botindex-mcp-server

Server Quality Checklist

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Latest release: v2.1.1
Disambiguation3/5
The tools are grouped by domain (e.g., Agorion, BotIndex crypto, Hyperliquid, sports, Zora), which helps with differentiation, but there is significant overlap within domains. For example, botindex_crypto_intel, botindex_crypto_tokens, and botindex_crypto_graduating all relate to crypto intelligence with unclear boundaries, and botindex_hl_whale_alerts vs. botindex_hl_whale_alerts_full are redundant. Descriptions provide some clarity, but agents may struggle to choose between similar tools.
Naming Consistency5/5
Tool names follow a highly consistent pattern: most start with 'botindex_' or 'agorion_' as a prefix, followed by descriptive snake_case terms (e.g., 'crypto_intel', 'sports_odds'). This consistency makes the set predictable and easy to parse, with no mixing of naming conventions like camelCase or irregular verbs.
Tool Count2/5
With 38 tools, the count is excessive for a single server, indicating poor scoping. While the domain (crypto, sports, prediction markets) is broad, many tools could be consolidated (e.g., multiple Hyperliquid or Zora tools). This volume risks overwhelming agents and suggests fragmentation rather than a cohesive toolset.
Completeness4/5
The toolset covers a wide range of domains (Agorion discovery, crypto analytics, sports betting, prediction markets) with detailed operations like scanning, analytics, and intelligence. Minor gaps exist, such as no explicit update or delete tools, but these are less relevant for the data-focused domain. Overall, it provides comprehensive coverage for its intended purposes.
Average 3/5 across 38 of 38 tools scored. Lowest: 1.8/5.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 2 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on March 15, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description fails to explain key behaviors such as whether this is a read-only operation, if it requires authentication, rate limits, pagination, or what the output format looks like. The $0.01 reference is ambiguous and doesn't add meaningful context about the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief but not well-structured or front-loaded. It consists of three disjointed phrases that don't form a coherent sentence, with the $0.01 reference being particularly confusing and wasteful. While short, it lacks clarity and effective communication of the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool that presumably returns data about token launches. It doesn't explain what information is returned, the data format, or any behavioral aspects. For a tool with one parameter but potentially complex output data, the description fails to provide adequate context for effective 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?
The input schema has 1 parameter with 100% description coverage ('limit' with description 'Max results (default 10)'), so the schema provides complete parameter documentation. The description adds no additional information about parameters, but with high schema coverage, the baseline score is 3 as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Recent Doppler token launches on Base' which indicates the tool retrieves recent token launches, but it's vague about the exact action (e.g., list, fetch, display). It mentions 'New creator coins via Doppler liquidity protocol' which adds context but doesn't clarify the tool's function. The $0.01 reference is unclear and potentially misleading. It doesn't effectively distinguish from sibling tools like botindex_solana_launches or botindex_crypto_tokens.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention any prerequisites, context for use, or comparisons to sibling tools like botindex_doppler_intel or botindex_crypto_graduating. The description lacks any explicit or implied usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'Premium' and a cost '$0.05', hinting at a paid service, but doesn't disclose behavioral traits like rate limits, authentication needs, data format, or what 'reasoning trace' means operationally. This leaves critical gaps for an agent to understand how to invoke it effectively.
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 brief and front-loaded with the core purpose, though it includes an extraneous cost detail that doesn't aid tool selection. It avoids unnecessary elaboration, making it efficient but slightly cluttered with pricing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete. It lacks details on what the tool returns (e.g., trace format), behavioral constraints, or how it fits among sibling tools. For a tool with potential complexity in 'reasoning trace', this leaves significant gaps for an agent to use it correctly.
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 description coverage is 100%, with the parameter 'agentId' fully documented in the schema including its enum values. The description adds no additional meaning about parameters, so it meets the baseline of 3 by not detracting from the schema's completeness.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Premium reasoning trace for a specific agent' restates the tool name 'botindex_agent_trace' with minimal elaboration, making it tautological. It adds 'Premium' and 'reasoning trace' but doesn't specify what a reasoning trace entails or what resource it accesses, leaving the purpose vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling tools like 'botindex_discover' or 'botindex_signals', the description fails to differentiate this tool's specific use case or context, offering no help for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'early signal' and '$0.03,' hinting at cost or value, but doesn't explain what the tool returns (e.g., list of trends, scores), how it calculates momentum, rate limits, authentication needs, or error handling. For a tool with no annotations, this leaves significant behavioral gaps.
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 brief and front-loaded with key concepts ('attention momentum,' 'Zora trends,' 'early signal'), but includes an extraneous detail ('$0.03') that might confuse without context. It's efficient overall, with two sentences that convey the core idea without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool that likely returns complex trend data. It lacks details on return format, data freshness, how 'momentum' is defined, and error cases. For a tool named 'attention_momentum' in a crypto/analytics context, more behavioral and output context is needed to be fully helpful.
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?
The input schema has 1 parameter with 100% description coverage ('limit' with default 20). The description adds no parameter-specific information beyond what the schema provides. Since schema coverage is high, the baseline is 3, as the description doesn't compensate but also doesn't detract from the schema's documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool identifies 'which Zora trends are accelerating' and calls it an 'early signal for emerging attention markets,' which gives a vague purpose. It mentions 'Zora trends' but doesn't specify what type of trends (e.g., tokens, NFTs, creators) or what 'attention momentum' means operationally. It distinguishes from some siblings by focusing on Zora and momentum, but the purpose remains somewhat abstract.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions 'early signal for emerging attention markets,' which implies a use case for detecting trends, but doesn't specify scenarios, prerequisites, or compare it to sibling tools like 'botindex_zora_trending_coins' or 'botindex_zora_intel.' Without explicit when/when-not instructions, usage is unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'premium signals' and a cost ('$0.10'), implying a paid or premium service, but doesn't disclose behavioral traits like rate limits, authentication needs, data freshness, or what 'aggregated' entails. The cost hint is vague and doesn't clarify if it's per call, subscription, or something else.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief but not optimally structured. It lists signal types efficiently but includes the confusing '$0.10' without explanation, which doesn't earn its place. It's front-loaded with the core purpose but could be clearer by omitting or explaining the cost suffix.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a tool that likely returns complex signal data, the description is incomplete. It names signal types but doesn't explain the format, scope, or interpretation of results. For a tool with 'aggregated' data and potential cost implications, more context on what to expect is needed.
