cryptopunks-mcp-server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation3/5
Many tools have overlapping purposes, such as get_punk, get_punk_details, get_punk_metadata, and get_punk_traits, which all retrieve information about a specific punk with subtle differences. Similarly, generate_merkle_proof and generate_batch_proofs serve similar functions but for single vs. multiple punks. However, the detailed descriptions help clarify distinctions, preventing complete confusion.
Naming Consistency5/5
Tool names follow a highly consistent verb_noun pattern throughout, such as get_punk, generate_merkle_root, and verify_batch_proofs. All tools use snake_case uniformly, with clear and predictable naming conventions that enhance readability and predictability.
Tool Count2/5
With 28 tools, the count feels excessive for the domain of CryptoPunks data and proof generation. Many tools could be consolidated, such as the multiple punk info retrieval tools, leading to redundancy and potential confusion rather than necessary granularity.
Completeness5/5
The tool set comprehensively covers the CryptoPunks domain, including data retrieval for punks, market stats, bids, sales, history, images, and proof generation/verification. There are no obvious gaps; it supports full lifecycle and operational needs for agents interacting with this NFT collection.
Average 4/5 across 28 of 28 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 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
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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 provided, the description carries the full burden of behavioral disclosure. It states the tool returns specific data fields but doesn't mention error handling, performance characteristics, rate limits, or authentication requirements. It adds minimal context beyond the basic operation, leaving significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, stating the core purpose in the first clause. Both sentences earn their place by specifying the data returned and clarifying coverage for all punk types, with no redundant or verbose language.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is minimally adequate. It explains what data is returned but lacks details on output format, error conditions, or integration with sibling tools, leaving room for improvement in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'punk_index' fully documented in the schema. The description doesn't add any parameter-specific information beyond what the schema provides, such as examples or edge cases, so it meets the baseline for high schema coverage without compensating value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: retrieving traits/attributes for a specific CryptoPunk, including type, type name, attributes array, and count. It specifies the resource (CryptoPunk) and verb (get traits), but doesn't explicitly differentiate from sibling tools like get_punk or get_punk_metadata, which might provide overlapping or related data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions returning 'accurate type data for all punk types' but doesn't compare it to sibling tools like get_punk or get_punk_metadata, leaving the agent to infer usage context without explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool 'Returns summarized bid metadata,' which gives some insight into output behavior, but it lacks details on permissions, rate limits, pagination, or error handling. For a tool with no annotations, this leaves significant gaps in understanding how it behaves 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence clearly states the purpose, and the second sentence adds a practical tip without unnecessary details. Every sentence earns its place, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, no output schema, no annotations), the description is moderately complete. It covers the core purpose and offers a usage tip, but lacks details on output format, error cases, or how it differs from sibling tools. Without annotations or an output schema, more context would be beneficial for full understanding, but it meets a minimum viable level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 33% (only 'status' has a description in the schema). The description adds minimal parameter semantics: it hints at using 'status' with 'pending' for active bids, but doesn't explain 'limit' or 'chain_id' beyond what the schema provides (e.g., default values, ranges). Since schema coverage is low (<50%), the description doesn't fully compensate for the gaps, resulting in a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get the highest collection bids ordered by bid amount descending. Returns summarized bid metadata.' It specifies the verb ('Get'), resource ('collection bids'), and ordering/scope ('highest...ordered by bid amount descending'), which is specific. However, it doesn't explicitly differentiate from sibling tools like 'get_all_collection_bids' or 'get_collection_bids', leaving some ambiguity about when to use this vs. those alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage guidance through the tip: 'Tip: try status 'pending' if default returns empty results.' This suggests using the 'status' parameter for better results, but it doesn't explicitly state when to use this tool over alternatives (e.g., 'get_all_collection_bids' or 'get_collection_bids'), nor does it mention any exclusions or prerequisites. The guidance is helpful but incomplete for distinguishing among siblings.
