Server Quality Checklist

Tool Scores

• jackpotkeywords_recommendA
  3.7/5.0
  Behavior4/5

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

  With no annotations, the description discloses important behavioral traits: cost structure ($0.10 flat), automatic refunds on failure, latency range (60-180 seconds), and reliance on real data. It does not cover authentication, rate limits, or error handling, but the provided details are valuable.

  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?

  Four sentences, each serving a distinct purpose: core function, data source, pricing, and latency. Front-loaded with the main verb and resource. No unnecessary 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 5 parameters with full schema descriptions, no output schema, and no annotations, the description covers the tool's purpose and key execution details (cost, latency). However, it lacks information about the return format or how agents should handle the output, which is a gap for autonomous use.

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

  Parameters3/5

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

  Schema coverage is 100%, so baseline is 3. The description does not add extra meaning beyond the schema; it lists composite score components but does not explain how parameters like 'budget' or 'location' influence results. No additional parameter insights.

  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?

  Description clearly states the tool runs a full keyword research pipeline, returns ranked recommendations by Jackpot Score, specifies the data source (Google Ads Keyword Planner), and mentions key output criteria. This distinguishes it from sibling tools like the deep version.

  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 mentions cost and latency but provides no explicit guidance on when to use this tool vs siblings (e.g., jackpotkeywords_recommend_deep) or alternatives. It does not state prerequisites or context for optimal use.

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

• jackpotkeywords_aeo_scanA
  4.1/5.0
  Behavior4/5

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

  With no annotations, the description effectively discloses key behaviors: costs $1.00 per scan, automatic refund on failure, latency 30–120 seconds, and details the query process. It does not mention auth or rate limits but covers essential operation traits.

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

  Conciseness5/5

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

  The description is concise at three sentences, front-loaded with the core purpose, then details, then cost/latency. Every sentence adds value 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?

  The description covers the outcome per query (cited, mentioned, absent, top sources) despite no output schema. However, it lacks explicit return value structure or format, and could mention whether results are returned as JSON or text. Still sufficient for a paid tool.

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

  Parameters5/5

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

  Schema coverage is 100%, but the description adds significant value for productContext: explains internal extraction as default, cost implication ($1.00 flat), and when to pre-pass it (only if already called /v1/recommend). This goes beyond the schema's minimal 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 action 'Run an AI-visibility scan for a product URL' and specifies it involves asking 10 buyer-intent queries against Gemini's grounded search. It distinguishes from sibling tools (audit, credit balance, recommend) by focusing on a specific scan functionality.

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

  Usage Guidelines2/5

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

  The description does not provide guidance on when to use this tool versus alternatives like jackpotkeywords_audit or jackpotkeywords_recommend. It only describes what it does without contextual comparison, leaving the agent to infer usage from the name alone.

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

• jackpotkeywords_credit_balanceA
  4.2/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the full burden. It discloses the tool returns the credit balance and implies it is a read operation. It does not detail any authentication requirements, rate limits, or error states, but for a simple balance check this is acceptable.

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

  Conciseness5/5

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

  The description is two sentences with no wasted words. The first sentence states the purpose, the second gives usage guidance. Information is front-loaded and efficient.

  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 read-only tool with no parameters and no output schema, the description covers the essential aspects: what it does, that it requires authentication (implied by 'authenticated account'), and when to use it. It could mention the expected output format, but it is complete enough for the use case.

  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 zero parameters, so schema coverage is 100%. With no parameters, the description does not need to add param semantics. The baseline for 0 parameters is 4, and the description adds context about the return value.

  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 the current credit balance for the authenticated account, using specific verbs and resource. It distinguishes itself from sibling tools by mentioning it should be used before calls like /recommend and /aeo-scan.

  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 explicitly instructs using this tool before /recommend or /aeo-scan to verify credit availability, providing clear context. However, it does not mention when not to use it or list alternatives beyond the implied prerequisite relationship.

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

• jackpotkeywords_auditA
  4.7/5.0
  Behavior5/5

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

  With no annotations, the description fully discloses behavioral traits: cost, refund policy on failure, latency (20-60s), scope of crawling (primary + up to 8 secondary pages), and what returns (checks, issues, gaps, recommendations).

  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?

  Very concise, front-loaded with purpose, structured with bullet-worthy details (cost, latency, refund). Every sentence adds essential information without redundancy.

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

  Completeness5/5

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

  Complete given the tool's simplicity (1 param) and presence of siblings. Covers purpose, exclusions, cost, latency, failure behavior, and output components. No output schema, but description sufficiently describes returns.

  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 coverage is 100% for the single 'url' parameter, providing baseline of 3. Description adds minimal value beyond the schema: gives examples of acceptable URL formats but does not add new semantic constraints.

  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 'Run an SEO audit on a URL' and lists specific categories checked (technical, content, etc.) and outputs (scored checks, issues, recommendations). It explicitly differentiates from sibling jackpotkeywords_aeo_scan by noting that AEO data is intentionally omitted.

  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 states when to use (for SEO audit) and when not to (for AI-visibility, directing to jackpotkeywords_aeo_scan). Also mentions cost ($0.50), latency, and automatic refund on failure, providing clear decision-making context.

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

• jackpotkeywords_recommend_deepA
  4.8/5.0
  Behavior5/5

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

  No annotations exist, so the description carries full burden. It fully discloses: cost ($0.30), refund policy on failure, latency (75-200 seconds), and suggests generous timeouts. Also mentions parallel competitor discovery and what additional data is returned. No contradictions.

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

  Conciseness5/5

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

  The description is a single, well-structured paragraph. Every sentence serves a purpose: purpose, differentiation, usage guidance, cost, refund, latency, timeout. No redundancy or fluff. Front-loaded with the core action.

  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 5 parameters (all described in schema) and no output schema, the description explains what return values include (cluster, category, competitor-brand aggregates) but lacks detailed format. However, it covers cost, latency, refund policy, and use-case, making it fairly complete for the complexity.

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

  Parameters4/5

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

  Schema description coverage is 100%, so baseline is 3. The description adds value by stating 'Same inputs as jackpotkeywords_recommend' and clarifying that the limit does not affect clusters/categories/competitors, which is not in the schema. This extra context elevates the 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 starts with 'Run the deep keyword research pipeline for a product' which clearly states the verb and resource. It explicitly distinguishes from the sibling tool jackpotkeywords_recommend by noting additional outputs (clusters, categories, competitor aggregates), making the tool's unique scope clear.

  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 gives explicit guidance: 'Use this when you need to see WHICH keyword clusters matter and WHO else is ranking, in one call.' It implies that for simpler needs, the sibling recommend tool is appropriate. Also provides critical usage details (cost, latency, timeout advice).

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