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 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description doesn't add parameter semantics, which is fine here. Baseline is 4 for zero parameters, as the schema fully covers the absence of inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool provides 'aggregated premium signals' with three specific components (correlation leaders, prediction arbitrage, market heatmap), which gives a general purpose. However, it doesn't specify what resource or data source these signals come from, and the cryptic '$0.10' suffix adds confusion rather than clarity. It distinguishes somewhat from siblings by focusing on 'signals' but lacks specificity about the domain or target.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lists signal types but doesn't indicate context, prerequisites, or comparisons to sibling tools like 'botindex_hl_correlation_matrix' or 'botindex_hl_liquidation_heatmap' that might overlap. Users must infer usage from the signal names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions '$0.02,' which might hint at a cost or fee, but this is ambiguous and not elaborated. It fails to describe critical behaviors like data format, update frequency, or any limitations, leaving significant gaps for a tool with no structured safety hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief with two short phrases, but the second phrase '$0.02' is cryptic and does not clearly contribute to understanding the tool's function. It could be more front-loaded with essential details, making it somewhat inefficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete. It lacks details on return values, data structure, or operational constraints (e.g., rate limits, authentication). The ambiguous '$0.02' adds confusion rather than completeness, failing to provide adequate context for effective use.
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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description does not add parameter information, which is acceptable here, but it includes an ambiguous '$0.02' that could be misinterpreted as a parameter-related cost, slightly detracting from clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool provides 'All tracked Metaplex Genesis token launches on Solana mainnet,' which specifies the resource (Metaplex Genesis token launches) and scope (Solana mainnet). However, it lacks a clear verb (e.g., 'retrieve' or 'list') and does not differentiate from sibling tools like 'botindex_doppler_launches' or 'botindex_solana_active,' making it somewhat vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. It does not mention prerequisites, context, or exclusions, such as how it differs from other launch-related tools in the sibling list, leaving the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'signals' and a cost ('$0.02'), suggesting it might be a paid data-fetching operation, but doesn't disclose behavioral traits like rate limits, authentication needs, output format, or whether it's read-only or mutative. This leaves key operational aspects unclear.
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 very concise—two short phrases that convey the core purpose and cost. It's front-loaded with the main function. However, the cost mention ('$0.02') feels tacked on without context, slightly reducing efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity implied by 'signals' and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the signals entail, their format, frequency, or how to interpret them. For a tool that likely returns data, more context is needed to be useful.
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 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately doesn't mention any. A baseline of 4 is applied as per the rules for zero-parameter tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool provides 'Token graduation signals from Catapult launchpad to Hyperliquid mainnet via GradSniper', which gives a specific purpose (signals about token graduation) and mentions relevant platforms. However, it doesn't clearly distinguish this from sibling tools like 'botindex_crypto_tokens' or 'botindex_crypto_intel', leaving the exact differentiation ambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes no guidance on when to use this tool versus alternatives. It mentions a cost ('$0.02'), which might imply a paid service, but doesn't specify contexts, prerequisites, or exclusions. With many sibling tools in the botindex_crypto category, this lack of differentiation is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'AI-powered' and '$0.05', hinting at cost, but doesn't disclose behavioral traits like rate limits, authentication needs, output format, or whether it's a read-only vs. mutative operation. The description is insufficient for a tool with zero annotation coverage.
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 concise with three short phrases and a cost indicator, front-loading key capabilities. However, the lack of a clear verb and structure (e.g., fragmented phrases) slightly reduces effectiveness, but it's generally efficient with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity implied by 'AI-powered crypto correlation intelligence' and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns, how results are formatted, or operational constraints, leaving significant gaps for an agent to understand and use the tool effectively.
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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter semantics, but this is appropriate given the lack of parameters. A baseline score of 4 is assigned as the description doesn't need to compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool provides 'AI-powered crypto correlation intelligence' with specific capabilities like 'regime detection, portfolio risk clusters, alpha opportunities', which gives a general purpose. However, it doesn't specify a clear verb-action (e.g., 'analyze', 'generate', 'retrieve') or distinguish itself from sibling tools like 'botindex_hl_correlation_matrix' or 'botindex_hyperliquid_intel', making it somewhat vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description mentions capabilities but doesn't indicate specific contexts, prerequisites, or exclusions. With many sibling tools in the crypto domain, this lack of differentiation leaves the agent without clear usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions the data source and cost ('$0.02'), which adds some behavioral context (e.g., potential pricing implications), but fails to disclose critical traits like rate limits, authentication needs, data freshness, or what 'latest price data' entails (e.g., update frequency). This is inadequate for a tool with no annotation coverage.
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 brief and front-loaded, consisting of two concise sentences that convey the core purpose and cost. There's no wasted text, though it could be slightly more structured (e.g., separating functionality from metadata).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (crypto data tool with no annotations or output schema), the description is incomplete. It lacks details on output format, data scope (e.g., which tokens, timeframes), and behavioral constraints, making it insufficient for an agent to use effectively without additional 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?
The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description doesn't add parameter semantics, but this is acceptable given the lack of parameters, aligning with the baseline for 0 params.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool provides 'Token universe with latest price data from MemeRadar correlation engine,' which gives a general purpose (fetching token data with price info) but lacks specificity about what 'token universe' entails or how it differs from sibling tools like botindex_crypto_intel or botindex_crypto_graduating. It's vague but not tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description mentions a source ('MemeRadar correlation engine') but doesn't specify use cases, prerequisites, or exclusions compared to sibling tools, leaving the agent with no contextual direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'AI-powered' and includes a cost ('$0.05'), hinting at a paid or rate-limited service, but it doesn't detail authentication needs, rate limits, output format, or error handling. This leaves significant gaps in understanding how the tool behaves.
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 brief and front-loaded with key information ('AI-powered Doppler launch intelligence'), but the inclusion of '$0.05' could be more integrated or explained. Overall, it's efficient with minimal waste, though slightly disjointed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete. It lacks details on what the tool returns (e.g., data format, examples), error conditions, or how it integrates with other tools. For a tool with potential complexity in 'intelligence' analysis, this leaves the agent under-informed.
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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't add parameter details, as there are none to explain, aligning with the baseline for zero parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool provides 'AI-powered Doppler launch intelligence' with 'quality scores, rug probability, creator analysis', which gives a general purpose. However, it doesn't specify what exact action the tool performs (e.g., 'fetch', 'analyze', 'generate') or clearly distinguish it from sibling tools like 'botindex_doppler_launches' or 'botindex_crypto_intel', making it somewhat vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives. The description mentions 'Doppler launch intelligence', but it doesn't explain the context or prerequisites for usage, nor does it reference any sibling tools for comparison, leaving the agent with minimal direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions a cost ('$0.05'), which hints at potential rate limits or pricing, but lacks details on execution (e.g., real-time vs. historical data, latency, error handling). This is insufficient for a tool that likely involves financial data analysis.