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 states what the tool returns but doesn't disclose behavioral traits like whether results are paginated, real-time vs cached, rate limits, authentication requirements, or error conditions. The description is minimal and lacks operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every element ('Get', 'top CryptoPunks holders leaderboard', 'ranked by number of punks owned') contributes directly to understanding the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and no output schema, the description is incomplete. It doesn't specify what format the leaderboard returns (e.g., list of addresses with counts, timestamps, pagination details), whether it includes additional metrics like total value, or any limitations (e.g., top 100 only). For a data retrieval tool with no structured output documentation, this leaves significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters and 100% schema description coverage, the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and the schema already fully documents the empty input structure.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get'), resource ('top CryptoPunks holders leaderboard'), and ranking criteria ('ranked by number of punks owned'). It distinguishes this tool from siblings like get_account or get_punk which retrieve individual account or punk data rather than aggregated leaderboard rankings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (when you need top holders information) but doesn't explicitly state when to use this tool versus alternatives. No guidance is provided about prerequisites, exclusions, or comparisons to similar tools like get_market_stats or get_attribute_stats.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool reads trait distribution statistics but doesn't mention potential rate limits, authentication requirements, data freshness, or what format the statistics are returned in. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core functionality and purpose. Every element ('Get trait distribution statistics', 'across the entire 10,000 CryptoPunks collection', 'enabling rarity analysis') earns its place with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description provides adequate context about what the tool does and its scope. However, it lacks details about the return format (e.g., structured statistics vs. raw data) and doesn't address potential limitations or behavioral aspects that would be helpful given the absence of annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage. The description appropriately doesn't discuss parameters since none exist, and it adds value by explaining the scope ('entire 10,000 CryptoPunks collection') and purpose ('rarity analysis') beyond what an empty schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get trait distribution statistics') on a specific resource ('across the entire 10,000 CryptoPunks collection'), with explicit purpose ('enabling rarity analysis'). It distinguishes itself from sibling tools by focusing on attribute statistics rather than individual punks, bids, or market data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for 'rarity analysis' but doesn't explicitly state when to use this tool versus alternatives like 'get_punk_traits' or 'get_market_stats'. It provides context about the collection scope but lacks explicit guidance on when-not-to-use or named 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context by stating 'Pure computation, no wallet required,' which clarifies it's a non-destructive, read-like operation without external dependencies. However, it lacks details on computational limits, error handling, or output format, leaving gaps in behavioral understanding for an AI agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded and efficiently structured in two sentences: the first defines the core functionality, and the second adds context and usage. Every sentence earns its place by providing essential information without redundancy, making it easy for an AI agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's computational nature, no annotations, and no output schema, the description is moderately complete but has gaps. It covers purpose and basic usage but lacks details on output format, error cases, or performance constraints, which could hinder an AI agent's ability to handle edge cases effectively in this context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents both parameters thoroughly. The description adds minimal value beyond the schema by implying the tool uses 'punk_indices' for the Merkle tree, but it doesn't explain parameter interactions or provide additional semantic context, such as how 'expected_root' affects verification behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Generate a Merkle root') for a specific resource ('set of CryptoPunk indices'), distinguishing it from siblings like 'generate_merkle_proof' or 'generate_batch_proofs' by focusing on root computation rather than proof generation. It also specifies the application context ('first step in constructing a collection bid'), making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use this tool ('first step in constructing a collection bid') and clarifies that it's 'Pure computation, no wallet required,' which helps differentiate it from wallet-dependent operations. However, it doesn't explicitly state when not to use it or name specific alternatives among siblings, such as when proofs are needed instead.
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 the full burden of behavioral disclosure. It adds useful context about the maximum batch size (50 punk indices per call), which is not in the schema. However, it does not disclose other behavioral traits like rate limits, authentication needs, response format, or what 'recent' means temporally, leaving gaps for a mutation-free read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with three concise sentences. Each sentence earns its place: the first states the purpose, the second provides usage context, and the third specifies a key constraint. It is front-loaded with essential information and has zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (batch read operation), no annotations, and no output schema, the description is partially complete. It covers purpose, usage context, and a size constraint, but lacks details on response format, error handling, or temporal scope ('recent'), which are important for a tool with no structured output documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents the single parameter 'punk_ids' with its constraints. The description adds no additional semantic meaning beyond what the schema provides (e.g., it repeats the max 50 limit but doesn't explain format or usage nuances). Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get recent transaction history'), the resource ('multiple CryptoPunks'), and the scope ('in a single request'). It distinguishes from sibling tools like 'get_punk_history' (which appears to fetch history for a single punk) by emphasizing batch capability for comparison across punks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool ('Useful for comparing activity across a set of punks'), but does not explicitly state when not to use it or name specific alternatives. It implies usage for batch operations versus single-punk tools, but lacks explicit exclusions or named sibling comparisons.
