Server Quality Checklist

Tool Scores

• quantdata_weis_waveA
  4.5/5.0
  Behavior4/5

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

  Annotations declare readOnlyHint and openWorldHint, but the description adds meaningful behavioral context: it requires real exchange volume (spot FX has none), notes that two events came out REVERSED against tradition, and warns that session='full' can return 422 NO_EXTENDED_VOLUME and to obey retryable. This exceeds the annotation coverage without contradiction.

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

  Conciseness4/5

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

  The description is four sentences, each earning its place: definition, measured outcomes, FX/volume caveat, and session recommendation. It is dense but not bloated; all information is relevant. Slightly longer than necessary, but the structure is logical and front-loaded with the core purpose.

  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?

  Without an output schema, the description must convey what is returned, and it does: waves with summed volume, the five events, and their win rates. It also covers data requirements, error handling, and session semantics. Missing is a precise output format or example, but for the complexity, it is sufficiently complete.

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

  Parameters4/5

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

  Schema covers both parameters 100%, so baseline is 3. The description adds value by advising to use CME currency futures instead of spot FX due to volume requirements (relevant for symbol selection) and by recommending the session parameter based on the reference-rate window, which is a meaningful use-case nuance beyond the schema's technical detail.

  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 defines the tool as a Weis Wave volume-price structure analyzer, grouping price into waves and summing volume, plus identifying five classical volume-price events with measured win rates. It explicitly answers the question 'is there volume behind this move,' and is distinct from siblings like day_type, max_pain, and gamma.

  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 states when to use this tool ('Answers is there volume behind this move'), provides an explicit alternative for spot FX ('use CME currency futures (6E=F) instead'), and gives session selection guidance ('full' to match published rates, default 'rth' for regular-session reads). This goes beyond simple context to explicit when-not and alternatives.

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

• quantdata_max_painA
  4.7/5.0
  Behavior5/5

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

  The description discloses key behavioral traits beyond the readOnly/openWorld annotations: reproducibility due to 'pure arithmetic', deterministic results ('anyone with the same chain gets the same number'), error conditions for cash-settled indices, and the fact that results describe prior-session positioning. This adds significant value over the bare 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 a single dense paragraph, but every sentence adds value: it defines the metric, explains the computational invariant, lists additional return fields, justifies the 45-day window, enforces the universe restriction, and notes data timing. No fluff or redundancy; sentence order is logical and front-loaded with the core purpose.

  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 moderate complexity and absence of an output schema, the description provides sufficient context: it names return components (put/call ratio, heaviest strikes, as_of, spot_date), explains per-expiration semantics, states the 45-day horizon, and covers error cases. This is fully actionable for an agent without further structure.

  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%, and both parameters have clear descriptions in the schema (symbol and distribution). The tool description adds no new parameter-level details beyond the schema, e.g., it does not explain that the distribution parameter corresponds to the distributionally heavy output mentioned. Thus, 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 computes 'Options max pain per expiration' with a specific method (from open interest alone), and distinguishes itself from siblings like quantdata_gamma and quantdata_weis_wave by emphasizing it uses no pricing model or volatility assumption. It also specifies unique outputs (put/call ratio, heaviest strikes) and a specific scope (US stocks/ETFs), making it unambiguous.

  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 usage guidelines: 'Returns every expiration inside 45 days rather than picking one' and 'US listed stocks and ETFs only', with direct alternatives for excluded assets ('use SPY, QQQ, IWM'). It also gives behavioral context about data freshness ('open interest settles overnight'), helping the agent decide when to use this tool.

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

• quantdata_request_free_api_keyA
  4.7/5.0
  Behavior5/5

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

  The description discloses several behavioral traits beyond the annotations: the key is delivered only to the inbox and is never returned in the tool result, there is a shared daily quota of 10 successful calls, and a true marketing_opt_in stays pending until the recipient replies SUBSCRIBE. This adds substantial context that annotations (readOnlyHint=false, openWorldHint=true) do not convey.

  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 well-structured and front-loaded with the core action. Every sentence adds value: no account required, coverage of data tools, key delivery mechanism, consent guidance, and pending status. It is appropriately detailed 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 thoroughly covers prerequisites, side effects, quota, and parameter handling. However, it does not explicitly state what the tool result contains (only that the key is not returned). Given there is no output schema, a brief mention of the expected result would improve completeness, but it is not a major gap.

