lso-mcp
Server Quality Checklist
Latest release: v1.1.1
- Disambiguation5/5
Each tool targets a distinct domain or function with clear, detailed descriptions. Even with overlapping themes like risk assessment, tools are differentiated by specific focus (pool, wallet, DeFi protocol, portfolio). Confusion is minimal.
Naming Consistency4/5Names are consistently lowercase with underscores, and most follow a descriptive noun_verb or verb_noun pattern. Minor inconsistencies exist (e.g., 'agricultural_commodities' vs. 'insider_trading') but overall pattern is clear.
Tool Count2/545 tools is excessive for a single MCP server, spanning crypto, finance, weather, content creation, and more. The sheer volume overwhelms the agent's selection surface, making it harder to find the right tool quickly.
Completeness3/5The server covers many domains but only scratches the surface of each. For example, financial data lacks fundamentals or corporate actions; crypto misses DeFi lending rates. Useful as a broad aggregator, but not comprehensive for any single domain.
Average 4/5 across 45 of 45 tools scored. Lowest: 2.6/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 17 commits in the last 12 weeks
- No stable releases found
- 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.
Add a glama.json file to provide metadata about your server.
This server has been verified by its author.
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
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits but only mentions data source and content. Does not explain read-only nature, pagination, default behavior, or limitations. For example, the output schema exists but behavior around filtering by status or area is unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, concise and front-loaded with the key purpose. Could be slightly more structured but no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and optional parameters, the description lacks sufficient detail for an agent to understand filtering, return format, or how to interpret results (e.g., block status). Missing parameter guidance reduces completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no explanation of the three parameters (status, area, limit). Their defaults and possible values are left entirely to the schema, which lacks enum constraints or descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool provides Gulf of Mexico oil & gas lease intelligence from BOEM, mentioning 218k+ leases, block status, and upcoming BBG2 auction. It distinguishes from siblings as the only lease-specific tool among many, though it lacks an explicit verb like 'retrieve' or 'search'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Does not mention prerequisites, typical use cases, or contrast with sibling tools like 'energy_markets' or 'grid_intelligence'.
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?
The description only lists data categories and does not disclose behavioral traits such as read-only nature, update frequency, or any limitations. Since annotations are absent, the description carries the full burden but provides minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (one sentence) and front-loaded with the key concept 'US energy market intelligence'. However, the list format is somewhat run-on and could be improved with better structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main data areas but lacks context on output format, update frequency, or geographic scope beyond 'US'. An output schema exists, so return values are partly covered, but more completion would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, so the baseline is 4. The description adds value by enumerating the types of data returned, which goes beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description lists specific energy market data points (WTI, Brent, Henry Hub, etc.), making the tool's purpose clear. However, it lacks an explicit action verb and does not distinguish itself from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does 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 does not mention any context, exclusions, or prerequisites.
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, and the description does not disclose behavioral traits such as authentication requirements, rate limits, or side effects. The tool is read-only implied but not stated, and there is no mention of what happens on empty results or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no wasted words. It front-loads the main purpose and output. However, it could be slightly more structured (e.g., listing parameters explicitly).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has three optional parameters and an output schema, the description covers core functionality and outputs but lacks detail on parameters and behavioral edge cases. It is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description hints at the min_amount parameter via 'Federal contract awards $10M+' but does not explain days_back or agency. The default values are mentioned in the schema but not in the description, leaving the agent without full understanding of parameter effects.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves federal contract awards over $10M from USASpending.gov and cross-references vendors with stock tickers. It also specifies outputs: agency breakdown, award amounts, AI narrative. This distinguishes it from siblings like contract_check and gov_edge_opportunities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. It does not advise against certain uses or provide context for selection among siblings, leaving the agent without decision criteria.
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?
With no annotations, the description carries the full burden. It discloses caching behavior (5 min refresh) and implies read-only access, but does not explicitly state nondestructiveness, rate limits, or required permissions. The mention of caching helps but lacks completeness for full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences, the first front-loading core functionality and outputs, the second adding important caching info. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple input (single symbol) and presence of an output schema (which details return fields), the description covers the tool's purpose, outputs, and cache duration adequately. It omits symbol format or error cases, but for a low-complexity tool this is minor.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, meaning the description must explain parameters. However, it does not mention the 'symbol' parameter at all—no format, sources, or examples. The description implies it is for a financial symbol but fails to add meaningful semantic value beyond the schema's basic string type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs multi-timeframe technical analysis (15m/1h/4h/1d) and lists specific outputs (overall_signal, confluence_score, etc.). It is distinct from generic tools like tech_analysis but does not explicitly contrast with siblings, so it falls short of a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 compared to alternatives like tech_analysis or equity_analysis. There is no mention of prerequisites, ideal scenarios, or situations where other tools might be preferred.
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 provided, and the description does not explicitly state that the tool is read-only or disclose any side effects. The term 'analysis' implies a safe query, but behavioral expectations are vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose. Every word earns its place with no unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool is simple with one parameter and an output schema exists (though not shown), the description is minimally complete. However, it could mention what the output contains (e.g., risk metrics) to improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has a single parameter 'tickers' with no description (0% coverage). The description adds crucial meaning by specifying the format (comma-separated string) and providing an example, which is valuable beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool performs portfolio risk analysis covering concentration, volatility, and correlation. This distinguishes it from sibling tools like equity_analysis or tech_analysis that focus on different aspects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description provides format guidance ('comma-separated string') but no information on when to use this tool versus alternatives like equity_analysis or defi_risk for individual stock analysis.
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?