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 the tool's purpose and context (on-chain settlement), but lacks details on behavioral traits such as rate limits, error handling, or response format. It does not contradict annotations, as there are none.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence, followed by usage context. Both sentences are essential—the first defines the tool, and the second provides practical guidance—with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a single-parameter tool for proofs), no annotations, and no output schema, the description is adequate but incomplete. It explains the purpose and usage but lacks details on output format, error cases, or behavioral constraints, which are important for a tool involved in on-chain settlement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the bid_id parameter fully documented. The description adds minimal semantic context by mentioning the source of the bid_id ('from any of the collection bid listing tools'), but does not provide additional meaning beyond what the schema already covers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get the Merkle proofs') and the resource ('every punk index covered by a specific collection bid'), with a specific purpose ('Required for on-chain settlement when accepting a collection bid'). It distinguishes from siblings by focusing on proofs for collection bids, unlike tools like get_punk or get_collection_bids.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool ('Required for on-chain settlement when accepting a collection bid') and specifies the source of the bid_id ('Use the bid UUID from any of the collection bid listing tools'). However, it does not explicitly state when not to use it or name alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions ordering and scope ('all-time highest'), but lacks details on behavioral traits like pagination, rate limits, permissions, or what the output format looks like (e.g., list of sales with details). This leaves gaps for an agent to understand how to handle results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the key information ('Get the all-time highest sales') and includes essential details ('ordered by sale value descending') without any waste. Every word contributes to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (simple read operation with no parameters) and lack of annotations and output schema, the description is minimally complete. It specifies what data is retrieved and ordering, but does not cover output format or behavioral aspects like result limits, which could be important for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so no parameter information is needed. The description does not add param semantics, but with no params, the baseline is 4 as it adequately addresses the tool's function without unnecessary details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('all-time highest sales in the CryptoPunks collection'), and distinguishes it from siblings like get_recent_sales by specifying 'all-time highest' and 'ordered by sale value descending'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying 'all-time highest sales' and 'ordered by sale value descending', which helps differentiate it from tools like get_recent_sales. However, it does not explicitly state when to use alternatives or any exclusions, such as whether it returns a limited number of results or all sales.
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 behavioral traits like returning comprehensive data and being information-dense, but it lacks details on rate limits, authentication needs, or potential errors. The description does not contradict any annotations, as none exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the first sentence clearly stating the purpose and scope, followed by a list of data types and a concluding statement about its density. Every sentence adds value without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (comprehensive data retrieval) and lack of annotations and output schema, the description is mostly complete but could improve by detailing output format or behavioral constraints. It covers the purpose and data types well, but additional context on response structure or limitations would enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters well. The description does not add meaning beyond the schema, as it does not explain parameter usage or interactions (e.g., how 'owned_only' affects the output). Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('Get comprehensive portfolio data') and resources ('Ethereum wallet or ENS name'), and it distinguishes itself from siblings by listing detailed data types (owned punks, punks for sale, bids, history, PnL, volume) that are not covered by other tools like get_punk or get_punk_history.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool ('most information-dense endpoint in the API'), implying it's for comprehensive portfolio analysis. However, it does not explicitly state when not to use it or name specific alternatives among the sibling tools, such as using get_punk for individual punk data instead.
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 the full burden of behavioral disclosure. It adds useful context: it describes the scope of events (initial claim through all transfers, offers, bids, and sales), the data included in each event, and mentions 'Uses the POST endpoint for reliable history retrieval' which hints at implementation details. However, it doesn't cover potential limitations like rate limits, error conditions, or data freshness, leaving gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured in two sentences: the first explains what the tool does and what data it returns, and the second adds implementation context. Every sentence adds value without redundancy, making it front-loaded and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (retrieving detailed historical data), no annotations, and no output schema, the description does a good job of explaining the scope and content of the returned data. It covers the types of events and data fields included, which is crucial for understanding the tool's output. However, without an output schema, it could benefit from more detail on the response structure or pagination, but it's largely complete for its purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the single parameter 'punk_index' well-documented in the schema (CryptoPunk index 0–9999). The description doesn't add any parameter-specific semantics beyond what's in the schema, but it reinforces the context by mentioning 'for a specific CryptoPunk'. Baseline 3 is appropriate given high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get the full transaction history for a specific CryptoPunk' with specific details on what events are included (initial claim, transfers, offers, bids, sales) and what data each event contains (type, addresses, amounts, timestamp, transaction hash). It distinguishes itself from siblings like get_batch_recent_history or get_recent_sales by focusing on a single punk's complete history rather than batch or recent data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying 'for a specific CryptoPunk' and 'full transaction history', suggesting it should be used when detailed historical data is needed for one punk. However, it doesn't explicitly state when to use this tool versus alternatives like get_batch_recent_history or get_recent_sales, nor does it mention any prerequisites or exclusions.