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 brief and front-loaded, stating the core purpose in one sentence. However, the inclusion of '$0.05' feels slightly out of place without context, slightly reducing efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of arbitrage detection and lack of annotations or output schema, the description is incomplete. It doesn't explain what the output entails (e.g., opportunity details, timestamps, confidence scores), leaving the agent unsure of what to expect upon invocation.
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 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description doesn't add parameter semantics, but this is acceptable given the lack of inputs, warranting a baseline score of 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool identifies 'funding rate arbitrage opportunities between Hyperliquid and major CEXs,' which provides a specific purpose (arbitrage detection) and resource (funding rates across platforms). However, it doesn't clearly differentiate from sibling tools like 'botindex_arb_scanner' or 'botindex_hl_correlation_matrix,' leaving ambiguity about scope overlap.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives. The description mentions a cost ('$0.05'), which implies a usage consideration, but doesn't specify prerequisites, frequency, or comparison to other arbitrage-related tools in the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions ranking, trust scores, fees, and checkout details, which adds some context about output behavior. However, it lacks critical details such as rate limits, authentication requirements, error handling, or whether the operation is read-only or has side effects. The cost hint ('$0.05') is useful but insufficient for comprehensive 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 concise and front-loaded, stating the core functionality in a single sentence. The cost hint is included efficiently. However, it could be slightly more structured by separating functional details from metadata, but overall, it avoids unnecessary verbosity and earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of comparing merchant offers across protocols and the lack of annotations and output schema, the description is incomplete. It mentions output elements like ranking and trust scores but does not detail the return format, error cases, or operational constraints. For a tool with 4 parameters and no structured output information, more context is needed to guide the agent effectively.
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 description coverage is 100%, so the schema already documents all parameters thoroughly. The description does not add any additional meaning or context beyond what the schema provides (e.g., it doesn't explain how 'q' relates to merchant offers or how 'protocol' affects results). With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
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's purpose: comparing merchant offers across specific commerce protocols (ACP, UCP, x402) with ranking, trust scores, fees, and checkout details. It uses specific verbs ('compare', 'ranked') and identifies the resource ('merchant offers'), but does not explicitly differentiate from sibling tools like 'botindex_commerce_protocols' or 'agorion_discover', which might have overlapping commerce-related functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions comparing offers across protocols but does not specify use cases, prerequisites, or exclusions. Sibling tools like 'botindex_commerce_protocols' might be related, but no explicit comparison or context is given, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions a cost ('$0.50'), which is useful behavioral context, but lacks other critical details: whether it's read-only or mutative, rate limits, authentication needs, or what happens upon invocation (e.g., opens a dashboard vs. returns data). For a tool with no annotations, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief but could be more structured. It lists components in a dash-separated format and includes cost, which is efficient, but the phrasing 'Full premium dashboard — all agents, traces...' is slightly informal and could be clearer. It's front-loaded with the main purpose, but the cost mention feels tacked on without context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and 0 parameters, the description is incomplete. It names components but doesn't explain what the tool actually does (e.g., displays data, generates a report) or the output format. For a tool with potential complexity (implied by 'premium dashboard'), more behavioral and output context is needed.
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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter info, which is appropriate. Baseline is 4 for 0 parameters, as the schema fully covers the absence of inputs.
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 provides a 'full premium dashboard' with specific components listed (agents, traces, correlation matrices, etc.), giving a good sense of what resource it accesses. It doesn't explicitly distinguish from siblings like 'botindex_hl_correlation_matrix' or 'botindex_agent_trace' which might offer similar components individually, but the 'full dashboard' concept implies a comprehensive view.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling tools offering specific components (e.g., 'botindex_hl_correlation_matrix'), the description doesn't explain if this is for an overview, when it's preferred over individual tools, or any prerequisites. The mention of '$0.50' hints at cost but doesn't clarify usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions a cost ('$0.10'), which is useful context about pricing, but fails to describe critical behaviors: whether it's a read-only or mutation operation, what permissions or inputs are needed beyond the schema, how lineups are returned (e.g., format, pagination), or any rate limits. For an optimizer tool with no annotation coverage, this leaves significant gaps in 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 concise and front-loaded, stating the core purpose in the first sentence and adding cost information in the second. There's no wasted text, and it efficiently conveys key details without unnecessary elaboration. It could be slightly improved by integrating the cost into the main sentence, but overall it's well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (an optimizer with financial and sports inputs), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'optimized lineups' entail (e.g., number of lineups, criteria), how correlations are handled, or the return format. The cost mention adds some context, but overall, it fails to provide sufficient information for an agent to understand the tool's full behavior and outputs.
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 description coverage is 100%, so the schema already documents both parameters ('budget' and 'sport') adequately. The description adds no additional meaning about these parameters—it doesn't explain expected budget ranges, sport options, or how they influence optimization. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
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's purpose: 'Correlation-adjusted DFS lineup optimizer. Returns optimized lineups accounting for player correlations.' It specifies the verb ('optimizer'), resource ('DFS lineups'), and key feature ('accounting for player correlations'), which distinguishes it from most siblings focused on crypto, sports odds, or other domains. However, it doesn't explicitly differentiate from 'botindex_sports_correlations' or other sports-related tools, keeping it from a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions a cost ('$0.10'), which implies a paid service, but doesn't specify prerequisites, constraints, or recommend other tools for different scenarios. Without any when-to-use or when-not-to-use instructions, it offers minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the analytics scope but doesn't describe what 'deep analytics' entails operationally—no information about rate limits, authentication needs, whether this is a read-only or mutating operation, response format, or any behavioral traits. The cost mention adds some context but insufficient for a mutation-capable analytics tool.
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 appropriately concise—two short phrases that communicate core functionality and cost. It's front-loaded with the main purpose. The cost mention could be considered extraneous but doesn't significantly detract from efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For an analytics tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'deep analytics' returns, how results are structured, whether there are pagination or filtering options, or any behavioral constraints. The cost mention adds some context but doesn't compensate for the missing operational details needed for effective tool 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?
