Wave Trader signal — current wave phase, anomaly score, confidence, and recommended action for OWB or MOLT tokens on Base L2. Real-time market analysis.
| Name | Required | Description | Default |
|---|---|---|---|
| token | Yes | Token symbol: OWB or MOLT |
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 provided, so the full burden is on the description. It discloses the signal payload (wave phase, anomaly score, confidence, recommended action) but does not define what output shape looks like or what the values mean. For a real-time market signal tool, agents need unit/threshold context to act on results; without an output schema, the description should disclose more.
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 sentences, direct, and front-loaded with the core purpose. Wastes no tokens. The second sentence adds a small amount of useful context.
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?
Description covers what data comes back (signal fields) but not the output structure, threshold interpretation, or urgency. For a decision-support tool, agents need more context on how to interpret the recommended action and what to do with a NON-urgent signal.
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?
Schema coverage is 100% with a clear enum description. The description repeats that the tokens are OWB or MOLT but adds no additional context about the parameter beyond the schema.
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 a specific action (signal analysis) and resource (OWB/MOLT tokens on Base L2). Clear distinction from generic market tools. However, does not explicitly differentiate from prediction_signals sibling.
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?
Implied usage: for tokens OWB or MOLT; use when real-time wave analysis needed. Does not state when NOT to use it or name alternatives like prediction_signals or get_prices.
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.
Multiple signal tools (front_run_watch, prediction_signals, wave_signal) serve similar purposes and could be confused, though each has a distinct data source. Similarly, soul_insights and soul_stack_feed both present agent-generated content, creating some ambiguity.
All names use snake_case, but there's no consistent pattern: some are verb-first (get_prices, search_products), some are brand-prefixed nouns (soul_bounties, wave_portfolio), and mixed usage like daloopa_query and soul_verify. The inconsistency is readable but not predictable.
16 tools for a multi-source market data server is reasonable; there are no outright redundant tools, though a few (think, fusion_capabilities) feel auxiliary. The count is slightly above ideal but well within acceptable bounds.
The server provides extensive read-only browsing (soul_bounties, soul_insights) but lacks corresponding action tools like claiming a bounty or purchasing insights, creating dead ends. For a 'market', there are no execute/trade/buy operations, leaving significant gaps for agent workflows.