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 full burden and does well by disclosing: the tool returns a URL string (not the image itself), the image format (PNG), dimensions (1024×1024), and available customizations. It could improve by mentioning rate limits, authentication needs, or error conditions, but covers core behavioral aspects adequately.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tightly packed sentences with zero waste. First sentence establishes purpose and key features, second clarifies the return type and next steps. Every word earns its place, and the most important information (what the tool does) appears immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only tool with comprehensive schema coverage and no output schema, the description provides sufficient context about what the tool delivers. It could be more complete by mentioning typical use cases, performance characteristics, or error scenarios, but covers the essential functionality well given the structured data available.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds marginal value by grouping parameters conceptually ('transparent background', 'custom hex background color', 'optional overlays') but doesn't provide additional syntax, format details, or usage examples beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get the URL'), resource ('CryptoPunk image'), and key characteristics ('1024×1024 PNG', 'transparent background', 'custom hex background color', 'optional overlays'). It distinguishes itself from sibling tools by focusing on image URL generation rather than data retrieval or proof generation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a CryptoPunk image URL is needed with specific visual customizations, but provides no explicit guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, limitations, or compare with other image-related tools (though none appear in the sibling list).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 this is a read operation ('Get') and highlights reliability for type classification, which is useful behavioral context. However, it does not mention potential limitations like rate limits, authentication needs, or error conditions, leaving gaps in behavioral transparency for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence and adds a key behavioral insight in the second. Both sentences earn their place by providing essential information without redundancy, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is fairly complete. It covers purpose, usage context, and key behavioral traits. However, without annotations or output schema, it could benefit from more detail on return format or error handling, but it adequately supports basic agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'punk_index' well-documented in the schema (integer, 0-9999). The description does not add any parameter-specific information beyond what the schema provides, such as examples or usage tips. Baseline 3 is appropriate since the schema handles parameter semantics adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get lightweight metadata') and resource ('for a CryptoPunk'), listing the exact data returned (type, type name, attributes array, attribute count). It distinguishes from siblings by specifying this is for 'lightweight metadata' and 'the most reliable endpoint for accurate type classification,' differentiating from tools like get_punk_details or get_punk_traits.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool: for obtaining 'lightweight metadata' and 'accurate type classification.' It implies this is preferable for type classification over other tools, but does not explicitly state when not to use it or name specific alternatives, though siblings like get_punk_details suggest more detailed data might be available elsewhere.
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 full burden for behavioral disclosure. It effectively describes key behaviors: the tool returns specific data fields (buyer, seller, price in wei/USD, timestamp, transaction hash), has a count cap of 50, and focuses on 'most recent' sales. However, it doesn't mention potential limitations like rate limits, authentication requirements, or data freshness guarantees.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise with two sentences that each earn their place. The first sentence states purpose and return values, the second adds the critical constraint about count capping. No wasted words, and information is front-loaded appropriately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read operation with no output schema, the description provides good coverage of what the tool does, what it returns, and its main constraint. However, without annotations or output schema, it could benefit from more behavioral context about response format, pagination, or error conditions to be fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing complete documentation for the single 'count' parameter. The description adds minimal value beyond the schema by mentioning 'Count is capped at 50', which is already covered by the schema's maximum constraint. No additional parameter semantics are provided beyond what's in the structured schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get the most recent sales'), identifies the resource ('across the CryptoPunks collection'), and specifies the scope ('most recent'). It distinguishes itself from sibling tools like 'get_top_sales' by focusing on recency rather than value ranking.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving recent sales data, but provides no explicit guidance on when to use this tool versus alternatives like 'get_top_sales' or 'get_punk_history'. It mentions the count cap of 50, which offers some contextual constraint, but lacks explicit when/when-not scenarios or prerequisite information.