The schema description coverage is 100%, so the schema already fully documents the single 'address' parameter. The description doesn't add any parameter semantics beyond what's in the schema—it doesn't clarify format expectations, provide examples beyond what the schema shows, or explain how the address affects the analytics. Baseline 3 is appropriate when schema does the heavy lifting.
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 provides 'Deep analytics for a specific Hyperliquid coin' and lists specific metrics (OI, funding, volume, liquidation history), which gives a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'botindex_hl_correlation_matrix' or 'botindex_hl_funding_arb' that might also analyze Hyperliquid data, so it doesn't reach the highest level of sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites, when this tool is appropriate versus other analytics tools in the sibling list, or any exclusions. The only contextual hint is the cost ('$0.05'), but this doesn'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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but lacks behavioral details. It mentions 'AI-powered' and '$0.05' (possibly a cost), but doesn't disclose rate limits, authentication needs, data freshness, or what 'intelligence' entails (e.g., format, confidence scores). The cost hint adds minimal value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief but could be more structured; 'Rate persistence prediction, optimal entry timing' is somewhat fragmented. It's front-loaded with core purpose, but '$0.05' at the end is ambiguous—does it indicate cost or something else? Slightly inefficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool offering 'intelligence' and predictions. It lacks details on output format, data sources, update frequency, or error handling, leaving significant gaps for an AI agent to use it effectively.
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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add param info, which is appropriate, earning a baseline 4 for not compensating unnecessarily.
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 provides 'AI-powered Hyperliquid funding rate intelligence' with 'rate persistence prediction, optimal entry timing', specifying the resource (Hyperliquid funding rates) and actions (prediction, timing). It distinguishes from siblings like 'botindex_hl_funding_arb' by focusing on intelligence/prediction rather than arbitrage, though not explicitly named.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives is provided. The description mentions 'optimal entry timing', implying usage for trading decisions, but doesn't specify contexts, prerequisites, or exclusions compared to other botindex tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'Live' (implying real-time data) and '$0.02' (possibly indicating cost), but doesn't address critical aspects like rate limits, authentication needs, data freshness, error conditions, or what 'snapshot' means operationally. The behavioral context is insufficient for a tool with no annotation coverage.
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 efficiently structured in a single sentence that packs key information: what it provides (odds snapshot), for which sports, what types of odds, and additional feature (bookmaker comparisons). The '$0.02' at the end is somewhat cryptic but doesn't significantly detract from the overall conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a simple single parameter with full schema coverage, the description provides adequate basic purpose but lacks important contextual details. It doesn't explain return format, error handling, or operational constraints that would be needed for proper tool invocation, leaving gaps in completeness.
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?
The schema description coverage is 100% with one parameter clearly documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema (which already describes the sport filter with allowed values). This meets the baseline expectation when schema coverage is complete.
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 provides a 'Live sports odds snapshot' for specific sports (NFL, NBA, UFC, NHL) with types of odds (moneyline, spread, totals) and bookmaker comparisons. It uses specific verbs ('snapshot', 'comparisons') and identifies the resource (sports odds), but doesn't explicitly differentiate from sibling sports tools like botindex_sports_lines or botindex_sports_props.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions '$0.02' which might imply a cost, but doesn't clarify usage context, prerequisites, or when to choose this over other sports-related tools in the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'confidence scores' and 'market value signals', which hints at analytical outputs, but doesn't specify data freshness, update frequency, rate limits, authentication needs, or what 'movements' entails (e.g., timeframes, sources). For a tool with no annotations, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two main sentences, but the phrase '$0.02' adds informal clutter without clear value. The core information is front-loaded, but the informal tag slightly reduces efficiency. It could be more structured by explicitly stating the tool's output or context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and 0 parameters, the description is minimal. It covers the basic purpose but lacks details on output format (e.g., structure of confidence scores, what 'signals' include), data sources, or usage constraints. For a tool likely providing dynamic betting data, this is incomplete and leaves the agent guessing about behavioral aspects.
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 0 parameters, with 100% schema description coverage (since there are no parameters to describe). The description doesn't need to add parameter semantics, so a baseline score of 4 is appropriate, as it efficiently states the tool's purpose without unnecessary parameter details.
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's purpose: 'Top prop bet movements with confidence scores. Player prop market value signals.' It specifies the resource (sports prop bets) and the type of data provided (movements with confidence scores, market value signals). However, it doesn't explicitly differentiate from sibling tools like 'botindex_sports_lines' or 'botindex_sports_odds', which might offer related sports betting data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, context for usage, or comparisons with sibling tools like 'botindex_sports_lines' or 'botindex_sports_odds'. The phrase '$0.02' is informal and doesn't add functional guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions monitoring with labels but doesn't disclose critical traits like whether this is a read-only query, rate limits, authentication needs, data freshness, or what 'whale/exchange/bridge flow labels' entail operationally.
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 efficiently structured in a single sentence that front-loads key information (monitoring function, assets, chains, labels). The '$0.02' note is slightly cryptic but doesn't significantly detract from overall conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a monitoring tool with no annotations and no output schema, the description is incomplete. It lacks details on return format, pagination, error handling, and behavioral constraints, leaving significant gaps for an AI agent to understand how to effectively invoke and interpret results.
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 description coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds no additional meaning about parameters beyond implying monitoring scope, meeting the baseline for adequate but unenhanced parameter 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 monitors large stablecoin transfers (USDC/USDT) on Base and Ethereum with flow labels, which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'botindex_hl_whale_alerts' that might have overlapping functionality, preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions '$0.02' which might imply a cost, but doesn't clarify use cases, prerequisites, or exclusions compared to other botindex tools that handle whale alerts or crypto intel.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'attention metrics' and a cost '$0.03,' hinting at behavioral aspects like pricing or metric focus. However, it lacks critical details: whether it's read-only, if it requires authentication, rate limits, pagination, or what the output looks like. The description adds minimal value beyond the basic purpose.
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 concise and front-loaded, stating the core purpose in the first part. The second part adds cost information, which is relevant. However, the inclusion of '$0.03' might be slightly extraneous if not standard across tools, but it doesn't significantly detract from efficiency. Overall, it's well-structured with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a query tool with one parameter), no annotations, and no output schema, the description is incomplete. It lacks details on output format, error handling, authentication needs, or how 'attention metrics' are defined. The cost hint is insufficient to compensate for these gaps, making it inadequate for full agent understanding.
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 description coverage is 100% for the single parameter 'limit,' with a clear description in the schema. The tool description adds no parameter-specific information beyond what's in the schema. According to guidelines, with high schema coverage, the baseline is 3, as the description doesn't need to compensate but also doesn't enhance parameter understanding.
