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Get Conviction Score

get_conviction_score
Read-only

Aggregates funding outlier, whale imbalance, OI/volume ratio, and momentum into a single directional score (-100 short ↔ +100 long) plus a 0-100 strength score. One call replaces 6+ lookups, returns a clean number for LLM decisions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assetYesAsset ticker to analyze, e.g. "BTC", "ETH", "HYPE"
whale_window_minutesNoLookback window for whale trades (default: 60min)
min_whale_notional_usdcNoWhale trade threshold in USDC (default: 25,000)

TDQS

A4/5.0
Behavior3/5

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

Annotations already provide readOnlyHint and openWorldHint. The description adds that the tool returns a clean number for LLM decisions but does not discuss data freshness, update frequency, or whether score is real-time. Adds some context beyond annotations.

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?

Two concise sentences that front-load purpose and value, with no extraneous information. Every sentence earns its place.

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?

Given the tool's complexity and existence of many sibling indicators, the description positions it well as a composite. No output schema, but output is adequately described. Could add constraints like supported assets or data freshness, but overall sufficient for careful use.

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

Parameters3/5

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

Schema coverage is 100%, so baseline 3. Description mentions the aggregated components (funding outlier, whale imbalance, etc.) but does not elaborate on parameter details beyond what the schema already provides for asset, whale_window_minutes, and min_whale_notional_usdc.

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?

Description clearly states it aggregates four factors into a directional score (-100 to +100) and strength score (0-100), and explicitly says it replaces 6+ lookups, distinguishing it from other tools.

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

Usage Guidelines4/5

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

Implies use as a higher-level decision tool over individual lookups ('one call replaces 6+ lookups'), but does not explicitly state when not to use or name specific alternatives among the many sibling indicator tools.

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

A3.7/5.0
Disambiguation3/5

Many tools are specialized, but several pairs have fuzzy boundaries: e.g., get_funding_rates vs get_top_funding_rates, get_basic_macro vs get_macro_context, get_simple_iv vs get_options_iv. An agent could easily select the wrong one.

Naming Consistency4/5

Most tools follow a 'get_X' pattern with descriptive noun phrases. There are a few exceptions like 'create_api_key' and 'search_markets', but overall the convention is consistent and readable.

Tool Count2/5

With 47 tools, the server is overloaded. While the domain is broad, this many tools makes discovery and selection difficult for an agent, reducing coherence.

Completeness5/5

The tool set covers an impressively wide range: macro data, funding, prediction markets, OI history, whale tracking, risk analytics, position sizing, backtesting, and signal generation. It leaves no obvious gaps for a crypto trading assistant.