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 effectively discloses key behavioral traits: it's a pure computation (stateless, no side effects), requires no wallet (no authentication needed), and returns results per punk index. It doesn't mention error handling, performance characteristics, or rate limits, but covers the essential safety profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences with zero waste: first states purpose, second adds behavioral context, third specifies output format. Each sentence earns its place by providing distinct, valuable information beyond what's in the name or schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a pure computation tool with no annotations but 100% schema coverage and no output schema, the description is reasonably complete. It covers purpose, behavioral context, and output format. The main gap is lack of explicit guidance on when to use batch vs singular verification, but otherwise it provides sufficient context for agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents both parameters. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain proof array format or root encoding). Baseline 3 is appropriate when the schema does all the parameter documentation work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('verify Merkle proofs'), the resource ('multiple punks'), and the scope ('against a single Merkle root'). It distinguishes from sibling tools like 'verify_merkle_proof' (singular) and 'generate_batch_proofs' (generation vs verification).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through 'Pure computation, no wallet required,' suggesting this is a stateless verification tool. However, it doesn't explicitly state when to use this batch version versus the singular 'verify_merkle_proof' sibling tool, nor does it mention prerequisites 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively communicates key behavioral traits: 'Pure computation, no wallet required' indicates this is a stateless calculation without authentication or side effects, and 'Used to prove... for on-chain settlement' clarifies the real-world application. However, it doesn't mention performance characteristics, error conditions, or what the proof output looks like.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise with three sentences that each earn their place: first states the core functionality, second provides important behavioral context (computation-only), third gives usage context. No wasted words, and the most important information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 3-parameter computational tool with no annotations and no output schema, the description provides adequate but incomplete coverage. It explains the purpose and behavioral context well but doesn't describe the proof output format, error conditions, or performance characteristics. Given the computational nature and lack of output schema, more detail about what the tool returns would be helpful for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 67% (2 of 3 parameters have descriptions). The description adds minimal parameter semantics beyond the schema - it mentions 'single punk' and 'set of punk indices' which aligns with target_punk_index and punk_indices parameters. However, it doesn't explain the expected_root parameter (which has no schema description) or provide additional context about parameter relationships or constraints beyond what's in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('Generate a Merkle proof') and resource ('for a single punk within a set of punk indices'). It distinguishes from siblings by specifying it's for single-punk proofs (vs. batch operations like generate_batch_proofs) and mentions the context of collection bids for on-chain settlement, which differentiates it from verification tools like verify_merkle_proof.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context about when to use this tool: 'Used to prove a specific punk is included in a collection bid for on-chain settlement.' It implies this is for proof generation rather than verification or root calculation (distinguishing from verify_merkle_proof and generate_merkle_root). However, it doesn't explicitly state when NOT to use it or name specific alternative tools for different 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?
With no annotations provided, the description carries full burden. It discloses ordering behavior and limit differences, but doesn't mention pagination, rate limits, authentication needs, or what 'summarized bid metadata' entails. It adds some behavioral context but leaves significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with zero waste. First states purpose and ordering, second describes return format, third provides crucial sibling comparison. Every sentence earns its place and is front-loaded with essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 3-parameter tool with no annotations and no output schema, the description provides good purpose and usage guidance but lacks details about authentication, error handling, rate limits, and the structure of returned 'summarized bid metadata.' It's adequate but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 33% (only 'status' has a description). The description mentions 'limit' parameter implicitly ('Higher limit... up to 1000') but doesn't explain 'chain_id' or provide additional context for 'status' beyond what's in the schema. It adds marginal value but doesn't fully compensate for low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get all collection bids'), specifies ordering ('ordered by creation date (most recent first)'), and distinguishes from a sibling tool ('Higher limit than get_collection_bids'). It provides specific verb+resource+scope differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly compares to sibling tool get_collection_bids, indicating when to use this tool ('Higher limit than get_collection_bids — up to 1000') and when to use the alternative. This provides clear guidance on tool selection.
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 returns 'summarized bid metadata' and mentions an alternative for Merkle proofs, but lacks details on permissions, rate limits, pagination, or error handling. It adds some context but is incomplete for behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with zero waste: the first states the purpose and return value, and the second provides explicit usage guidance with an alternative. It is front-loaded and efficiently structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is moderately complete: it clarifies the tool's purpose and distinguishes it from a sibling, but lacks details on output format, error cases, or behavioral constraints like rate limits. It's adequate but has gaps for a tool with 4 parameters and no structured output documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50%, with only 'punk_index' and 'status' having descriptions. The tool description does not add any parameter-specific information beyond what the schema provides, such as explaining 'limit' or 'chain_id' usage. Baseline is 3 due to partial schema coverage without compensation from the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('collection bids that cover a specific CryptoPunk'), and distinguishes it from the sibling tool 'get_bid_proofs' by specifying that it returns 'summarized bid metadata' rather than Merkle proofs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly provides when to use this tool ('Get all collection bids that cover a specific CryptoPunk') and when to use an alternative ('For Merkle proofs needed for on-chain settlement, use get_bid_proofs with the bid UUID'), offering clear guidance on tool selection.