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's purpose: retrieving 'Creator performance scores on Zora' and specifies 'Top-performing creators by attention metrics.' It distinguishes from siblings like 'botindex_zora_attention_momentum' or 'botindex_zora_trending_coins' by focusing on scores rather than momentum or trending items. However, it doesn't explicitly mention the verb 'retrieve' or 'fetch,' slightly reducing specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'botindex_zora_attention_momentum' or 'botindex_zora_trending_coins,' nor does it specify use cases, prerequisites, or exclusions. The only contextual hint is the cost '$0.03,' but this doesn't inform tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions a cost ($0.03), which is useful, but lacks other critical details: it doesn't specify if this is a read-only operation, what the output format looks like (e.g., list of coins with metrics), any rate limits, or error conditions. For a tool with no annotations, this leaves significant behavioral gaps.
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 extremely concise—a single sentence that efficiently conveys the tool's core function and cost. It is front-loaded with the main purpose and includes no redundant information, making every word earn its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete for a tool that likely returns complex data (trending coins). It mentions cost but omits details on output format, error handling, or behavioral constraints. For a tool in a domain with many siblings (e.g., crypto/attention markets), more context is needed to guide effective 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?
The input schema has 100% description coverage, with the 'limit' parameter clearly documented in the schema. The description adds no additional parameter information beyond what's in the schema, so it meets the baseline of 3 for high schema coverage without compensating with extra details.
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's purpose: it returns trending Zora attention market coins based on volume velocity. It specifies the resource (Zora attention market coins) and metric (volume velocity), and includes a cost ($0.03). However, it doesn't explicitly differentiate from sibling tools like 'botindex_zora_attention_momentum' or 'botindex_zora_intel', which likely serve related but distinct purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, exclusions, or compare it to sibling tools such as 'botindex_zora_attention_momentum' or 'botindex_zora_intel', leaving the agent to infer usage context solely from the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool's purpose and cost, but lacks details on operational behavior—such as whether it performs real-time scans, how results are returned, rate limits, authentication needs, or error handling. This is insufficient for a tool that likely involves data retrieval and processing.
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 brief and front-loaded, stating the core function and cost in a single sentence. There's no wasted text or redundancy. However, it could be slightly more structured by separating functional details from cost information for clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., arbitrage opportunities, odds data), how results are formatted, or any behavioral nuances. For a tool with potential complexity in scanning multiple platforms, this leaves significant gaps in understanding its operation and outputs.
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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's function and cost. This aligns with the schema's completeness, warranting a baseline score of 4 for not adding unnecessary information.
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's function: scanning for arbitrage opportunities in prediction markets and sportsbooks. It specifies the domain (cross-platform) and includes a cost indication ($0.05), which adds practical context. However, it doesn't explicitly differentiate from sibling tools like 'botindex_sports_odds' or 'botindex_hl_funding_arb', which might offer overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description mentions the tool's function but doesn't indicate specific scenarios, prerequisites, or comparisons with sibling tools such as 'botindex_sports_odds' or 'botindex_hl_funding_arb'. This leaves the agent without clear direction on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'Live' data and 'FREE' access, which adds some behavioral context about real-time updates and cost. However, it lacks critical details like rate limits, authentication needs, data freshness, or output format, making it insufficient for a zero-parameter tool with no output schema.
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 concise and front-loaded, stating the core purpose in the first phrase. Every sentence ('Polymarket FOMC tracker.' and 'Live Fed/FOMC/interest rate markets with probabilities and liquidity. FREE.') adds value without waste. It could be slightly more structured but is efficient overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and no output schema, the description should fully explain what the tool returns and its behavioral traits. It mentions 'probabilities and liquidity' but doesn't specify the format, scope, or limitations of the data. With no annotations to fill gaps, this leaves the agent under-informed about how to interpret results.
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 with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's function. A baseline of 4 is applied since the schema fully covers the absence of parameters.
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's purpose: tracking FOMC markets with probabilities and liquidity. It specifies the resource (Polymarket FOMC tracker) and key data elements (probabilities, liquidity). However, it doesn't explicitly differentiate from sibling tools like 'botindex_polymarket_micro_markets' or 'botindex_polymarket_whale_trades', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions 'FREE' but doesn't explain if this is a distinguishing feature or prerequisite. There's no mention of context, exclusions, or comparisons to sibling tools, leaving the agent with minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. The description mentions filtering by status but doesn't explain what 'active' means, what status values exist, whether this is a read-only operation, potential rate limits, or authentication requirements. The '$0.02' notation is cryptic and provides no meaningful behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief (one sentence plus cryptic notation) but could be more front-loaded. The '$0.02' at the end adds confusion rather than clarity. While concise, the structure could be improved by placing the core functionality more prominently and eliminating the ambiguous notation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters (100% schema coverage) and no output schema, the description provides basic context about what data is retrieved. However, for a tool querying blockchain data with no annotations, it should ideally specify more about the return format, data freshness, or limitations. The cryptic '$0.02' notation reduces rather than enhances completeness.
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 0 parameters with 100% schema description coverage. The description appropriately doesn't discuss parameters since none exist. It does mention the filtering by status, which is the implicit behavior rather than a parameter. This meets expectations for a parameterless tool.
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's purpose: to retrieve currently active Metaplex Genesis launches on Solana filtered by status. It specifies the resource (Metaplex Genesis launches), platform (Solana), and filtering criterion (status). However, it doesn't explicitly differentiate from sibling tools like 'botindex_solana_launches' or 'botindex_doppler_launches' which might have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal usage guidance. It mentions the tool is filtered by status, but doesn't specify when to use this tool versus alternatives like 'botindex_solana_launches' or 'botindex_doppler_launches'. No explicit when/when-not instructions or alternative tool recommendations are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the output type (heatmap) and purpose (prediction), but fails to detail critical traits such as data sources, update frequency, accuracy limitations, or the '$0.05' cost implication. This leaves significant gaps in understanding the tool's behavior and constraints.
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 concise and front-loaded, stating the core function in the first phrase. The additional detail about prediction and cost is relevant, though the '$0.05' could be clarified. Overall, it's efficient with minimal waste, earning a high score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (predictive financial analysis), lack of annotations, and no output schema, the description is moderately complete. It covers the basic purpose and output type but misses details on data sources, format, reliability, and cost implications. This is adequate for a no-parameter tool but leaves room for improvement in behavioral 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?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately avoids discussing parameters, focusing instead on the tool's function. A baseline of 4 is assigned since the schema fully covers parameters, and the description doesn't need to compensate.
