Server Quality Checklist

Tool Scores

• commonalityA
  4.4/5.0
  Behavior4/5

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

  Annotations already mark readOnly and openWorld; the description adds specifics about deterministic output, verdict values, and survivorship/multiple-comparisons framing. It does not contradict annotations and provides extra behavioral detail.

  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 compact sentences that convey purpose, output format, exclusion, and follow-up guidance without fluff. Each clause adds value and the description is well front-loaded.

  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 explains the return value composition (per-field verdicts and framing) and disambiguates from prediction tools. There is slight ambiguity around 'framing' but overall it is complete for a read-only tool with no output schema.

  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 already fully describes the moments parameter (array of {symbol, at}, min 2, lowercase perp, RFC3339). The description adds no additional parameter-level meaning beyond the schema, so 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 uses the specific verb 'return' and defines the resource as a deterministic intersection with explicit verdict types (agree, partial, disagree, quiet, absent). It also clearly distinguishes from similarity search, differentiating it from sibling tools.

  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 'Never similarity search' as a when-not, and provides actionable follow-up advice to test AGREE verdicts with base_rate. This gives clear context for when to use this tool versus alternatives.

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

• interpret_proseA
  4.5/5.0
  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 result is labeled proposal:true, it is never executed here, output includes unsupported[] stand-ins and clarify notices, it requires the research:interpret scope, and each call spends provider money. This goes well beyond the readOnly and openWorld hints, and no contradiction with annotations exists.

  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 four sentences, each serving a distinct purpose: purpose, proposal nature, workflow with run_scan, and auth/cost. It is front-loaded with the core function and contains no filler or redundant information.

  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 there is no output schema, the description compensates by explaining the output (proposal:true, unsupported[] stand-ins, clarify notices), the workflow (show to user, then run_scan), and important operational details (scope and cost). It covers all essential aspects for an agent to correctly select and invoke this 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?

  Schema coverage is 100%, with both language and time_zone already fully described in the input schema. The description adds general context (e.g., 'plain-language market question') but no parameter-specific details or new meaning beyond the schema, so 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 function: 'Turn a plain-language market question into a PROPOSED research_query.v2 document.' It emphasizes that the result is a proposal, never executed, which distinguishes it from the sibling run_scan tool that executes scans. The verb 'Turn' and specific output resource make the purpose explicit and 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 gives clear usage context: it says to show the proposal to the user and then call run_scan to execute, framing this tool as the first step in a two-step workflow. It also notes the required scope and metering. However, it does not explicitly state when not to use the tool or provide alternative scenarios beyond run_scan, so it falls short of a 5.

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

• next_pageA
  4.5/5.0
  Behavior5/5

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

  Annotations indicate readOnly and openWorld hints, but the description adds substantial behavioral context: cursor handling, revision scoping, ETag details, pricing/free nature, and independence of counts and summaries. This goes well beyond the 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 but each sentence contributes important operational detail. It is front-loaded with the core action and then presents necessary edge-case handling. Length is appropriate given the complexity, though it could be slightly more concise.

  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?

  With no output schema, the description compensates by explaining the counts_by_symbol projection, full_counts behavior, and independence of page rows. It covers critical complexities like revision changes and ETags, making the tool sufficiently understandable 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% with detailed parameter descriptions. The tool description mostly reinforces these (e.g., 'SAME document', 'Never construct cursors') without adding new parameter-level meaning beyond what the schema already 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 tool's purpose: to continue a prior run_scan by re-sending the same document with the opaque cursor. It is specific and distinguishes itself from the sibling run_scan tool.

  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 explicitly describes when to use this tool (after a prior run_scan) and provides concrete guidance, such as restarting from page 1 if X-Dataset-Revision changed, and never constructing cursors.

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

• base_rateA
  4.7/5.0
  Behavior5/5

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

  The description significantly expands on the annotations (readOnlyHint=true, openWorldHint=true) by disclosing behavior around missing values ('never coerced to false or zero'), determinism ('Deterministic and free, including reruns'), error code expectations ('expect the 422 contract code verbatim'), and output echo. It also describes the output structure (base_rate_result.v1 fields), which is especially valuable given no output schema is present.

  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 of about 7 sentences, each delivering distinct value: purpose, output fields, exclusions, missing-data handling, guarantees, error behavior, and the echo. It is front-loaded with the core purpose and avoids redundancy with the schema.

  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?

  With no output schema, the description fully compensates by listing the exact result fields (predicate_true_buckets, predicate_false_buckets, eligible_buckets, absent_or_ineligible_buckets, true prevalence) and global/per-symbol breakdown. It covers edge cases (missing values, grammar errors, determinism) and the echo behavior, making the tool's behavior completely understandable without needing to guess.

  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%, so baseline is 3. The description adds meaningful parameter context beyond the schema by stating that 'field, operator and value must be grammar-valid (see list_features)' and warning about the 422 error code for invalid grammar. It also clarifies the meaning of 'eligible' buckets. These additions go beyond the schema's property descriptions, justifying a 4.

  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 measures how often a single condition is true over eligible symbol-minute buckets, with a specific verb ('measure') and resource scope. It distinguishes itself from sibling tools by noting it is not a count of false-to-true episodes and computes no forward outcomes, differentiating it from tools like run_scan that may analyze outcome episodes.

