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 full burden. It transparently states the exact output content (eight named skills and the selected one). It does not disclose any side effects (none expected for a getter) or error conditions, but for a simple read operation this is sufficient and not misleading.
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, dense sentence that front-loads the core purpose ('Trading skill catalog + currently active overlay') and then provides the specific skill identifiers. Every word earns its place; there is no fluff.
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 parameterless getter with no output schema, the description fully specifies what the agent will receive: the complete list of skills and the active one. Nothing an agent needs to understand the tool's contract is missing.
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 schema coverage is trivially 100%. The description adds no parameter-specific information, which is fine; the baseline of 4 applies per the rubric for zero-parameter tools.
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 it returns a trading skill catalog and the user's active overlay. It enumerates the exact skill identifiers, leaving no ambiguity about what is returned. It is easily distinguished from siblings like set_skill_overlay, which modifies the 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 purpose is self-evident: to read the skill catalog and current selection. It provides clear context for when to use it (e.g., before decision-making or before set_skill_overlay), but it does not explicitly state when not to use it or name an alternative. The absence of parameters and the clear read-only intent make it a minor gap.
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.
Execution and settings tools are clearly separated, but there is a dense cluster of analytical getters (get_view, get_reading, get_signals, get_assembly) that all return market verdicts and coordinates; their boundaries are only clear after reading the long descriptions. get_market_state versus get_state_timeline is cleaner, but the overlap among the analysis-verdict tools could still cause misselection.
All tools share the decker_ prefix and a consistent snake_case verb_noun pattern (get_* for reads, place_order/close_position/update_protective_stops/set_skill_overlay/validate_intent for actions). There is no mixing of naming conventions or vague generic verbs.
Thirteen tools is within the ideal well-scoped range for an execution-plus-analysis server. Each tool maps to a distinct responsibility (state reading, timeline history, signals, execution, position management, user settings, pre-trade validation), so none feels like filler.
The lifecycle is well covered: validate_intent → place_order → get_positions → update_protective_stops → close_position, with signal/analysis and skill-overlay tools around it. Minor gaps like a dedicated account-balance or full order-history tool are absent, but the execution engine handles caps server-side and closed round-trips are included in get_positions.