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's purpose: generating a 'liquidation cluster heatmap by price level' for predicting support/resistance zones. It specifies the resource (heatmap) and function (predicting zones), though it doesn't explicitly differentiate from sibling tools like 'botindex_hl_correlation_matrix' or 'botindex_hl_whale_alerts', which keeps it from a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives is provided. While the description implies usage for predicting support/resistance zones in financial contexts, it lacks specific scenarios, prerequisites, or comparisons to sibling tools like 'botindex_hl_coin_analytics', leaving the agent with minimal direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions a cost ('$0.02'), which is useful context, but doesn't describe other behavioral traits like rate limits, authentication needs, data freshness, or what happens when invoked (e.g., real-time vs. historical data). For a tool with zero annotation coverage, this leaves significant gaps.
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 a single, efficient sentence that front-loads the key information (what it does and cost). It avoids unnecessary words, though it could be slightly more structured (e.g., explicitly stating it's a retrieval tool). Every part of the sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters, no annotations, and no output schema, the description provides basic purpose and cost information. However, it lacks details on output format, data scope (e.g., time range, limits), and behavioral context, which are important for an agent to use it correctly. It's minimally adequate but has clear gaps.
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 0 parameters with 100% schema description coverage (empty schema). The description doesn't need to add parameter semantics since there are none, so it appropriately focuses on what the tool returns. Baseline is 4 for 0 parameters, as the description provides context about the output data.
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 retrieves 'Polymarket whale trades over $10K notional' with specific data fields (side, outcome, wallet proxy info), providing a specific verb (implicitly 'retrieve' or 'get') and resource. It distinguishes from most siblings by focusing on Polymarket whale trades, though it doesn't explicitly differentiate from other Polymarket-related tools like 'botindex_polymarket_fomc' or 'botindex_polymarket_micro_markets'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, context for use, or compare it to similar tools (e.g., other whale alert tools like 'botindex_hl_whale_alerts'). The agent must infer usage from the tool name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool shows 'co-performance patterns' and includes a cost ('$0.05'), but doesn't describe output format, data freshness, rate limits, authentication needs, or whether it's read-only/destructive. The cost hint is useful but insufficient for comprehensive 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 brief (one sentence plus cost) and front-loaded with the core purpose. Every phrase adds value: 'player correlation matrix' defines the output, 'DFS and correlated betting' specifies context, 'co-performance patterns' clarifies the analysis type, and '$0.05' indicates cost. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 0 parameters and no output schema, the description covers the basic purpose and cost adequately. However, for a tool with no annotations and potentially complex output (a correlation matrix), it lacks details on return format, data scope, or limitations. It's minimally viable but has clear gaps in behavioral 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?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, maintaining focus on the tool's purpose. A baseline of 4 is applied since no parameters exist.
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's purpose: generating a 'player correlation matrix' for 'DFS and correlated betting' that shows 'co-performance patterns'. It specifies the resource (player correlation matrix) and context (DFS/betting), though it doesn't explicitly differentiate from sibling tools like 'botindex_hl_correlation_matrix' or 'botindex_sports_lines'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description mentions 'DFS and correlated betting' as contexts, but doesn't specify prerequisites, exclusions, or compare it to related sibling tools (e.g., botindex_sports_lines, botindex_sports_odds).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It hints at output content ('line movements', 'sharp money action flags') but does not specify data format, update frequency, rate limits, or authentication needs. The phrase '$0.02' is ambiguous—possibly indicating cost or trivial value—but adds minimal practical context. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
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 concise and front-loaded, with two sentences that directly state the tool's purpose. The first sentence covers core functionality, and the second adds context. However, the phrase '$0.02' is cryptic and could be considered extraneous, slightly reducing efficiency. Overall, it avoids unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 0 parameters, no annotations, and no output schema, the description provides basic purpose but lacks completeness. It does not explain return values, data structure, or operational constraints (e.g., real-time vs. historical data). For a sports betting analytics tool, this leaves gaps in understanding how to interpret results, though the simplicity of no parameters mitigates some complexity.
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 input schema has 0 parameters with 100% coverage, meaning no parameters are documented in the schema. The description does not mention any parameters, which is appropriate since none are required. It adds no semantic details beyond the schema, but with zero parameters, the baseline is 4 as the description adequately aligns with the parameterless nature.
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's purpose: 'Line movements with sharp money action flags. Identifies professional bettor market impact.' It specifies the verb ('identifies') and resource ('line movements'), distinguishing it from siblings like 'botindex_sports_odds' or 'botindex_sports_props' by focusing on market impact analysis rather than raw odds or prop bets. However, it lacks explicit differentiation from 'botindex_sports_correlations', which might overlap in sports betting context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions 'sharp money action flags' and 'professional bettor market impact', but does not specify scenarios, prerequisites, or exclusions. Without explicit when/when-not instructions or named alternatives, users must infer usage from the purpose alone, which is insufficient for clear decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions a cost ('$0.05'), which is useful behavioral context about pricing. However, it lacks other critical details like whether this is a read-only operation, if it requires authentication, rate limits, or what format the intelligence comes in (e.g., report, API response).
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 concise and front-loaded, stating the core purpose and key outputs in one sentence, followed by pricing. Every element adds value without redundancy. It could be slightly more structured by explicitly separating features from cost.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and 0 parameters, the description provides basic purpose and cost. However, for a tool offering 'market intelligence', it lacks details on output format, data freshness, or scope (e.g., timeframes, asset types). This leaves gaps in understanding what the tool actually returns.
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 input schema has 0 parameters with 100% coverage, so no parameters need documentation. The description appropriately doesn't discuss parameters, which is efficient. Baseline is 4 for 0 parameters as it doesn't need to compensate for gaps.
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 provides 'AI-powered Zora market intelligence' with specific outputs like risk scores, fair value estimates, creator grades, and BUY/WATCH/FADE signals. It distinguishes itself from siblings like 'botindex_zora_creator_scores' by offering broader intelligence rather than just creator scores. However, it doesn't specify the exact verb (e.g., 'retrieve' or 'generate') for the action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools focused on Zora (e.g., 'botindex_zora_attention_momentum', 'botindex_zora_creator_scores'), there's no indication of how this tool's 'market intelligence' differs in context or when one should be preferred over another.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a 'get' operation (implying read-only) and describes what data is returned, but doesn't mention authentication requirements, rate limits, error conditions, or whether the data is real-time vs. cached. For a stats tool with zero annotation coverage, this leaves significant behavioral questions unanswered.
