Server Quality Checklist

Tool Scores

• patternfetch_analogsA
  4/5.0
  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 and discloses the behavioral nature: it returns historical distribution data, explicitly states it is not a prediction or advice, and notes past performance does not guarantee future results. This is transparent for a read-only analytical tool.

  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: three sentences, no redundant text. The key action and output are front-loaded, and every sentence contributes essential information (purpose, usage guidelines, limitations).

  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?

  The description adequately explains the return value (FULL distribution with specific metrics) but fails to explain all input parameters, especially ticker and timeframe. Given that there is no output schema and schema coverage is 0%, the description should provide more parameter context to be 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 description coverage is 0%, and the description only indirectly hints at 'window' and 'horizon' without explaining their meaning or format. The required parameters 'ticker' and 'timeframe' are not mentioned at all, leaving their semantics entirely to the schema which lacks descriptions.

  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 finds historical windows resembling current price action and returns a distribution of forward outcomes. It uses specific verbs and lists exact return fields (win-rate, median, min, max, n), and distinguishes itself from siblings by explicitly stating it is not a prediction or backtest.

  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 states when to use ('agent wants historical context for a setup') and what not to use ('NOT a prediction, NOT a backtest'). It provides clear context for appropriate usage, though it does not directly reference sibling tools as alternatives.

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

• patternfetch_briefA
  4.1/5.0
  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 discloses that output is 'impersonal market data, NOT investment advice,' which is critical for safe use. It also notes token-saving and hallucination avoidance. It does not detail rate limits, required permissions, or data freshness, but these are acceptable gaps for a read-like tool.

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

  Conciseness4/5

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

  The description is well-structured with a clear opening statement, a bullet-like list of outputs, and usage sections. It is informative without being verbose. Minor redundancy (e.g., 'token-compact' and 'saves tokens') could be trimmed, but overall it earns its length.

  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 three parameters, no output schema, and no annotations, the description provides a solid overview of the tool's purpose, return content, and usage boundaries. It lacks details on error handling, pagination, or data latency, but covers essentials well for a tool of moderate complexity.

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

  Parameters3/5

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

  The schema has 0% parameter descriptions, so the description must compensate. It explains 'ticker' and 'timeframe' via example and context ('crypto ticker + timeframe'), but the optional 'limit' parameter is not mentioned at all. Partial coverage; more detail on parameter format or defaults would improve clarity.

  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 it retrieves a 'token-compact market-state brief' with specific outputs (candles, patterns, support/resistance, etc.). It identifies the resource (crypto ticker + timeframe) and the action (get). However, it does not explicitly differentiate from sibling tools like 'patternfetch_analogs' or 'patternfetch_delta', missing a chance to clarify unique positioning.

  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' and 'WHEN NOT' guidance, specifying ideal use (saving tokens, avoiding hallucination) and contraindications (order execution, portfolio advice, non-crypto). It also includes a concrete example, making it extremely clear for an agent when to select this tool.

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

• patternfetch_capabilitiesA
  4.1/5.0
  Behavior3/5

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

  With no annotations, the description carries full burden. It says 'list', implying a read-only operation, but doesn't explicitly disclose behavioral traits like auth needs or rate limits. For a simple listing tool, this is minimally adequate.

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

  Conciseness5/5

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

  Single sentence, front-loaded with key information. No wasted words.

  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?

  Given the tool has no parameters and no output schema, the description sufficiently explains what the tool returns for its intended 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?

  Schema coverage is 100% with 0 parameters, baseline score 4. Description adds no parameter info because none exist.

  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 lists supported assets, timeframes, endpoints, and limits for patternfetch. The verb 'list' and specific resource differentiate it from sibling tools like patternfetch_analogs or patternfetch_delta.

  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 use for retrieving capabilities but provides no explicit guidance on when to use this tool versus alternatives or when not to use it.

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

• patternfetch_deltaA
  4.2/5.0
  Behavior4/5

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

  With no annotations, description discloses key behaviors: returns changed=false when nothing changed, provides impersonal data not advice, and focuses on minimal tokens. Implies statefulness (requires previous brief) without fully detailing prerequisites 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?

  Two sentences plus a WHEN clause; front-loaded with purpose, efficient with no fluff. Every sentence adds value: what, when, result on no change, disclaimer.

  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?

  Adequate for a delta tool: explains purpose, usage, return flag, and uses sibling names for context. Could be more explicit about state dependency and output format, but given 3 param inputs and no output schema, it covers essential aspects.

  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 0%, so description must compensate. It explains ticker and timeframe as 'ticker+timeframe' but omits the optional 'limit' parameter. Adds meaning to required params but not complete 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?

  Description clearly states verb 'Get only what CHANGED' and resource 'since your last brief for a ticker+timeframe', listing specific change types like trend flips and RSI-state changes. It distinguishes from sibling tools (e.g., patternfetch_brief, patternfetch_analogs) by focusing on delta updates.

  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?

  Explicitly states when to use: 'when an agent polls the same market repeatedly and wants minimal tokens'. Implies not for first-time queries, and sibling names provide context for alternatives, but no explicit exclusions.

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