With no annotations provided, the description carries full burden. It discloses caching (5 min) and available timeframes, which are useful behavioral traits. However, it omits whether the tool is read-only, any authentication requirements, or rate limits. The 'Cached 5 min' adds value beyond the schema, but more context is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using only two short sentences with no filler. Key information (indicators, AI signal, timeframes, caching) is front-loaded. Every word contributes value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema, so return values are covered elsewhere. However, given the low parameter documentation (0% schema coverage) and moderate complexity (2 params, no nested objects), the description should provide more context on symbol and timeframe semantics. The timeframes are listed but not formally associated with the parameter. Overall adequate but incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It mentions timeframes in the free text (15m, 1h, 4h, 1d) but does not explicitly link to the 'timeframe' parameter. The 'symbol' parameter lacks any description of acceptable formats or asset types (e.g., tickers, crypto pairs). This leaves the agent guessing on parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides '18 technical indicators + AI signal for any ticker', specifying the resource (ticker) and verb (provides analysis). It lists available timeframes, making the purpose specific and actionable. While sibling tools exist, this tool's focus on technical indicators with AI signal distinguishes it adequately.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for technical analysis but provides no explicit guidance on when to use this tool versus siblings like equity_analysis or multi_timeframe_scan. No prerequisites, exclusions, or alternative tools are mentioned, leaving the agent without clear selection criteria.
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 exist, so the description must cover behavioral traits. It does not state whether the tool is read-only, requires authentication, has rate limits, or any side effects. It only lists what it checks, not how it behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with a clear front-loaded purpose and a bullet-like list of checks. Every word contributes value; no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values are covered. The description adequately lists the checks and supported chains. Missing prerequisites or error handling, but for a due diligence tool the core functionality is well described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds allowed values for the 'chain' parameter (eth, base, bsc, arb, poly) but provides no additional details for 'contract_address' (e.g., format, examples). Partial improvement over bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('due diligence') and resource ('ERC-20 token') and lists concrete checks (risk score, honeypot, liquidity, holder concentration, ownership status). It clearly defines the tool's scope and supported chains, distinguishing it from vague or tautological descriptions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'contract_check' or 'defi_risk'. No explicit when-not-to-use or prerequisites are mentioned, leaving the agent to infer usage context.
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 provided, so description must cover behavioral traits. Mentions caching (30 min) and AI analysis, but omits authentication needs, rate limits, or potential delays.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. First sentence lists outputs, second adds scope and caching. Efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers key outputs and caching behavior. With an output schema likely detailing return shape, description is sufficient. Missing rate limits but acceptable for a simple query tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has one parameter (ticker) with 0% coverage. Description adds meaning by specifying 'US stocks and ETFs', guiding the agent on valid ticker values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly describes outputs (buy/hold/sell, upside %, P/E, etc.) and scope (US stocks and ETFs). However, uses noun phrase 'Equity intelligence' instead of a specific verb like 'provides'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like tech_analysis or news_sentiment. Only implicitly through scope (US stocks/ETFs). Lacks exclusion criteria or prerequisites.
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 urgency flags (≤14 days) but omits other behaviors such as auth requirements, rate limits, pagination, or cost implications. The AI BD briefing mention is a feature, not a behavioral trait.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences with no wasted words. It front-loads the core action, then lists returns and filters efficiently. Every sentence adds distinct value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given an output schema exists (though not provided), the description adequately summarizes returns. However, it fails to mention the 'days_back' parameter or any prerequisites (e.g., API access). The gap in parameter coverage reduces completeness for a 4-parameter tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain parameters. It covers 'keyword', 'naics', and 'set_aside' (including example values), but omits the 'days_back' parameter entirely. This partial coverage leaves a meaningful gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches active federal contract opportunities from SAM.gov and lists specific returned fields (deadlines, urgency flags, agency, NAICS code, set-aside type, AI BD briefing), making its purpose highly specific and distinguishable from sibling tools like 'gov_edge' or 'contract_check'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lists filters (keyword, naics, set_aside) and hints at use cases for searching opportunities, but does not explicitly state when to use this tool over alternatives or provide exclusions (e.g., when not to use it). The usage context is implied rather than explicit.
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 must carry the full burden of behavioral transparency. It discloses latency differences and return types, but does not mention authentication requirements, rate limits, or whether the tool is read-only or has side effects. It omits important behavioral traits beyond basic functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of just two sentences. It front-loads the main purpose and includes key details (supported assets, outputs, latency) without any fluff. Every sentence serves a clear informative purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool is simple (one parameter) and an output schema exists, the description is mostly complete. It covers what the tool does, what it returns, and performance nuances. However, it could add brief context on how the conviction trade or unusual activity is determined to slightly improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, and the description does not elaborate on the single 'ticker' parameter beyond implying it accepts stock tickers or crypto symbols. No format, examples, or constraints are given, leaving the agent with minimal semantic guidance beyond the parameter name and overall tool purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides options flow analysis for both stocks and specific cryptocurrencies (BTC/ETH/SOL/AVAX via Deribit). It lists the return outputs: signal, conviction trade, put/call ratio, and unusual activity. This distinguishes it from sibling tools like 'equity_analysis' or 'token_launches' by focusing on options-specific flow data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives context on when to use this tool (for options flow) and differentiates update speeds (crypto under 1s, stocks cached 5 min), but does not explicitly state when not to use it or mention alternatives among siblings. There is no comparison to other tools, leaving the agent to infer usage without clear 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?