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 history fetching uses a 'reliable POST endpoint' when include_history is true, adding implementation context. However, it lacks details on permissions, rate limits, error conditions, or response format, which are important for a tool with no output schema. The description does not contradict any annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose and key data points, followed by a specific behavioral note about the history endpoint. Every word earns its place, with no redundancy or fluff, making it highly efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is moderately complete. It covers the tool's purpose, parameters, and some behavioral context (POST endpoint for history). However, it lacks details on response structure, error handling, or authentication needs, which are gaps for a tool fetching detailed data. It's adequate but has clear room for improvement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents parameters. The description adds value by explaining that include_history fetches 'complete transaction history' and clarifies it uses a POST endpoint, providing context beyond the schema's boolean description. With 0 parameters, baseline would be 4, but here it compensates well for the high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and specifies the resource 'full details for a specific CryptoPunk', listing specific data points like owner, price, bid, attributes, and transaction history. It distinguishes from siblings like get_punk (likely basic info), get_punk_history (just history), and get_punk_metadata (just metadata) by emphasizing comprehensive details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: to retrieve detailed information about a specific CryptoPunk, optionally with history. It implies usage vs. simpler siblings by mentioning 'full details' and the include_history parameter. However, it does not explicitly state when NOT to use it or name specific alternatives, keeping it from a perfect score.
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 of behavioral disclosure. It effectively adds context by stating 'Pure computation, no wallet required' (clarifying authentication needs) and 'More efficient than calling generate_merkle_proof repeatedly' (performance characteristic), though it doesn't cover rate limits or error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise with two sentences that are front-loaded and zero wasted words. Every phrase adds value: the first sentence states the core purpose, and the second adds important behavioral context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a computational tool with no annotations and no output schema, the description provides good context about what it does and its efficiency advantage. However, it doesn't describe the return format or what happens with invalid inputs, leaving some gaps in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 67% (two parameters have descriptions, one does not). The description doesn't add any parameter-specific information beyond what the schema provides, so it doesn't compensate for the coverage gap. With moderate schema coverage, the baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('Generate Merkle proofs') and resources ('multiple target punks within a set'), and explicitly distinguishes it from its sibling 'generate_merkle_proof' by noting it's 'more efficient than calling generate_merkle_proof repeatedly.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool ('more efficient than calling generate_merkle_proof repeatedly'), but does not explicitly state when not to use it or mention other alternatives beyond the one sibling 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It specifies what data is returned ('full details, signature, status, and covered punk count'), which adds useful context beyond the input schema. However, it doesn't mention potential errors, rate limits, authentication requirements, or response format details, leaving some behavioral aspects unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with zero waste: the first sentence states the purpose and return data, and the second provides explicit usage guidance. It is front-loaded with the core functionality and efficiently structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (single parameter, no output schema, no annotations), the description is mostly complete: it covers purpose, usage guidelines, and return data. However, without annotations or output schema, it lacks details on error handling or response structure, which could be beneficial for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents the single parameter (bid_id as a UUID). The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints, resulting in the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get a specific collection bid') and resource ('by its UUID'), and distinguishes it from sibling tools by explicitly naming an alternative ('get_bid_proofs') for a different purpose ('For Merkle proofs'). This provides precise verb+resource+scope differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool ('Get a specific collection bid by its UUID') and when to use an alternative ('For Merkle proofs, use get_bid_proofs with the same UUID'), providing clear guidance on tool selection versus sibling 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?
