Prediction market signals from Polymarket paper trading bot — strategy performance, active trades, signal feed
| Name | Required | Description | Default |
|---|---|---|---|
| view | No | View type: stats (strategy performance), trades (recent trades), prediction (active signals) | |
| limit | No | Max results for trades view (default: 10) |
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?
With no annotations present, the description carries the burden of behavioral disclosure. It indicates this is a data/signal feed from a paper trading bot and lists output categories, which implies a read-oriented monitoring tool. It does not explicitly state read-only behavior, freshness, pagination, or whether any side effects occur, so some gaps remain.
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 a single, tightly written sentence with no filler. It front-loades the key domain and source, then uses an em dash to enumerate the main output categories. Every word 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?
For a simple tool with two optional parameters and no output schema, the description plus schema provide sufficient context to select and invoke correctly. The enum view values align well with the output categories. A small gap is the lack of stated default behavior when 'view' is omitted, and no explicit mention of read-only safety, but overall it is reasonably complete.
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 input schema fully documents both parameters: 'view' has an enum with explanatory descriptions, and 'limit' states max results and default. The description adds no parameter-level detail, but because schema coverage is 100%, the baseline of 3 is appropriate.
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 identifies the resource—prediction market signals from a Polymarket paper trading bot—and names the content categories (strategy performance, active trades, signal feed). It lacks a specific verb like 'retrieve' or 'list', and it does not explicitly contrast with sibling tools, though the domain specificity makes its purpose clear.
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?
Usage is implied: an agent would call this tool to inspect Polymarket paper trading strategy stats, recent trades, or active signals. However, the description does not explicitly state when to prefer this over sibling tools or provide any exclusions, leaving some inference required.
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.