No annotations are provided, and the description does not disclose behavioral traits such as data freshness, update frequency, or any side effects. For a read-only data tool, the description only lists content, not behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with a clear list of data points. It is concise but slightly dense; could be broken into two sentences for readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and an output schema (not shown), the description covers the data content. However, it lacks context on update frequency, data source, or intended use cases, which would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, and schema coverage is 100%. The description adds value by specifying the exact data items returned (e.g., mortgage rates, HPI), which is sufficient for a parameterless tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool provides US real estate market data and enumerates specific metrics (mortgage rates, housing starts, etc.). It is distinct from sibling tools focusing on other economic sectors.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for real estate market data but does not explicitly state when to choose this over siblings like 'macro_indicators' or 'geo_pulse'. No exclusions or context for alternatives are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
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 details the output fields (realized/unrealized gains, portfolio value, win rate, holdings, verdict), but does not mention that the tool is read-only, rate limits, or any prerequisites. Still, it adds significant context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the tool's purpose and outputs without any wasted words. It is front-loaded and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description does not need to fully detail return values, but it lists them helpfully. However, it omits critical context: the wallet must be on Base, the data source, error conditions, and no guidance on parameters or usage boundaries.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, yet the description does not explain the parameters 'wallet' (likely an address) or 'days' (lookback period). The parameters are only defined by type in the schema, and the description adds no meaning, which is a critical gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as an on-chain wallet PnL analyzer for Base, a specific verb+resource combination. It distinguishes from siblings like wallet_risk by focusing on profit/loss analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for PnL analysis but does not explicitly state when to use or when not to use, nor does it mention alternatives. With a similar sibling tool wallet_risk, more explicit guidance would improve clarity.
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 lists return fields (risk_score, sanctions_hit, etc.) and implies read-only behavior, but lacks details on data freshness, rate limits, or behavior for non-eth chains. It adds value but leaves gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences: first states output, second lists fields, third gives usage. No wasted words, efficient structure, front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values are partially covered. However, the description lacks explanation for the chain parameter and ambiguity about 'any Ethereum address' vs. chain default. Given the moderate complexity, it is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description does not explain the address parameter format or validation, nor does it mention the chain parameter (default eth) or its values. The description adds no meaning beyond the schema, failing to compensate for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns a wallet risk score for an Ethereum address, lists specific outputs, and provides a concrete use case. It distinguishes from siblings like defi_risk (which likely focuses on DeFi protocol risks) by being wallet-specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use: 'Use before transacting with an unknown counterparty or screening a wallet for compliance.' It does not provide explicit when-not-to-use or alternatives, but the usage context is clear and actionable.
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 must fully disclose behavioral traits. It lists what the tool assesses but fails to mention critical behaviors such as whether it is read-only, if there are rate limits, authentication requirements, or what the response format looks like. The output schema exists but its content is not described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the main purpose. Every sentence adds value: the first defines the tool's function, the second explains parameter usage. No superfluous text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only one optional parameter and an output schema (which reduces the need to explain return values), the description provides a reasonable overview. However, the lack of annotations and behavioral details (e.g., whether the data is real-time, caching, or scope) limits completeness for an AI agent deciding to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, so the description compensates by explaining that 'protocol' takes a protocol name for specific assessment or leaves empty for an overview. This adds meaningful context beyond the schema definition, which only shows a string with a default.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it performs 'DeFi protocol risk assessment' and lists specific risk factors (TVL, audit status, exploit history, smart contract risk). It also distinguishes behavior based on whether a protocol name is provided or not, making its purpose and scope explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides usage instructions ('Pass protocol name or leave empty for top protocols overview') but does not offer guidance on when to use this tool over siblings like contract_check or token_due_diligence. No exclusions or explicit when-to-use/when-not-to-use advice.
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 must convey all behavioral traits. It discloses the cost ($0.15 via x402) and the four output formats. However, it does not mention rate limits, error handling for invalid URLs, or any potential limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the action and outcome. It is highly concise with no wasted words. A small improvement could be adding a brief note about the cost or structure in a second sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only one parameter and an output schema exists, the description covers the key context: input (URL), purpose, and cost. It does not need to explain return values. It is fairly complete for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema description coverage at 0%, the description should clarify the parameter. It names the parameter implicitly ('any URL') but does not specify the expected format (e.g., must include protocol), validation rules, or provide examples. This adds minimal meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('repurpose') and resource ('any URL') and lists the four distinct output formats. This distinguishes it from the diverse set of sibling tools, which are unrelated topics like crypto, weather, and finance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use it ('turning research reports, blog posts, or news articles into ready-to-publish social content'), which is clear context. It does not list alternatives, but given the sibling tools are unrelated, the guidance is sufficient.
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 discloses it's a GET request with a cost ($0.05 via x402) and states it returns real-time prices with momentum signals and category analysis. However, it does not disclose rate limits, authentication needs, or any side effects beyond the cost.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences. The first sentence states the core function and features. The second lists specific metals and pricing details. Every sentence adds new information with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and presence of an output schema (not shown but indicated), the description covers the essential: what metals, features (momentum signals, category analysis), and cost. It does not describe the output schema format, but that is handled by the schema itself. The tool is simple with no inputs, so the description is mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, and schema coverage is 100%. With no parameters, the description does not need to explain parameter semantics. The description adds value by explaining the output content (prices, signals, categories).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides real-time prices for 13 specific industrial metals, along with momentum signals and category analysis. It lists all metals covered and mentions the API endpoint and cost. This verb+resource description distinguishes it from sibling tools like agricultural_commodities or energy_markets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly suggests using this tool when needing prices for these metals but does not provide explicit guidance on when to use it versus alternatives like energy_markets or agricultural_commodities. No exclusion criteria or alternative tools are mentioned.