  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 enriches parameter meaning. For email, it implies the user's consent is needed. For marketing_opt_in, it adds crucial semantics: defaults to false, not required, only set true with explicit consent, and pending behavior. This is significantly more than the schema's brief 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 starts with a specific verb and resource: 'Send a free qd_ API key to an email address.' It clearly distinguishes this from sibling market-data tools by stating the key covers all four market-data tools and that no account or payment is required. The purpose is unambiguous 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 Guidelines4/5

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

  The description provides practical usage guidance: 'Ask the user for the email address before calling' and explicitly instructs when to set marketing_opt_in to true ('only when the email owner explicitly asks'). It also clarifies that marketing_opt_in defaults to false and is not required. While it does not explicitly name alternatives, the context of siblings makes the appropriate scenario clear.

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

• quantdata_gammaA
  4.8/5.0
  Behavior5/5

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

  Beyond the readOnlyHint and openWorldHint annotations, the description discloses critical behavioral details: the Black-Scholes estimation assumptions (zero rate, zero dividend, implied volatility from EOD), the dealer convention (long calls, short puts), the null flip handling (flip_status values and their meaning), and data freshness ('Reads the prior session's settled open interest'). This goes far beyond annotations.

  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 dense and every sentence adds distinct value, but it is somewhat lengthy for a single tool. It is front-loaded with the core purpose and then unfolds limitations and usage nuance. No waste, but the length itself slightly reduces conciseness.

  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?

  Despite lacking an output schema, the description covers the key output concepts (net/gross GEX, flip status, as_of/spot_date), error conditions, and limitations. It is comprehensive for a tool of moderate complexity, giving the agent sufficient context to set expectations and invoke 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 input schema already documents both parameters (symbol and by_strike) with clear descriptions, achieving 100% coverage. The description adds extra value by explaining the by_strike parameter's size implications ('Large; only request it when the user wants strike detail') and reinforcing the symbol scope ('US listed stocks and ETFs only'). This is a meaningful enhancement over schema alone, though not exhaustive.

  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 phrase ('Estimated dealer gamma exposure') and clearly defines the resource ('US listed stock or ETF') with concrete outputs (net/gross GEX, zero gamma flip level, heaviest strikes). It explicitly contrasts itself with sibling tool max pain, making differentiation unambiguous.

  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 usage boundaries: 'Unlike max pain this is a Black-Scholes ESTIMATE', states exclusions ('cash-settled index options (SPX, NDX, RUT, VIX) return an error — use SPY, QQQ, IWM instead'), and warns about intraday limitations ('cannot update intraday'). It also advises when to request by_strike ('only request it when the user wants strike detail').

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

• quantdata_day_typeA
  4.9/5.0
  Behavior5/5

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

  The description adds substantial behavior beyond the readOnlyHint and openWorldHint annotations: it explains that the output is a calibrated distribution, based on S&P 500 futures 5-minute bars, descriptive rather than predictive, and provisional under certain bar counts. It also discloses that the Asia session is explicitly unvalidated.

  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 dense but every sentence adds value: it front-loads the core purpose, then covers output interpretation, caveats, and prerequisites without fluff. It is appropriately sized given the tool's complexity and safety checks.

  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?

  Despite having no output schema, the description fully explains what the tool returns (a calibrated five-class distribution plus descriptive statistics about past sessions), and it covers important context like the model training data and when results are provisional. The complexity is well handled with no major 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?

  The schema already covers both parameters thoroughly, so the baseline is 3. The description adds meaningful context by explaining that the default US session is the only window the model was measured on, and that the 'asia' session is accepted only for 24-hour instruments and is explicitly unvalidated.

  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 provides day-type probabilities for the trading session in progress, naming the five specific classes and the underlying model. It directly answers 'what kind of day is this so far', distinguishing it from the sibling tools which address other quantdata metrics.

  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?

  It gives explicit prerequisites: check session_is_live before reading 'today', and fewer than 18 bars means the distribution is provisional. It also clearly warns against treating the output as a forecast or recommendation, and explains when to omit or pass the 'session' parameter, including the unvalidated Asia session.

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