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Sector Rotation

get_rotation
Read-only

[CONTEXT] Altseason/rotation read: is capital rotating INTO alts (altseason) or back to BTC (risk-off)? rotation_score in [-1,1] from relative-strength breadth + correlation trend. Breadth is a PROXY, not true BTC dominance. Uncalibrated heuristic. Same data as REST /rotation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
regimeNo
breadthNo
disclaimerNo
rotation_scoreNo
sufficient_dataNo
top_rotating_inNo
top_rotating_outNo

TDQS

A3.9/5.0
Behavior4/5

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

The description discloses that breadth is a proxy, not true BTC dominance, and that the heuristic is uncalibrated, adding context beyond the readOnlyHint annotation. This is valuable transparency about the tool's limitations.

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

Conciseness5/5

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

The description is brief, front-loaded with context, and each sentence adds substantive information. The caveats are concise and the text is well-structured.

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

Completeness4/5

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

For a parameterless read-only tool with an output schema, the description covers the concept, calculation basis, and limitations. It does not explain when to use it, but that is covered elsewhere, and the lack of parameters simplifies the context.

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?

There are no parameters, so the baseline of 4 applies. The description adds context about the output (rotation_score range) that compensates for any lack of input semantics.

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

Purpose4/5

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

The description clearly states the tool reads sector rotation/altseason, explaining the output metric rotation_score and its interpretation. It distinguishes itself by focusing on capital rotation between alts and BTC, though it does not explicitly name sibling tools.

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

Usage Guidelines3/5

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

The description implies when to use this tool when assessing altseason or risk-off sentiment, but it does not explicitly state when not to use it or which alternative tools to prefer. The caveats about being a proxy and uncalibrated are helpful but don't constitute usage guidance.

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

A4.1/5.0
Disambiguation4/5

Most tools have distinct purposes, but a few pairs like get_liquidation_map vs get_liquidity_map and multiple signal-fetching tools (get_signal, get_signals_since, list_signals, get_actionable_signals) could be confused without careful description reading. Overall, each tool has a clearly defined role, so the ambiguity is limited.

Naming Consistency4/5

The naming is overwhelmingly consistent: snake_case verb_noun patterns like get_price, list_signals, close_trade, and amend_trade. The exception is 'health' as a plain noun, and a few compound verbs like find_similar_signals, but the overall pattern is strictly followed.

Tool Count2/5

With 52 tools, this is far beyond the typical well-scoped range and falls into the 'too many' category. The broad platform scope justifies many tools, but the sheer number makes the set heavy and harder for an agent to navigate efficiently.

Completeness5/5

The surface covers the full lifecycle: journal management (log, amend, close, void, read), trade vetting (check, plan, rank), signal discovery (list, get, actionable, similar), market data (price, levels, indicators, options), context (macro, liquidity, flows), forensics (manipulation, trust, narrative), and meta (playbook, usage, health). No obvious gaps or dead ends.

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