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 bears full responsibility. It explains the tool scans the first 3 blocks and returns risk score, bundle wallets, and dump status. However, it does not disclose potential costs, API key requirements, or error handling for invalid addresses, leaving some 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences: first states purpose, second details scanning logic and outputs, third gives usage advice. No redundant information, and each sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no nested objects, output schema present), the description adequately covers what the tool does and when to use it. It does not detail the output schema (which is separate) but is otherwise complete for a data-checking tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter ('address') with 0% description coverage. The description only implies it is a token address on Base but does not specify format, required network, or any constraints. Since schema coverage is low, the description should compensate but falls short.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool detects token launch bundles and snipers on Base, scanning the first 3 blocks for coordinated buys. It specifies the resource (token launches), verb (scans), and outputs (risk score, bundle wallets, dump status). This clearly distinguishes it from sibling tools like token_launches or contract_check.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use before buying any new token to check if the launch was bundled,' providing clear when-to-use guidance. It does not mention when not to use or alternatives, but the context is sufficient for typical use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
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 that the tool returns earnings dates, estimates, history, and details like EPS, surprise percentage, and price reaction. It also specifies the days_soon parameter's default and maximum. This is good transparency for a read-only tool, though it could explicitly state that it is read-only and does not modify data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, consisting of two sentences. The first sentence states the tool's purpose and output details, while the second provides parameter guidance. Every sentence adds value, and there is no unnecessary information. It is front-loaded with the most critical information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 2 optional parameters, a simple output schema, and no annotations, the description covers the input parameters well and gives a solid overview of the output. However, it doesn't explicitly mention that the output is from the last 4 quarters, which is important context. Also, it lacks a note about the tool being read-only. Nonetheless, for a tool of this complexity, it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, but the description adds meaningful semantics: 'tickers' should be a comma-separated string, and 'days_soon' has a default of 7 and max of 90. This clarifies the parameter format and constraints beyond the schema's type and default. However, it doesn't explain what 'days_soon' controls beyond 'near-term window' – is it looking ahead or behind? The context implies forward-looking earnings calendar, but it's not explicit.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides earnings dates, estimates, and beat/miss history for the last 4 quarters. It specifies EPS actual/estimate, surprise percentage, day-after price reaction, and consecutive beats. This is a specific verb+resource description, though it doesn't use the verb 'retrieve' or 'get', which would be slightly clearer. It effectively distinguishes from sibling tools like equity_analysis or insider_trading by focusing on earnings calendar data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains how to pass tickers (comma-separated string) and the days_soon parameter (near-term window, default 7, max 90). However, it does not provide guidance on when to use this tool versus alternatives, nor does it mention when not to use it. For example, if the user needs broader financial data, equity_analysis might be more appropriate. No explicit exclusions or alternatives are given.
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 exist, so description carries full burden. It discloses that the tool converts PDFs, returns multiple data fields (markdown, counts, summary), but omits behaviors like error handling, rate limits, or file size constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with action and output, followed by use cases. No redundant words, highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, return values are covered. The description lists return components. For a two-parameter tool, it's mostly complete, but could explicitly tie the summarize parameter to the summary output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% for parameters, so description must add meaning. It mentions 'via URL' but doesn't specify URL requirements. The boolean 'summarize' is implied by the output mention of 'AI summary', but not explicitly linked. Adds partial context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Convert any PDF document via URL to clean Markdown'), lists output components, and specifies use cases (whitepapers, reports, etc.), distinguishing it from unrelated siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides explicit use case examples ('whitepapers, reports, contracts, or research papers'), giving context for when to use. However, no direct exclusions or alternatives are mentioned, though none are needed given sibling diversity.
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 provided, so description must cover behavioral aspects. It mentions outputs (risk score, liquidity, deployer history, launch metadata) but does not disclose details like update frequency, real-time vs. cached, or limitations. This leaves 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words, front-loaded with purpose. Highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With zero parameters and an output schema, the description covers the key outputs sufficiently. Could elaborate on 'launch metadata' but not necessary. Complete enough to understand tool's capabilities.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters (schema coverage 100%). Description does not need to explain params, but it clarifies the tool's function and outputs, adding value beyond the schema. Baseline 4 for zero-param tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('scan'), resource ('newly launched tokens'), and purpose ('filters for legitimate vs. honeypots'). It clearly distinguishes from siblings like token_due_diligence or contract_check which have different scopes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for identifying legitimate new token launches but does not explicitly state when to use vs. alternatives or when not to use. No comparison with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It transparently lists what the tool checks (honeypots, rug pulls, etc.) and what it returns (scores, flags, verdict). It implies it is a read-only safe operation. However, it does not disclose potential error conditions (e.g., invalid pool address) or API dependencies, which would be helpful.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences: purpose, detailed checks, and use case. It is front-loaded, every sentence adds value, and there is no redundancy. Perfectly sized for a single-parameter tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (context indicates true), the description appropriately summarizes return values (risk scores, flags, verdict) without needing detail. It covers the essential checks and use case. However, it could mention that the input is a contract address format and that the tool runs on Base network.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The sole parameter 'pool_address' is not elaborated in the description; it only implies it is a pool address via the tool's purpose. With 0% schema description coverage, the description should provide format hints (e.g., Ethereum address format, checksum requirement). The description adds no semantic value beyond what 'pool_address' already conveys.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs risk assessment on Aerodrome DEX pools on Base, specifying exact checks (honeypots, rug pulls, hidden ownership, tax manipulation) and outputs (per-token risk scores, flags, AI verdict). It differentiates from sibling tools like 'contract_check' or 'token_due_diligence' by targeting a specific DEX and pool context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises 'Use before providing liquidity', which is a strong usage guideline. However, it does not mention when not to use the tool or provide alternative tools for different contexts (e.g., single token checks). Still, the primary use case is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It describes the return data and detection capabilities. Does not mention potential errors, rate limits, or side effects, but is reasonably transparent about what the tool does.