With no annotations provided, the description carries the full burden. It discloses the tool's behavior by specifying it returns 'full details including index, owner, price, and attributes' and that it fetches the 'cheapest punk for sale right now.' However, it lacks information on potential limitations like rate limits, data freshness, or error conditions, which would be helpful for a read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently conveys the tool's purpose, scope, and output details without any wasted words. It is front-loaded with the core action and resource, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 0 parameters, no annotations, and no output schema, the description does a good job of explaining what the tool does and what it returns. However, it could be more complete by explicitly stating the lack of parameters or detailing the exact structure of the returned 'full details,' especially since there's no output schema to rely on.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately does not discuss parameters, focusing instead on the tool's purpose and output. This meets the baseline for zero parameters, but a perfect score would require explicit mention of the lack of parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get') and resource ('specific CryptoPunk currently listed at the floor price'), distinguishing it from siblings like 'get_floor_price' (which likely returns just the price) and 'get_punk' (which requires a punk index parameter). It specifies the exact scope: the cheapest punk for sale with full details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly indicates when to use this tool: when you need the cheapest available CryptoPunk with its complete details. However, it does not explicitly mention when not to use it or name alternatives (e.g., 'get_floor_price' for just the price or 'get_punk' for a specific punk by index), though the context is clear enough for basic differentiation.
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 the full burden of behavioral disclosure. It implies a read-only operation by stating 'Get' and describes the type of data returned, but doesn't mention potential limitations like rate limits, authentication needs, or data freshness. It adds some context about the tool's scope but lacks details on error conditions or response format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured in two sentences: the first enumerates the specific data points retrieved, and the second provides usage guidance. Every word contributes to understanding the tool's purpose and context without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no annotations, no output schema), the description is reasonably complete. It clearly explains what the tool does and when to use it, though it could be more comprehensive by detailing the return format or data sources to fully compensate for the lack of structured output information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description appropriately doesn't discuss parameters, focusing instead on the output semantics by listing the statistics returned, which adds value beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get') and resource ('global CryptoPunks market statistics'), listing concrete data points like floor price, total supply, and volume. It distinguishes itself from siblings by emphasizing it's for a 'market overview' rather than individual punk details or specific bid/offer operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool ('best endpoint for a market overview'), helping the agent understand its general purpose. However, it doesn't explicitly mention when not to use it or name specific alternatives among the many sibling tools, such as get_floor_price for just floor data or get_recent_sales for transaction history.
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 of behavioral disclosure. It successfully communicates key behavioral traits: the tool performs verification (implying read-only operation), is 'pure computation' (suggesting deterministic, stateless behavior), and 'no wallet required' (clarifying no authentication or external dependencies). It doesn't mention performance characteristics or error conditions, but covers the essential safety profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise with two sentences that each earn their place. The first sentence states the core purpose, and the second adds crucial behavioral context about computation requirements. There's zero wasted language or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a verification tool with no annotations and no output schema, the description provides good coverage of the essential context: what it does, what it requires, and its computational nature. It doesn't describe the return value format (true/false, error details), which would be helpful given the lack of output schema, but otherwise addresses the key aspects needed for proper tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with each parameter well-documented in the schema itself. The description doesn't add any additional parameter semantics beyond what's already in the schema descriptions. According to the scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('verify that a Merkle proof is valid') with the target resource ('for a given punk index and Merkle root'), distinguishing it from sibling tools like generate_merkle_proof or verify_batch_proofs. It explicitly mentions the computational nature and lack of wallet requirement, which adds important context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context about when to use this tool ('Pure computation, no wallet required'), indicating it's appropriate for offline verification scenarios. However, it doesn't explicitly state when NOT to use it or mention specific alternatives like verify_batch_proofs for batch operations, which would have earned a perfect score.
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 retrieves 'active' bids and specifies they are 'on-chain native bids', which adds useful context about data source and state. However, it lacks details on rate limits, permissions, or response format, leaving behavioral gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with zero waste: the first defines the purpose and scope, and the second provides critical differentiation from sibling tools. It is front-loaded with essential information and efficiently structured without unnecessary details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description provides good purpose and usage guidance but lacks behavioral details like response format or error handling. For a tool with no structured metadata, it is moderately complete but could benefit from more operational context to fully compensate for missing annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description does not add parameter semantics, but with no parameters, this is acceptable. A baseline of 4 is applied as per rules for 0 parameters, indicating the description adequately handles the absence of parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'all CryptoPunks with active native bids', specifying they are placed via the marketplace contract. It explicitly distinguishes from sibling tools by contrasting with 'get_collection_bids' for off-chain collection bids, making the purpose specific and differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool versus alternatives by stating 'use get_collection_bids for those' for off-chain collection bids. It clearly defines the context (on-chain native bids) and excludes off-chain alternatives, offering direct sibling tool references.
