get_signal_with_context[RAW FEED — detail+context] Composite call: signal + same-asset S/R levels + active macro bias. Saves 2-3 round trips. Returns a dict (not a typed model — the composite shape varies).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds valuable context beyond that: it returns a dict rather than a typed model and notes that the composite shape varies. This warns the agent about an unstable return structure, which is a meaningful behavioral disclosure beyond the structured 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 extremely concise—two sentences—and every clause carries meaning: the composite nature, the included context elements, the efficiency benefit, and the return type caveat. No filler or repetition, and the front-loaded label adds useful categorization.
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?
With an output schema present, the description need not detail return values, but it still discloses the dynamic shape. The composite scope is clearly explained, and the single required parameter is a minor ambiguity. Overall, the tool description is nearly complete for a read-only tool with annotations and output schema.
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 0%, and the description does not explain the 'id' parameter at all. With no compensatory detail about what id refers to (e.g., signal ID, asset ID, trade ID), the agent is left to guess, making this a significant gap in a low-coverage scenario.
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 is a composite call combining signal, same-asset S/R levels, and active macro bias. It distinguishes itself from simpler siblings like get_signal, get_levels, and get_macro by highlighting the composite nature and saved round trips, though it does not explicitly name those alternatives.
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 phrase 'Saves 2-3 round trips' implies the tool is intended when you need signal plus context and want efficiency, but it does not explicitly state when to use it versus calling separate tools. No exclusions or alternative naming are provided, leaving usage guidance only implicit.
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 clearly distinct purposes with detailed descriptions, but there are clusters of similar concepts (e.g., get_liquidity_map vs get_liquidation_map, get_state vs get_state_brief, multiple signal-related tools) that could cause misselection despite thorough documentation.
All tools follow a consistent lowercase verb_noun pattern, predominantly get_* nouns, with only a few non-get verbs like list_signals, rank_trades, log_trade, etc., but the style is uniform.
With 52 tools, the surface is extremely heavy for an agent to navigate. While the server's scope is broad, the count far exceeds the typical 3-15 range and falls into the 'too many' category.
The tool set covers the full lifecycle for journaling, signals, market analysis, and proof, with no major dead ends. Minor gaps exist, such as no dedicated get_trade_by_id (workaround via get_journal) and no get_market_state tool despite being referenced in get_state.