Server Quality Checklist

Tool Scores

• fetch_plain_textC
  2.9/5.0
  Behavior2/5

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

  No annotations were provided, placing the full disclosure burden on the description. While the cost disclosure ('Requires 0.005 USDC on Polygon') is a valuable and candid piece of behavioral context, it stands alone without details on payment flow (who pays, when), failure modes (insufficient balance), or network/dependency caveats. The description is far too sparse for a monetized tool carrying transaction risk.

  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 extremely compact at just 10 words, following a logical order of verb→object→qualifier→cost. Every word except 'ultra-lightweight' (which adds no measurable value) serves a purpose. This efficiency is a strong match for the tool's stated goal.

  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?

  Considering there is an output schema (return type is thus documented), a small parameter set, and a stated cost, the description could still do more. The tool introduces a non-trivial concept: a per-call cost on the Polygon network with a required payment transaction hash. The description does not explain the lifecycle: does the caller need prior approval? What happens if the payment hash is invalid or already used? This is core operational context that feels missing for a payment-gated tool.

  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?

  With 0% schema description coverage and no property descriptions in the JSON schema, the description needed to explain the parameters. The cost mention is helpful, implying why `payment_tx_hash` exists and why a URL alone is insufficient. However, the description does not specify expected format for the URL (http/https), what the payment hash represents (prior approved payment?), or how the client is expected to request/handle the 0.005 USDC fee, leaving meaningful gaps.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description uses a clear verb+resource structure: 'Extracts ultra-lightweight pure plain text from any web page.' It effectively separates this tool from obvious siblings like fetch_youtube_transcript and fetch_pdf_markdown by specifying text-from-web output. However, it does not clearly distinguish from the similarly-scoped sibling 'fetch_clean_web_content', which could cause confusion about which to choose.

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

  Usage Guidelines2/5

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

  No guidance is provided on when to use this tool over its close sibling 'fetch_clean_web_content'. The description fails to offer any exclusions, prerequisites, or situational triggers (e.g., 'use when you need raw text without HTML tags'). Users are left to guess whether this is for articles, dynamic pages, or simple sites.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• fetch_clean_web_contentB
  3.2/5.0
  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 and does disclose one genuinely non-obvious behavioral trait: 'Requires 0.01 USDC on Polygon' flags an external financial cost and chain dependency. However, it omits other behavioral details like how the payment_tx_hash is produced, what happens without payment, or rate/usage 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?

  Two crisp, front-loaded sentences of 16 words total. The primary capability lands in the first sentence, the critical cost dependency in the second. Zero filler.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a simple two-parameter tool with an output schema, much is covered, but the payment flow is a black hole: the sibling get_payment_info strongly suggests a payment-generation prerequisite that is never connected. An agent would be stuck knowing it must pay without knowing how to attach the transaction hash.

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

  Parameters2/5

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

  Schema description coverage is 0%, so the description needed to compensate entirely, yet it never names 'url' or 'payment_tx_hash'. The '0.01 USDC on Polygon' clause loosely implies the purpose of the payment parameter, but the agent is left guessing about the transaction-hash format or how to obtain it.

  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 verb phrase 'Fetches and transforms' paired with 'any webpage' and the output 'AI-ready clean Markdown' gives a specific verb+resource+result description. It indirectly distinguishes itself from siblings like fetch_youtube_transcript and fetch_pdf_markdown via 'any webpage,' though it never explicitly names alternatives as in the calibration high example.

  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?

  Usage context is only implied: 'any webpage' suggests this is the general-purpose fetcher among the sibling specializations, and the payment mention signals a real-world prerequisite. However, there are no explicit exclusions ('use fetch_youtube_transcript for videos') or references to sibling tools.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• fetch_youtube_transcriptA
  3.7/5.0
  Behavior3/5

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

  With no annotations, the description must disclose behavioral traits. It mentions the payment requirement ('0.02 USDC on Polygon'), which is a key constraint, but it does not explain how payment is processed or how the payment_tx_hash parameter is used, leaving ambiguity.