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states purpose and return fields, second gives usage context. No wasted words, front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has an output schema, so description needn't detail return values fully, but it lists several key fields. Lacks details on supported chains for the 'chain' parameter. Overall covers main aspects adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 2 parameters with 0% description coverage. The description only implicitly addresses 'address' by mentioning 'any EVM address' but does not explain 'chain' parameter (default 'eth') or valid values. Adds little meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it verifies smart contracts for any EVM address, listing specific return fields (verified, is_proxy, proxy_type, owner, deployment age). Distinguishes itself from sibling audit tools by focusing on proxy detection and verification status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use before interacting with an unknown contract to detect hidden admin keys, upgradeable proxies, or unverified bytecode.' Provides clear context for when to use, though does not explicitly mention alternatives or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses the process (analyze, write, test, open PR), return value (pr_url), cost ($0.50 via x402), and extra capabilities (web research, complex tasks). This is strong transparency, though it could mention time estimates or failure modes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is 4 sentences with a clear front-loaded purpose. It efficiently covers purpose, usage, outcome, and cost. Slightly less concise due to extra examples of use cases, but still well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description adequately covers return value (pr_url). It explains inputs (task, repo), process, and cost. Missing details like error handling or expected duration, but overall complete for a coding agent tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 3 parameters with 0% coverage, so description adds value. It explains 'task' and 'repo' (optional), but does not describe the 'context' parameter. This leaves a gap in understanding all inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Hire' and the resource 'Floyd, LoneStarOracle's autonomous coding agent' and details the actions: analyzes repo, writes code, runs tests, opens PR. This distinguishes it from sibling tools which are primarily data/analytics tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description specifies it is 'Best for well-scoped coding tasks: bug fixes, feature additions, test coverage, refactors' and mentions additional abilities like hunting bounties and web research. It gives clear context but does not explicitly state when not to use it or list alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the key behavior (providing prices and 6-month trends for a fixed set of commodities). With no annotations provided, this covers the essential behavior. It could be more precise about data freshness (e.g., 'current prices') but is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single, clear sentence of 14 words with no fluff. It front-loads the tool's purpose and lists specifics efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and an output schema exists (documenting return values), the description is complete enough for a simple data retrieval tool. It names all relevant commodities and the key metric (trend). Could explicitly mention 'current prices' but suffices.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so the description does not need to add parameter info. Schema coverage is 100% trivially. Baseline for 0 params is 4, and the description adds no misleading or redundant info.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly lists specific commodities (corn, wheat, etc.) and states it provides prices with a 6-month trend. This distinguishes it from sibling tools like energy_markets or industrial_metals. The verb 'provides' is implied and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use or not. However, for a zero-parameter data retrieval tool, the usage context is self-evident: call it when you need agricultural commodity prices. Lacks exclusions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description covers behavioral traits: it returns annualized rates, breakdown, alert, and bias. It implies read-only data retrieval without destructive effects, though not explicitly stated. Could mention non-destructive nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise, front-loaded sentences with no redundancy. Key information (exchanges, assets, signals, output) presented efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown), the description adequately covers return values (annualized rates, breakdown, alert, bias). Could mention any rate limits or pagination, but overall complete for a simple retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one string parameter with no description (0% coverage). The description adds value by clarifying that the asset parameter filters to a single coin, compensating for schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves perpetual futures funding rates across specific exchanges (Binance, Bybit, OKX) and assets (BTC/ETH/SOL/AVAX/LINK/ARB), with distinct signal categories. This differentiates it from siblings like open_interest or liquidations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does 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 (e.g., open_interest, liquidations). The description mentions signal-first approach and optional asset filtering, but lacks context for selection among many market data tools.
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 full burden. It discloses that the tool returns risk_score, conflict signals, and commodity impact, but lacks details on update frequency, authentication, or side effects. It is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, each with clear purpose. First sentence defines the tool and its outputs; second sentence provides usage guidance. No fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one optional parameter) and the presence of an output schema, the description covers the essentials: what it does, when to use, and parameter behavior. Could further differentiate from sibling tools, but overall complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only defines 'region' as a string with default empty. The description adds meaning: 'Pass a region name or leave empty for global overview.' This clarifies usage beyond the schema. With 0% schema description coverage, the description compensates well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Geopolitical risk assessment by region.' It specifies outputs (risk_score, signals, commodity impact) and usage pattern (pass a region or leave empty for global). This effectively distinguishes it from sibling tools like latam_pulse or real_estate_pulse.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage context: 'Use when geopolitical events may affect a trade, supply chain, or commodity position.' While not comparing directly to siblings, this guidance is clear and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden. It mentions real-time nature and a monetary cost ($0.05 via x402), which is critical behavioral context. Does not mention rate limits or authentication, but cost and real-time are key traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: three short sentences, each adding unique value (scope, outputs, cost). No redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-input tool with output schema, description is thorough: models, providers, outputs, and cost. Does not explain 'x402' mechanism but overall adequate. Minor detail missing but still effective.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist; schema coverage is 100% by default. Baseline for 0-parameter tools is 4. Description adds context about the return structure, indirectly helping understand the lack of input.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool retrieves real-time GPU compute spot prices for specific models (H100, H200, etc.) from named providers (Vast.ai, RunPod, etc.), and lists the exact outputs (best_deals, market_signal, AI infrastructure brief). A specific verb and resource with precise scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit instructions on when to use versus alternatives; usage is implied by the domain (GPU pricing). Lacks guidance on when not to use or alternative tools, though siblings are mostly unrelated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes the return of a severity-graded report with root cause analysis and remediation, lists vulnerability types, and states the pricing model. It does not mention auth requirements or rate limits, but the behavioral core is well-covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and packed with essential information: purpose, supported platforms, vulnerability types, output format, input options, and pricing. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (security audit with multiple vulnerability types) and the presence of an output schema (so return values are covered), the description provides sufficient context. It could include expected usage notes or prerequisites, but is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description mentions two parameters implicitly ('source' and 'github_url' via 'Provide raw Move source code or a GitHub URL') and adds context about their purpose, but does not explicitly describe all three parameters or their formatting requirements.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it's a 'Move smart contract security audit' for Aptos and Sui, specifying types of vulnerabilities detected. This distinguishes it from sibling tools like 'smart_contract_audit' and 'rust_contract_audit' which target other languages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions providing source code or a GitHub URL as input, and indicates the cost and output format. However, it does not explicitly state when to prefer this tool over siblings or when not to use it.