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 a single, efficient sentence that front-loads the core purpose ('Get aggregate stats') followed by specific metrics. Every word earns its place with no redundancy or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description provides adequate information about what the tool returns (aggregate stats with specific breakdowns). However, without annotations or output schema, it doesn't address important contextual elements like authentication requirements, data freshness, or error handling that would help an agent use it correctly.
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 0 parameters with 100% schema description coverage, so the schema fully documents the parameter situation. The description appropriately doesn't waste space discussing parameters that don't exist. A baseline of 4 is appropriate for zero-parameter tools where the schema handles the documentation.
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's purpose: 'Get aggregate stats for the Agorion discovery network' with specific metrics (total providers, services, capabilities breakdown). It distinguishes from most siblings by focusing on Agorion stats rather than botindex or other domains, though it doesn't explicitly differentiate from 'agorion_discover' or 'agorion_providers'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention when this tool is appropriate, what prerequisites might exist, or how it differs from sibling tools like 'agorion_discover' or 'agorion_providers' that might offer related functionality.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions fee structures and merchant counts, which hints at read-only data retrieval, but doesn't explicitly state this is a read-only operation, nor does it disclose any behavioral traits like rate limits, authentication needs, or data freshness. The description is minimal and lacks critical behavioral context.
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 a single, efficient sentence that packs essential information: what it is (directory), what it contains (protocols with examples), and additional details (fee structures, merchant counts). There is no wasted verbiage, and it's front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and no output schema, the description is moderately complete. It explains what the tool provides but lacks details on output format, data scope, or behavioral aspects. For a tool with no structured annotations or output schema, more context would be helpful, but it meets a basic threshold.
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 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description doesn't add parameter semantics, but this is acceptable given the lack of parameters. A baseline of 4 is appropriate as the schema fully covers the inputs.
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 provides a directory of agentic commerce protocols with specific examples (ACP, UCP, x402) and includes fee structures and merchant counts. It distinguishes from siblings by focusing on commerce protocols rather than other domains like crypto, sports, or analytics. However, it doesn't specify a precise action verb like 'list' or 'retrieve'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, context for usage, or compare it to sibling tools like botindex_commerce_compare. The agent must infer usage from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool is 'FREE' which hints at pricing, but doesn't describe authentication requirements, rate limits, response format, pagination, or what 'full' means in terms of completeness. For a catalog tool with zero annotation coverage, this leaves significant behavioral gaps.
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 extremely concise (one sentence) with zero wasted words. It's front-loaded with the core purpose and includes only essential additional context ('FREE'). Every element earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters (schema coverage 100%) and no output schema, the description adequately covers the basic purpose. However, for a catalog/discovery tool that presumably returns structured data about APIs, the description should ideally mention what format the catalog is returned in or how to interpret results. The 'FREE' mention adds some context but doesn't fully compensate for the lack of output information.
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 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and the schema already fully documents the empty parameter set.
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 action ('Get') and resource ('full BotIndex API catalog') with specific details about what it includes (endpoints, pricing, descriptions). It distinguishes itself from siblings by being a catalog/discovery tool rather than specific data retrieval functions, though it doesn't explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus the many sibling tools. While it implies this is for discovering available endpoints, it doesn't specify use cases, prerequisites, or exclusions. The 'FREE' mention hints at cost but doesn't provide meaningful usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions a cost ('$0.05'), which hints at a paid or rate-limited operation, but doesn't specify authentication needs, rate limits, data freshness, or output format. For a tool with potential financial implications, this lack of detail is a significant gap.
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 extremely concise—two short phrases that convey the core purpose and cost. Every word earns its place, with no redundancy or fluff, making it easy to scan and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (financial correlation matrix) and lack of annotations or output schema, the description is minimally adequate. It states the purpose and cost but omits critical details like data sources, update frequency, return format, and error handling. For a tool in a suite with many siblings, more context would help differentiate and ensure correct usage.
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 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate, but it could have explained any implicit inputs (e.g., time range or asset selection). Since there are no parameters, a baseline of 4 is justified, as the description doesn't need to compensate for gaps.
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's purpose: providing a correlation matrix for Hyperliquid perpetuals, specifically for portfolio construction. It distinguishes itself from siblings by focusing on correlation analysis rather than other crypto analytics (e.g., funding arbitrage, whale alerts, token launches). However, it doesn't specify the exact verb (e.g., 'generate' or 'retrieve'), keeping it slightly less specific than a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives is provided. The description mentions portfolio construction as a use case, but it doesn't clarify prerequisites, timing, or how it differs from other correlation tools like 'botindex_sports_correlations'. Without such context, users must infer usage from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the timeframe and format but does not explain key behavioral traits such as whether this is a read-only operation, if it requires authentication, rate limits, error handling, or what the output looks like (e.g., list structure, data fields). For a tool with zero annotation coverage, this lack of detail is a significant gap.
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 a single, efficient sentence that conveys the essential information without any waste. It is front-loaded with the core purpose and includes necessary details (timeframe, format, price) in a compact form. Every part of the sentence earns its place, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (0 parameters, no output schema, no annotations), the description is adequate but incomplete. It specifies what data is retrieved but lacks details on behavioral aspects (e.g., safety, output format) that would help the agent use it correctly. Without annotations or an output schema, the description should compensate more fully, but it only partially does so, leaving gaps in understanding the tool's operation.
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 0 parameters, and the schema description coverage is 100% (as there are no parameters to describe). The description does not need to add parameter semantics, so it meets the baseline expectation. No additional information is required, and the description does not contradict the schema.
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 what the tool does: it retrieves Polymarket micro-markets ending in the next 2 hours in 'Up or Down format' with a price point of '$0.01'. It specifies the resource (Polymarket micro-markets), timeframe (next 2 hours), format (Up or Down), and price, making the purpose specific and actionable. However, it does not explicitly distinguish itself from sibling tools like 'botindex_polymarket_fomc' or 'botindex_polymarket_whale_trades', which limits the score to 4.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, exclusions, or specific contexts for usage, nor does it refer to sibling tools for comparison. Without such information, the agent must infer usage based on the purpose alone, which is insufficient for optimal tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool returns endpoints from specific providers, which gives some context about output, but lacks details on rate limits, authentication requirements, error handling, or whether it's a read-only operation. For a search tool with no annotation coverage, this leaves significant gaps in understanding its behavior.