  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, front-loaded sentence that packs purpose and a key requirement efficiently. It contains no fluff and every phrase adds value.

  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?

  Despite having an output schema, the description is incomplete for a paid tool. It does not explain the payment mechanism, how to provide a transaction hash, or what happens without payment, leaving critical usage details missing.

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

  Parameters2/5

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

  Schema description coverage is 0%, so the description should compensate for explaining parameters. It only hints at the URL via 'any YouTube video' and mentions payment cost, but it does not clarify the 'url', 'language', or 'payment_tx_hash' parameters, their formats, or defaults.

  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 extracts full transcript and timestamps from any YouTube video into Markdown format. It specifies the resource (YouTube video), the action (extract transcript), and the output format, distinguishing it from sibling content-fetch tools.

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

  Usage Guidelines4/5

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

  The description implies usage for YouTube transcript extraction, clearly different from siblings that handle web content, PDFs, or plain text. However, it does not explicitly state alternatives or when not to use this tool, only that payment is required.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• get_payment_infoA
  4/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the burden. It states the tool 'returns' information, implying read-only behavior, but does not disclose potential errors, auth requirements, or any side effects. The phrase 'for tools in this server' adds a scoping dimension, yet it lacks details on output structure (though output schema covers that). This is minimal but not misleading, so a middle score is appropriate.

  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, front-loaded sentence that conveys the core functionality without redundancy. Every word earns its place; it is 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 low complexity (no params, read-only getter) and the presence of an output schema, the description is largely complete. It covers the purpose and scoping but could benefit from a note on when to invoke it (e.g., before using other tools) or any assumptions about network connectivity. Nevertheless, it is sufficient for a simple tool, earning a high score.

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

  Parameters4/5

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

  The tool has zero parameters, so the description needs no parameter explanations. Per the rubric, baseline for 0 params is 4. The description aligns with the empty schema, and no additional meaning is required.

  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 returns specific information: 'Polygon Web3 micropayment pricing and recipient details for tools in this server.' This is a specific verb+resource and distinguishes itself from sibling fetch tools which handle content types like web content or transcripts. The purpose is unambiguous.

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

  Usage Guidelines3/5

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

  The description implies usage (when you need payment info for tools), but it does not explicitly state when to call it or whether there are any prerequisites or alternatives. Since it is the only payment-related tool among siblings, the context is clear, but explicit 'use this when...' guidance is missing, giving a baseline adequate score.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• fetch_pdf_markdownA
  4.1/5.0
  Behavior4/5

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

  With no annotations, the description carries the burden of disclosing behavioral traits. It adds a unique operational detail: 'Requires 0.05 USDC on Polygon,' which implies payment/authentication prerequisites not present in the schema. However, it omits other potential side effects like network calls or failure modes, so it's not a 5.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is extremely concise—two short sentences. It front-loads the primary function in the first sentence and adds crucial cost information in the second. Every word earns its place, with no fluff 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 simple fetch-and-convert tool, the description covers the essentials: input (PDF), output (Markdown), and a key prerequisite (payment). An output schema exists, so return details aren't needed. It lacks a bit of detail about error cases or what happens without payment, but overall it's sufficiently complete.

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

  Parameters2/5

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

  Schema coverage is 0%, so the description should compensate by explaining the parameters. It mentions the 0.05 USDC cost, which hints at the purpose of payment_tx_hash, but it never explicitly ties the cost to that parameter or describes the url parameter. This indirect and incomplete guidance warrants a low score.

  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 uses a specific verb ('Extracts') and resource ('PDF research papers and reports') with output format ('structured Markdown'). It clearly distinguishes itself from sibling tools like fetch_youtube_transcript or fetch_clean_web_content, which target different content types.

  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 PDF-only usage and mentions a payment requirement, giving clear context. Though it doesn't explicitly list alternatives or exclusions, the sibling names and the explicit 'PDF' qualifier make the appropriate use case apparent.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.