BRS Signals

get_dashboard

The full picture in one call (free key). Use the individual tools when you want one answer cheaply; use this when you want everything at once.

Bundle: regime + signal + funding + suppressed signals.

Returns: - regime_meta: Full regime classification with confidence and range info - signal: Latest bullish/bearish/WAIT with confidence and reasoning - funding: Cross-exchange funding squeeze data - suppressed: Signals that were filtered by the noise detector - cycle_context: Time cycle analysis (if available) - options_context: Deribit options market context (if available)

This is the most comprehensive single endpoint — use it when you want the full picture in one call.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.6/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden and delivers detailed return-contract information: regime_meta, signal, funding, suppressed, cycle_context, options_context, including conditional 'if available' fields. It does not explicitly discuss side effects or errors, but as a read-only dashboard getter the return details provide sufficient transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a short usage comparison, a bundle summary, and a bulleted return list. The only redundancy is repeating 'full picture in one call' at the start and end, which slightly detracts from conciseness but does not undermine clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter aggregate endpoint with an output schema, the description is complete: it explains the tool's scope, names the bundled data sources, lists the returned fields, notes conditional availability, and gives usage context relative to siblings. Nothing needed for correct selection or invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the input schema is already fully covered. The rubric baseline for 0 parameters is 4; the description appropriately spends no space on parameter details and instead documents what the caller receives.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies this as an aggregate dashboard endpoint: 'The full picture in one call' and 'Bundle: regime + signal + funding + suppressed signals.' It names the specific resource and distinguishes it from the individual sibling tools that return single answers.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit guidance is given: 'Use the individual tools when you want one answer cheaply; use this when you want everything at once.' It directly addresses when to prefer this tool over the alternatives, which are its siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4/5.0

Disambiguation4/5

Tools like get_convergence, get_directional_bias, and get_dashboard are related but clearly scoped: convergence checks sensor agreement, directional_bias gives the trade call, dashboard bundles everything. Mempool fees vs stats are distinct (rates vs pending tx). Some overlap exists between convergence/regime_current, but descriptions disambiguate well.

Naming Consistency5/5

All tools follow a consistent get_verb_noun pattern (get_block_tip, get_funding_divergence, get_system_health). The only exception is query_db, which uses 'query' instead of 'get', but it still follows the verb_noun structure and same snake_case style. No mixed conventions.

Tool Count4/5

15 tools is at the high end of the ideal range, but each serves a distinct function in a complex domain: sensor convergence, regime, funding, gamma, mempool, system health, audit. The Pro/free tier adds some apparent duplication (get_convergence vs get_directional_bias), but they address different questions.

Completeness5/5

The tool set covers the full workflow: convergence check, directional call, regime context, specialized indicators (funding, gamma, stablecoin flows, fee histogram), mempool data, system health, audit trail, and a queryable database. No obvious dead ends; public signal history and counters support verification.

Resources

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