get_confluence_signalsReturn public cached Confluence v1 signals. Scores are ordinal heuristic ranks, not probabilities.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum signals returned by the public API when supported. | |
| window | No | Confluence window in days. |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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?
Annotations already indicate readOnlyHint, idempotentHint, and destructiveHint=false. The description adds that signals are cached and scores are ordinal heuristic ranks (not probabilities), which provides behavioral context beyond the annotations.
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 two sentences, front-loaded with the core purpose, and every sentence adds value. There is no wasted text.
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?
Given the presence of a complete output schema and comprehensive annotations, the description is adequate. It adds context about cached data and ordinal scores, which rounds out the tool's behavior.
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 description coverage is 100%; the schema itself documents both parameters (limit, window) with defaults, ranges, and descriptions. The description does not add any additional parameter semantics beyond what the schema already provides.
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 returns public cached Confluence v1 signals and specifies that scores are ordinal heuristic ranks. It uses a specific verb and resource, but does not explicitly differentiate from siblings like get_confluence_methodology or get_signal_history.
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?
There is no guidance on when to use this tool versus alternatives, no mention of prerequisites or exclusions. The description does not help the agent decide which tool to invoke.
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 distinct purposes, but there is potential confusion between get_confluence_signals and get_signal_history (both dealing with signals) and between get_fund and get_stock (both about holdings). Descriptions help clarify, but minor overlap remains.
All tool names follow a consistent verb_noun pattern (e.g., get_fund, list_funds, preview_watchlist) and use snake_case throughout, making them predictable and easy to understand.
With 13 tools, the server is well-scoped for its domain of 13F filings and research. Each tool serves a clear function, and the count is neither too sparse nor overwhelming.
The tool set covers key operations like listing funds, getting holdings, signal history, and quality warnings. However, it lacks a tool for searching tickers or funds by name, which could be a minor gap for some use cases.