Trading skill catalog + currently active overlay for this user. Returns 8 published skills (conservative_v0/standard_v0/aggressive_v0/default_v0/scalp_v0/tight_v0/wide_v0/swing_v0) and the user's selected one.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It does disclose the exact returned content (8 published skills plus the active selection), which is helpful. However, it does not explicitly state that this is a non-mutating read, how freshness works, or what happens when no skill is selected.
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 entire description is one efficient, front-loaded sentence. The exact skill list adds useful precision without unnecessary length, and every phrase 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 zero-parameter read tool with no output schema, the description gives the agent a clear expectation of both the fixed catalog and the active overlay. It could be slightly more explicit about the return shape of the 'selected one,' but this is a minor gap.
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 and 100% schema coverage, so there is nothing for the description to add about arguments. The baseline of 4 applies because the schema fully covers this dimension.
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 uses a precise verb and resource: 'Returns 8 published skills... and the user's selected one.' It enumerates every skill name, making the tool's purpose concrete and unambiguous, and it is clearly distinct from mutation siblings like set_skill_overlay.
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 implies a read-only catalog/overlay use case but gives no explicit guidance about when to use this tool versus alternatives such as set_skill_overlay or get_reading. It lacks any when-to-use or when-not-to-use guidance.
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.
Each tool targets a distinct purpose: state readings (raw vs. view vs. AI-synthesized), signals vs. historical triggers, execution (place/close/update stops), pre-trade validation, and skill management. Cross-references between tools (e.g., get_signals vs. get_trigger_history) explicitly clarify boundaries, leaving no ambiguity about which tool to call.
All tools follow a consistent verb_noun pattern with the 'decker.' prefix: get_* for reads, place/close/update for actions, set_* for settings, and validate_* for checks. This uniformity makes the tool surface predictable and easy to navigate.
14 tools is well-scoped for a comprehensive trading engine MCP, covering state observation, signal generation, execution, risk management, and user configuration. Each tool earns its place and there are no redundant or missing core functions.
The tool surface covers the full trading lifecycle: reading market state (multiple layers), obtaining signals and historical triggers, checking positions, opening/closing positions, updating protective stops, validating intent before orders, and managing skill overlays. The absence of a cancel_order tool is explicitly justified (only market orders), and the domain shows no obvious gaps.