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 efficiently structured in two sentences: the first states the core function, and the second specifies the providers and search criteria. Every sentence adds essential information without redundancy, making it front-loaded and zero-waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the purpose and providers well, but lacks details on output format (e.g., structure of returned endpoints), error cases, or performance considerations. Without annotations or output schema, more behavioral context would be needed for full completeness.
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 description coverage is 100%, so the schema already documents all four parameters thoroughly. The description adds marginal value by listing example capabilities and mentioning the 6+ providers, but doesn't provide additional syntax, format details, or constraints beyond what the schema provides. The baseline of 3 is appropriate when the schema does the heavy lifting.
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 states the tool's purpose with a specific verb ('Search') and resource ('Agorion agent service discovery network'), and distinguishes it from siblings by specifying it finds APIs from 6+ named providers. It explicitly differentiates from tools like 'agorion_providers' or 'botindex_discover' by focusing on multi-provider API discovery rather than single-source operations.
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 usage context by listing search criteria (capability, price, network) and the types of providers it covers, but it doesn't explicitly state when to use this tool versus alternatives like 'agorion_providers' (which might list providers) or 'botindex_discover' (which appears to be a BotIndex-specific discovery tool). No explicit exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool lists providers with service counts, but does not disclose important behavioral traits such as whether the data is real-time or cached, any rate limits, authentication requirements, or pagination behavior for potentially large result sets.
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 a single, efficient sentence that directly states the tool's purpose without any redundant or vague language. It is front-loaded with the core action and resource, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there are no parameters, no annotations, and no output schema, the description adequately explains what the tool does. However, it lacks details on behavioral aspects like data freshness or format, which would be helpful for an agent to use it effectively in a broader 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?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately does not discuss parameters, and the baseline score for 0 parameters is 4, as it avoids unnecessary information.
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 states the specific action ('List all providers') and resource ('registered in the Agorion discovery network'), with additional detail about what information is included ('with their service counts'). It distinguishes itself from sibling tools like 'agorion_discover' by focusing on listing providers rather than general discovery.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, context for usage, or comparisons with sibling tools like 'agorion_discover' or 'agorion_stats', leaving the agent to infer usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions cost ('$0.02'), which is useful behavioral context, but lacks details on rate limits, authentication needs, output format, or error handling. For a scanner tool with no annotations, this leaves significant gaps in behavioral understanding.
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 front-loaded with core functionality in the first sentence and includes cost in the second, with zero wasted words. It efficiently conveys essential information without redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description provides basic purpose and cost but lacks details on behavioral traits (e.g., rate limits), output structure, or error handling. For a scanner tool with 3 parameters, this is minimally adequate but has clear gaps in completeness.
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 description coverage is 100%, so the schema already documents all parameters (chain, min_score, limit). The description does not add any parameter-specific semantics beyond what the schema provides, such as explaining 'velocity score' or default behaviors. Baseline 3 is appropriate when schema does the heavy lifting.
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 states the tool's purpose with specific verbs ('scanner', 'detects') and resources ('meme token velocity', 'sudden volume/price spikes'), and distinguishes it from siblings by specifying cross-platform coverage (DexScreener, Zora, Pump.fun). It avoids tautology by not just repeating the name.
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 usage for detecting sudden spikes in meme tokens across specific platforms, but does not explicitly state when to use this tool versus alternatives (e.g., other botindex tools for crypto intel or launches). No exclusions or prerequisites are mentioned, leaving usage context somewhat vague.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: it's a summary tool (implying read-only, non-destructive), tracks specific data ('$187M+ in whale positions'), and has usage limits ('FREE (3/day)'). However, it lacks details on response format, error handling, or authentication needs, leaving gaps for an agent.
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 highly concise and front-loaded, with every sentence adding value: the first defines the purpose, the second adds context ('Tracks $187M+'), and the third specifies constraints ('FREE (3/day)'). There's zero waste or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0 parameters, and no output schema, the description is moderately complete. It covers purpose, scope, and constraints, but lacks details on output format, error cases, or deeper behavioral context. For a simple summary tool, this is adequate but has clear gaps, especially without structured data to rely on.
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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter info, which is appropriate. A baseline of 4 is applied since it compensates by not misleading about parameters, though it doesn't explicitly state 'no parameters required'.
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's purpose: 'Hyperliquid whale alert summary — top whale positions and recent large trade count.' It specifies the verb ('summary') and resource ('whale positions and recent large trade count'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from its sibling 'botindex_hl_whale_alerts_full', though the mention of 'summary' vs. 'full' implies a distinction.
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 usage context by mentioning 'FREE (3/day)', which suggests rate limits and when to use it cautiously. It also hints at an alternative with 'summary' vs. the sibling 'full' version, but doesn't explicitly state when to choose one over the other. No explicit exclusions or prerequisites are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions pricing ($0.05), which hints at a cost or rate limit, but does not disclose other behavioral traits such as data freshness, update frequency, authentication needs, or potential destructive actions. The description adds minimal context beyond the basic purpose, lacking details on how the tool behaves in operation.
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 a single, dense sentence that efficiently conveys the tool's purpose, data elements, and pricing without any wasted words. It is front-loaded with the core functionality ('Full Hyperliquid whale positions + recent large trades') and adds essential details concisely, making every part of the sentence earn its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (providing detailed financial data) and lack of annotations and output schema, the description is moderately complete. It covers what data is returned but does not explain the return format, structure, or any limitations. For a data-rich tool with no structured output information, the description should do more to clarify what users can expect beyond the listed data points.
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 0 parameters with 100% schema description coverage, so no parameter information is needed. The description does not add parameter semantics, but this is acceptable as there are no parameters to document. A baseline score of 4 is appropriate since the schema fully covers the absence of parameters, and the description does not need to compensate.
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 states the specific verb ('Full Hyperliquid whale positions + recent large trades') and resource ('whale positions + recent large trades'), distinguishing it from siblings like 'botindex_hl_whale_alerts' which likely provides alerts rather than full data. It includes detailed data elements (entry prices, leverage, PnL, liquidation levels) and pricing information ($0.05), making the purpose highly specific and differentiated.
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 usage for accessing comprehensive whale data on Hyperliquid, but it does not explicitly state when to use this tool versus alternatives like 'botindex_hl_whale_alerts' or other crypto-related tools. The context is clear (whale positions and large trades), but no exclusions or specific alternatives are mentioned, leaving usage somewhat implied rather than explicitly guided.
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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