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 provided, so description must cover behavior. It lists monitored metrics but lacks details on data freshness, rate limits, or effects of invalid symbols. As a monitoring tool, it's likely read-only, but not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff, front-loaded with key information. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description sufficiently covers inputs and purpose. It does not elaborate on output format, but the schema handles that. The description is adequate for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, but the description adds meaning by listing example symbols and the option to leave empty. It clarifies usage beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it monitors stablecoin stability with specific metrics like peg deviation, backing ratio, mint/burn activity, and depeg risk score. It distinguishes itself from sibling tools by focusing on stablecoins.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to pass a symbol (USDC/USDT/DAI/FRAX) or leave empty for a full report. However, it does not compare with alternatives or specify when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description bears full responsibility for behavioral disclosure. It discloses the cost ($0.05 via x402) and the data returned, implying a read-only operation. However, it does not mention caching, rate limits, or authentication requirements, which would improve transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences that front-load the purpose ('Global supply chain stress monitor') and quickly enumerate key outputs. No wasted words; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and an output schema exists, the description adequately covers the returned fields and their significance. It could be improved by briefly explaining how the stress_score is derived, but overall it is complete for its complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the input schema is empty. Per guidelines, a baseline of 4 is assigned. The description does not add parameter detail, but it is not needed since there are none.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly defines the tool as a 'Global supply chain stress monitor' and explicitly lists the data it returns (stress_score, shipping rates, etc.). It effectively distinguishes from sibling tools like agricultural_commodities or energy_markets, which focus on specific sectors.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context that high stress_score indicates input cost pressure and delivery delays upstream of earnings, which hints at usage for earnings analysis. However, it does not explicitly compare to alternative tools or specify conditions for when to use or avoid this tool.
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?
With no annotations provided, the description bears full responsibility for behavioral disclosure. It explains what the tool does (monitor) and what it returns (risk score, exposure at price drops, narrative). It does not mention authorization requirements, rate limits, or side effects, but the tool is inherently read-only. A score of 3 is appropriate as it adds value but lacks some context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with zero wasted text. The first sentence states the core function and platform, the second lists outputs and importance. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and a complex output (risk score, exposure at multiple thresholds, narrative), the description covers the key elements. However, without seeing the output schema, there might be additional return values not mentioned. Still, the description is sufficient for an AI to understand what the tool does and returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so schema description coverage is 100%. The description fully compensates by explaining the tool's purpose and output in detail, adding meaning beyond the bare schema. Baseline is 3, but the description is exemplary in this context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb-resource pair: 'tracks collateral-at-risk curves across Morpho Blue markets'. It clearly distinguishes itself from sibling tools like 'defi_risk' or 'liquidations' by naming the specific protocol and the exact type of risk assessment (liquidation cascade).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states it is 'critical for assessing systemic DeFi risk', providing a clear use case. However, it does not explicitly mention when not to use it or suggest alternatives among the many sibling tools, which would be helpful for an AI agent.
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?
Without annotations, the description carries full burden. It discloses the return fields (insider name, role, transaction type, shares, value, date) and source (SEC Form 4), but does not cover authorization needs, rate limits, data freshness, or error handling. The read-only nature is implicit but not stated, leaving moderate gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at three sentences, with the core action in the first sentence. Every sentence adds value: purpose, return fields, usage signals, and pairing suggestions. No redundant or unnecessary text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple one-parameter tool and presence of an output schema, the description is sufficiently complete. It explains what data is returned, gives interpretative signals, and suggests complementary tools. The output schema handles the details of the return structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'ticker' has 0% schema description coverage. The description adds critical meaning by specifying 'US stock ticker', clarifying the input type and geographic scope. This goes beyond the raw schema, but does not detail format (e.g., case, exchange suffix).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves 'SEC Form 4 insider trading activity for any US stock ticker', with a specific verb ('returns list of trades') and resource ('insider trading activity'). It distinguishes itself from sibling tools like equity_analysis and news_sentiment by focusing exclusively on insider transactions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides usage context by noting that insider buying clusters are bullish and selling before earnings is a red flag, implying when the tool is valuable. It also suggests pairing with equity_analysis() and news_sentiment(), offering integration guidance. However, it does not explicitly state when not to use it or compare against alternatives.
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 that the tool shows forced-out liquidation data and signals, but does not mention data freshness, update frequency, or any read-only guarantee. The disclosure is adequate but could be more explicit about behavioral traits like whether data is real-time or historical.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with five sentences each adding distinct value: core purpose, signal types, content summary, usage pairing, and comparative advantage. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given 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 an output schema exists (albeit not shown), the description is complete. It covers what the tool does, what it shows, how to use it with other tools, and its relative strength. No gaps are apparent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the input schema is fully covered. With no parameters, the description does not need to add parameter-level detail. Baseline score of 4 is appropriate as there is nothing further to explain.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides perp liquidation data across OKX for a specific set of assets. It lists what it shows (long vs short volume, biggest events, hottest zones) and distinguishes itself from siblings by mentioning pairing with funding_rates() and open_interest() and claiming higher-signal value.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly suggests using it alongside funding_rates() and open_interest() for a complete positioning picture, and compares it to OI and funding rates, stating it's higher-signal. This provides clear guidance on when to use this tool relative to alternatives, though it lacks explicit when-not-to-use scenarios.
