid content, not free — price is always disclosed. Use when the user wants an in-depth trading education resource (risk management, position sizing, trend-following, etc.).
| Name | Required | Description | Default |
|---|---|---|---|
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Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It clearly flags that content is paid and price is always disclosed, and it enumerates the fields returned, giving a solid sense of output. Auth and side effects are not mentioned, but a zero-parameter catalog read needs little additional disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tight sentences with no filler: the first lists what the tool returns, the second covers the paid-content caveat and the use condition. Information is front-loaded and every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the field enumeration sufficiently tells an agent what to expect in the response. The use trigger and pricing caveat fill out the context needed for a simple, zero-parameter list tool, so nothing essential is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so there is no ambiguity for an agent to resolve. Baseline 4 applies because the schema is trivially complete and the description does not need to compensate for any parameter documentation gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States the resource (Liquid State's premium trading guides) and enumerates the returned fields (title, description, tags, page count, price, URL). 'Premium' and 'education resource' clearly separate it from lighter sibling offerings like get_briefs or market data tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives an explicit 'Use when...' trigger tied to in-depth trading education topics such as risk management and position sizing. It does not explicitly name alternative tools or list when-not-to-use conditions, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are clearly distinct, but get_market_overview and get_market_state both return funding and price snapshots for BTC/ETH/SOL, with get_market_state adding OI, liquidations, and a regime signal. get_derivatives also overlaps with get_market_state on funding and open interest at the single-asset level, which could cause an agent to pick the wrong tool.
All six tools follow a consistent get_<resource> naming pattern with clear, descriptive nouns. There are no mixed casing styles, vague verbs, or inconsistent conventions.
Six tools is a well-scoped size for a crypto market intelligence server. Each tool has a distinct role in the set: news briefs, derivatives data, guides, market overview, market state, and track record.
The tool surface covers the core intelligence workflows well: recent analysis, derivatives data, market snapshots, educational content, and a verifiable track record. Minor gaps exist, such as no historical data endpoints and limited spot-price coverage beyond BTC/ETH/SOL, but agents can generally work around these.
