get_liquidity_map[CONTEXT] Net cross-asset liquidity map: Fed net liquidity, stablecoin dry-powder, total perp OI, liquidation pressure, net taker flow. Answers 'where is liquidity?'. Mirrors REST /liquidity. Descriptive, not advice.
| Name | Required | Description | Default |
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds valuable context: it is descriptive, not advice, and it enumerates the exact components returned. This goes beyond the annotations and helps the agent understand what to expect from the tool without contradicting any annotation.
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?
The description is extremely concise: a single sentence with a list and a clear tag. Every phrase earns its place, and the 'Answers "where is liquidity?"' line is a effective summary that helps the agent quickly grasp the tool's purpose.
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?
For a zero-parameter, read-only tool with no output schema, the description is quite complete. It names the key content areas and clarifies the descriptive nature. It doesn't detail the exact format or units, but that is less critical given the simplicity and the annotations.
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 the schema is trivially complete. The description adds no parameter-specific information because none is needed, but it does enrich the understanding of the output semantics by listing the liquidity components, which is useful context.
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?
The description clearly states the tool's function: it provides a net cross-asset liquidity map with specific components (Fed net liquidity, stablecoin dry-powder, total perp OI, liquidation pressure, net taker flow). It explicitly answers the question 'where is liquidity?' and distinguishes itself from siblings like get_liquidation_map by focusing on liquidity rather than liquidations.
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 clear context on when to use the tool (to understand overall liquidity) and even notes that it is 'descriptive, not advice', setting expectations. However, it does not explicitly mention alternatives or exclusion criteria, though its singular purpose strongly implies usage.
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 have clearly distinct purposes with detailed descriptions, but there are clusters of similar concepts (e.g., get_liquidity_map vs get_liquidation_map, get_state vs get_state_brief, multiple signal-related tools) that could cause misselection despite thorough documentation.
All tools follow a consistent lowercase verb_noun pattern, predominantly get_* nouns, with only a few non-get verbs like list_signals, rank_trades, log_trade, etc., but the style is uniform.
With 52 tools, the surface is extremely heavy for an agent to navigate. While the server's scope is broad, the count far exceeds the typical 3-15 range and falls into the 'too many' category.
The tool set covers the full lifecycle for journaling, signals, market analysis, and proof, with no major dead ends. Minor gaps exist, such as no dedicated get_trade_by_id (workaround via get_journal) and no get_market_state tool despite being referenced in get_state.