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 provided. Description says the tool gives 'real-time' data but does not mention update frequency, rate limits, or other constraints. For a read-only data retrieval tool, it is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, front-loaded with purpose and then usage/parameter guidance. No extraneous words; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a single optional parameter and an existing output schema, the description covers the tool's purpose, use cases, and parameter format completely.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description fully explains the 'region' parameter by listing all valid region codes (CISO, ERCO, etc.), adding significant meaning beyond the schema's plain string type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it provides US electricity grid intelligence (real-time demand, generation mix, grid stress signals) and specifies use cases like optimizing industrial operations, EV charging, and compute workloads. This differentiates it from sibling tools like energy_markets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Describes explicit use cases and provides region codes with guidance on leaving empty for all regions. Does not explicitly mention when not to use or alternatives, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It explains that the yield curve spread being negative indicates a recession signal, and lists all returned fields with brief interpretation. It does not mention data freshness, update frequency, or any limitations, but for a simple snapshot tool, the transparency is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only three sentences, with the purpose front-loaded. It is concise with no redundant or extraneous information. Every sentence serves a clear purpose: stating the function, listing outputs, and suggesting usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given 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, but has an output schema (context signals indicate 'Has output schema: true'), the description is complete. It explains the output in a way that compensates for the lack of annotations and provides sufficient context for an agent to decide when to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, and the description adds value by explaining each of the returned indicators and their meaning (e.g., negative spread = recession signal). This exceeds the baseline of 4 for no-parameter tools, as it enables an agent to correctly interpret the output.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a 'US macroeconomic regime snapshot' with specific indicators (fed funds rate, yield curve spread, etc.). It directly names the resource (macro indicators) and verb (returns/snapshot). While it pairs well with siblings like equity_analysis and portfolio_risk, it does not explicitly distinguish this tool from similar data tools in the sibling list, such as wealth_pulse or stablecoin_pulse.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly suggests using the tool to 'assess whether macro conditions favor risk-on or risk-off positioning.' It also mentions pairing with equity_analysis() and portfolio_risk(). However, it does not provide exclusions or alternatives for when not to use this tool, leaving some ambiguity among the many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Details output: USD totals, per-exchange breakdown, 5-min OI delta, dominant exchange. Implies read-only data retrieval without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences: first defines scope, second signals, third output and pairing. Front-loaded, no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With zero parameters and an output schema, description effectively covers return values and use case. Lacks mention of limitations (rate limits, history), but still substantial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters, baseline 4 per instructions. Description adds value by explaining what the tool returns, beyond empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Describes specific verb-resource: perpetual futures open interest across specific exchanges and assets. Distinguishes from sibling tool funding_rates by mentioning pairing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explains signal-first categorization (ACCUMULATING/DELEVERAGING/MIXED) and suggests pairing with funding_rates for a complete picture. Does not explicitly state when not to use, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
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 the analysis method (RattlerAI with Claude Opus + Slither), false positive filtering, and output format. It also mentions the cost ($2.00). Lacking are potential destructive behaviors or side effects, but as a read-only analysis tool, this is acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single five-sentence paragraph that is dense with information: purpose, capabilities, validation, output format, usage, and cost. Every sentence adds value with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of the tool and the presence of an output schema (not shown), the description covers key aspects: vulnerability classes, validation, output format (severity report), and usage. It lacks explicit error handling or prerequisites (e.g., Solidity version), but overall it is sufficiently complete for an AI agent to use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates by explaining that 'source' can be Solidity code or a GitHub URL (implied for `github_url` parameter). It also mentions `contract_name` with default 'Contract'. Although not all parameters are fully detailed, it adds meaningful guidance beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool does a 'Solidity smart contract security audit' and lists specific vulnerability classes, distinguishing it from sibling audit tools like 'rust_contract_audit' and 'move_contract_audit'. The verb 'audit' and resource 'smart contract' are explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states 'Ideal as a pre-deploy sanity check or audit triage', providing clear use cases. It also specifies input types (Solidity source code or GitHub URL). However, it does not explicitly exclude non-Solidity contracts or mention when not to use this tool over siblings.
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?
With no annotations, the description must fully disclose behavioral traits. It states 'real-time' and lists output fields, but omits details on rate limits, authentication, pagination, data freshness, or what happens when no transfers are found. This is adequate but has gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, with the purpose front-loaded. Each sentence adds value: first states what it does, second lists outputs, third explains parameter and use case. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one optional parameter and an existing output schema, the description covers inputs, outputs, and use case sufficiently. It provides all needed context for an AI agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, but the description fully explains the single parameter min_usd: it sets the threshold in USD with a default of $1M. This adds complete meaning beyond the schema's type and default.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool provides real-time whale transfer alerts on Base and Ethereum, listing large on-chain transfers with details. It clearly identifies the verb 'alert' and resource 'whale transfers', and the tool is distinct from its siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool (detect smart money movements, monitor capital flows) and how to set a threshold via min_usd. However, it does not provide explicit guidance on when not to use it or mention alternative tools, though siblings are unrelated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses auto-routing for crypto queries and details return fields including scales. No annotations provided, so description carries full burden and does so effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences front-loaded with purpose. No wasted words. Perfectly concise for the information conveyed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists (implied), description covers return fields, usage context, and special behavior. Complete for a simple parameter tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Single 'query' parameter with 0% schema coverage. Description gives examples (stock ticker or crypto asset) but no exact format or constraints. Adequate but not comprehensive.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb 'returns sentiment' and resource 'news'. Specific outputs listed. Distinguishes from siblings like equity_analysis by focusing on news sentiment.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit use case 'before a trade to detect sentiment regime or monitor news flow'. Pairs well with three sibling tools, providing context for when to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