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 full burden and does well by disclosing key behaviors: it specifies the data source ('bids.cryptopunks.app'), describes the return format ('summarized bid metadata'), explains the rationale ('to avoid payload overflow'), and mentions the bid types ('EIP-712 signed bids that cover sets of punks'). It doesn't cover rate limits or authentication needs, but provides substantial context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by usage guidance and alternatives in two efficient sentences. Every sentence adds value without redundancy, making it appropriately sized and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 4 parameters, 50% schema coverage, no annotations, and no output schema, the description does well by clarifying the tool's scope, return format, and sibling differentiation. It could improve by addressing missing parameter details or authentication, but it's largely complete given the context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50%, and the description adds no specific parameter information beyond what the schema provides. It mentions filtering by 'bidder' and 'status' implicitly through the example of 'get_bid_proofs', but doesn't explain parameters like 'limit' or 'chain_id'. The baseline is 3 since the schema covers half the parameters adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get collection bids from bids.cryptopunks.app' specifies both the verb ('Get') and resource ('collection bids'), and it distinguishes from siblings by explaining this returns summarized metadata versus full details available through 'get_bid_proofs'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly provides when to use this tool ('Returns summarized bid metadata... to avoid payload overflow') and when to use an alternative ('For full punk lists and proofs, use get_bid_proofs with a specific bid UUID'), offering clear guidance on tool selection.
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 the return value format ('Returns value in ETH') and scope ('lowest active asking price'), but lacks details on potential errors, rate limits, or data freshness. It adequately covers basic behavior but misses advanced operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with zero waste: the first states purpose and return value, the second provides alternative usage. Front-loaded with essential information, no redundant or verbose phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and 0 parameters, the description is reasonably complete for a simple read operation. It covers purpose, return format, and sibling differentiation, but could benefit from mentioning data source or update frequency for full context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters and 100% schema coverage, the baseline is 4. The description adds no parameter-specific information, which is appropriate since there are no parameters to document.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get'), resource ('current floor price of CryptoPunks'), and scope ('lowest active asking price across the entire collection'), distinguishing it from sibling tool 'get_floor_punk' by specifying it returns only the ETH value rather than full details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides when to use this tool (to get the floor price in ETH) and when to use an alternative ('For full details on the floor punk itself, use get_floor_punk instead'), offering clear guidance on tool selection.
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 of behavioral disclosure. It effectively describes key behavioral traits: it's a read operation (implied by 'Get'), returns specific fields, and includes a critical reliability warning about the type field for non-human punks. However, it lacks details on error handling or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured: the first sentence states the purpose and outputs, and the second provides crucial usage guidance. Every sentence adds value with zero wasted words, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read tool with no annotations or output schema, the description is largely complete: it covers purpose, outputs, and critical limitations. However, it doesn't specify the return format or error conditions, leaving minor gaps in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents the single parameter (punk_index). The description adds no additional parameter semantics beyond what's in the schema, but the baseline score of 3 is appropriate given the high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get basic information about a specific CryptoPunk') and enumerates the exact data returned (owner address, type, attributes, asking price, bid, sale status). It distinguishes itself from sibling tools like get_punk_metadata and get_punk_traits by noting its limitations for non-human punks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance is provided on when to use this tool versus alternatives: the NOTE specifies that for accurate type data on non-human punks, use get_punk_metadata or get_punk_traits instead. This directly addresses sibling tool differentiation.
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 full burden and adds valuable behavioral context: it discloses a reliability issue (HTTP 500 failures) and suggests fallback strategies. It doesn't cover other aspects like rate limits or authentication needs, but provides critical operational guidance.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tightly constructed sentences with zero waste: the first states the purpose, the second provides critical operational guidance. Every word earns its place, and the important 'KNOWN ISSUE' is front-loaded for immediate visibility.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no annotations or output schema, the description provides excellent context about purpose, reliability concerns, and alternatives. It doesn't describe return format or pagination, but given the simplicity of the tool, this is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't waste space discussing nonexistent parameters, focusing instead on tool behavior and usage context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get all CryptoPunks currently listed for sale') with the exact resource, distinguishing it from siblings like get_market_stats (aggregate data) and get_floor_punk (cheapest listing only). It goes beyond a tautology by specifying the scope of 'all' listings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides when-not-to-use guidance by mentioning a known issue (HTTP 500 failures) and naming two specific alternatives (get_market_stats for aggregate data, get_floor_punk for cheapest listing). This gives clear context for tool selection among siblings.
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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