Crypto market dominance: BTC.D, ETH.D and USDT.D as a percentage of total crypto market cap. Use as a regime filter (risk-on/off) and a BTC vs altcoin rotation signal.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| btcDominance | No | ||
| ethDominance | No | ||
| usdtDominance | No |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "description": "Share of total crypto market cap, in percent.",
+ "properties": {
+ "btcDominance": {
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "ethDominance": {
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "usdtDominance": {
+ "type": [
+ "number",
+ "null"
+ ]
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, fully covering the safety profile. The description adds context about the return format (percentages) and intended use, but does not disclose additional behavioral traits like data freshness or update frequency. With annotations carrying the main burden, the description provides adequate but not extra transparency.
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 two sentences long, front-loaded with the primary output definition and followed by usage guidance. Every sentence adds value, with no redundancy or 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?
Given no parameters, the presence of an output schema, and annotations covering safety, the description is complete. It explains what the tool returns, how to interpret it, and when to use it. No additional information is needed for correct invocation.
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?
There are zero parameters and schema description coverage is 100%. The description does not need to explain parameter semantics. Baseline for 0 parameters is 4, and the description meets this without adding unnecessary information.
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 explicitly states the tool returns crypto market dominance metrics (BTC.D, ETH.D, USDT.D) as percentages of total market cap. This clearly distinguishes it from sibling tools like get_crypto_market (overall market data) and get_fear_greed (sentiment), which serve different purposes.
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 description provides explicit usage guidance: 'Use as a regime filter (risk-on/off) and a BTC vs altcoin rotation signal.' This tells the agent when to invoke this tool, though it does not explicitly exclude alternatives or list sibling tools for comparison. The context is clear enough for correct selection.
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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