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 sources, cost ($0.05), and output fields including risk level. It implies read-only behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is 5 sentences, front-loaded with main purpose, and each sentence provides necessary information without fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers purpose, usage, output fields, and cost. An output schema exists, so return format is detailed elsewhere. Slightly more detail on risk levels could help, but sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'symbol' is explained: passing a symbol filters, leaving blank returns full report. The schema has 0% coverage, so the description fully compensates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides 'Live staking yield comparison across 7 assets' and lists the assets and output types. It distinguishes itself from sibling tools by focusing specifically on staking yields.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use when an agent needs to know where to stake an asset for maximum yield.' It also explains how to filter by symbol or leave blank for full report.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that the tool auto-fetches holdings, values positions, flags stablecoin% and concentration, and returns a unified risk score and narrative. It implies a read-only, analytical behavior but lacks explicit statements about destructive actions, authentication needs, or data freshness. Additional detail on input validation or network dependencies would improve transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the core purpose ('Cross-asset portfolio risk analyzer.') followed by concise details on inputs and outputs. Every sentence adds value without repetition or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 optional parameters) and the presence of an output schema, the description adequately covers inputs and outputs. It explains what the tool does, what it accepts, and what it returns (risk score 1-10, AI narrative, flags). No critical gaps are evident.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It explains that 'wallet' is a wallet address, 'tickers' are stock tickers, and 'contracts' are token contracts. This adds meaning beyond the property names, but does not specify formats (e.g., comma-separated) or provide examples, leaving some ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a cross-asset portfolio risk analyzer with specific inputs (wallet, tickers, contracts) and outputs (risk score, AI narrative, flags). It distinguishes itself from siblings like 'portfolio_risk' or 'defi_risk' by emphasizing its cross-asset scope and on-chain/off-chain integration.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that the tool accepts wallet addresses (auto-fetching Base on-chain holdings) plus stock tickers and token contracts. It implies usage for cross-asset risk analysis but does not explicitly state when to use this tool over siblings such as 'portfolio_risk' or 'wallet_risk', nor does it mention limitations (e.g., only Base network for wallet).
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, and the description does not disclose behaviors such as update frequency, permissions, or potential rate limits. It only describes outputs, which is sufficient but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four well-organized sentences: scope, outputs, key field explanation, and use cases. No unnecessary words, front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and presence of an output schema, the description covers all essential aspects for tool selection and invocation, including context about LatAm focus and specific crisis signals.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters, the description focuses on explaining output fields in detail, such as the meaning of argentina_blue_premium_pct >100%. This adds value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Latin American economic intelligence' and details specific outputs like per-currency rates and crisis signals, distinguishing it from broader tools like macro_indicators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides use cases: 'EM FX exposure, Argentina crisis monitoring, or commodity supply chain analysis', giving strong guidance on when to use this tool versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full weight. It discloses that the tool is a non-destructive analysis returning a severity-graded report, includes cost ($2 via x402), and mentions required inputs (source code or GitHub URL). No contradictions with annotations (none present).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense and informative, with the main purpose front-loaded. It includes details on framework detection, checks, output, and cost. While slightly verbose, it remains structured and efficient for the complexity of the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (multiple frameworks, many checks), the description is comprehensive. It specifies input methods, auto-detection, types of vulnerabilities, report format, and cost. This fully contextualizes the tool for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates by indicating that 'source' and 'github_url' are accepted inputs. It does not explicitly describe the 'contract_name' parameter, but overall provides sufficient guidance for the main parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it performs Rust smart contract security audits, auto-detects frameworks (CosmWasm, Anchor/Solana, Stellar/Soroban, NEAR), and lists specific checks. This distinguishes it from siblings like 'smart_contract_audit' and 'move_contract_audit' by specifying language and framework support.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (for Rust smart contracts) by naming frameworks and checks. It does not explicitly exclude other languages or mention alternatives, but the context of siblings and the focused description provide clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description fully discloses behavior: refresh every 15 minutes, lists endpoints (/whales, /trending, etc.), and format of whale_alerts output. Exceeds annotation requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with key purpose, uses brief sentences, no filler. Every sentence adds value (purpose, use cases, refresh rate, endpoints).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless tool with output schema, description fully covers input, behavior, use cases, refresh schedule, and extra endpoints. No gaps identified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters (0 params, 100% schema coverage), so baseline 4 applies. Description does not need to add param info; schema already sufficiently covers empty input.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly specifies it provides on-chain intelligence for Base and Ethereum, listing specific data points (whale_alerts, dex_volume_24h, gas_price_gwei, TVL rankings). Distinct from siblings like whale_alert by covering multiple data types and chains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states use cases: monitor large wallet movements, spot DEX volume spikes, track DeFi protocol health. Lacks explicit when-not-to-use or alternatives, but siblings list provides context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description fully shoulders the burden. It discloses the blend of empirical and Gumbel methods, the forced PASS signal when method_divergence > 0.15, the outlier model, coordinate alignment, and cost ($0.02). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact yet information-rich. Each sentence adds value: model composition, threshold behavior, signal logic, coordinate alignment, city list, direction, and cost. No redundant or superfluous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (multi-model, probabilistic methods, signal logic) and the existence of an output schema, the description provides thorough coverage of inputs, processing, outputs (including signal, outlier, probabilities), and cost. It is complete for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must add meaning. It enumerates cities, explains threshold usage (when given, returns probabilities and method_divergence), and clarifies direction as 'greater' or 'less'. However, it does not specify the date format or provide examples for all parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides weather probability using a 7-model consensus and 80 ensemble members. It lists specific cities, threshold, direction, and return fields (signal, probability, outlier). This distinguishes it from all sibling tools, which are non-weather.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for precise weather probability aligned to NWS ASOS stations used by Kalshi/Polymarket, suggesting use in prediction markets. However, it does not explicitly state when not to use it or provide alternative tools. Given siblings are unrelated, this is not a major omission.
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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