  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 gives clear context for use: 'SINGLE stated condition' and 'eligible symbol-minute buckets,' and explicitly says it is not for episode counts or forward outcomes. It does not name an alternative sibling directly, but the exclusions are strong enough to guide when not to use it, and it references list_features for grammar validation. However, it lacks an explicit 'use X instead' statement, so it doesn't quite reach a 5.

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

• list_instrumentsA
  4.7/5.0
  Behavior5/5

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

  Beyond readOnlyHint and openWorldHint, it reveals determinism, cost-free access, authoritative derivation, excluded symbol-day visibility, and the Binance perpetual mapping for NVDAUSDT/QQQUSDT. This is far richer than annotations alone, with no 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?

  Dense but efficient; every sentence contributes value. It is somewhat long due to explaining three modes and an overflow warning, but that complexity justifies the length.

  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?

  With no output schema, the description fully explains return modes, content of each mode, size constraints, determinism, cost, and edge cases. It provides all necessary context for an agent to invoke and interpret results correctly.

  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%, yet the description adds substantial meaning: default output fields, per-symbol record contents, lowercase convention, string-array repair, and ETag projection scoping. This goes well beyond the schema's own property 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 returns the authoritative feature-store universe from complete manifests, with distinct modes for summary, specific symbols, and full bytes. This specific verb+resource clearly distinguishes it from siblings like list_features.

  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?

  Provides explicit mode selection guidance: default compact summary avoids context overflow, symbols for specific canonical records, full for verbatim bytes. However, it does not explicitly name alternative tools for when not to use this one, so a small gap remains.

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

• snapshot_atA
  4.7/5.0
  Behavior5/5

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

  Beyond the readOnlyHint and openWorldHint annotations, the description discloses that the operation is 'never a scan (not credit-metered)', explains tier-based access restrictions (past-minute reads are Pro, returning 403 with an upgrade URL), and notes that results are canonical bytes. This adds meaningful behavioral context beyond what annotations provide.

  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?

  Although the description is longer than typical, every sentence adds actionable information: the read-only/credit distinction, the connection to run_scan, the deflation warning, and the tier/error details. The TIERS section is clearly separated and front-loaded with the core purpose in the first sentence, so the structure is efficient and purposeful.

  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?

  With no output schema, the description compensates by listing the exact contents of the returned snapshot (feature values, window aggregates, fired rulebook ids) and describing the canonical-byte format. It also covers the access model (free/present vs. paid/past), error behavior, and its relationship to run_scan, making it complete for an agent to decide when and how to invoke it.

  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 explains both parameters (symbol as lowercase perp, at as RFC3339 datetime floored to grid bucket). The description does not add parameter-specific semantics beyond restating the 'as-of' grid-bucket concept, which is already implied by the schema. 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 uses a specific verb ('Read') and resource ('engine registry AS-OF the grid bucket containing a moment'), and states the exact contents returned (every feature value, window aggregates, fired rulebook ids). It also explicitly distinguishes itself from run_scan, which is the primary sibling, by noting it is a read, never a scan.

  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 when-to-use guidance: 'Use it to turn one observed moment into candidate clauses, then run_scan to find every other time it looked like that.' It also provides selection discipline for choosing moments and clear tier-based guidance on when to query present vs. past minutes, including the 403 GRANT_REQUIRED behavior on free accounts.

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

• get_reportA
  4.8/5.0
  Behavior5/5

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

  The description goes beyond the readOnlyHint and openWorldHint annotations by disclosing that invalid or withdrawn reports carry correction and successor metadata and must not be presented as healthy. It also clarifies the return content (count, revision, integrity status) and the nature of the result pinned at publish time. This provides rich behavioral context without contradicting 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 conditional behavior (omit/provide) and packed with essential information. No filler or repetition. It is concise despite covering both modes and edge cases.

  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?

  The description fully covers the tool's behavior given the lack of an output schema: it describes what is returned in list mode (count, revision, integrity status) and fetch mode (title, author, definition, result), and warns about invalid/withdrawn reports. With only one optional parameter and good annotations, this is complete for an AI agent to select and use correctly.

  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?

  The input schema already has 100% coverage of the single parameter, but the description adds significant meaning: it explains that omitting hash8 lists reports, while providing it fetches one and details the returned fields (title, author, definition, result). This goes beyond the schema's 'Omit to list public reports' by fully explaining the dual 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 tool's purpose: it lists published archive and record reports when hash8 is omitted, and fetches a single report by an 8-hex canonical hash. It uses specific verbs (list, fetch) and identifies the resource (reports). The description also distinguishes from siblings like list_features and list_instruments by scoping to reports with integrity status.

  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 mode-specific instructions: omit hash8 to list reports, provide hash8 to fetch one. This effectively guides when to use each mode. However, it does not explicitly name alternatives or state when not to use the tool, though the sibling tool run_scan is indirectly referenced via 're-submittable to run_scan'.

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

• list_featuresA
  4.9/5.0
  Behavior5/5

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

  The annotations declare readOnlyHint and openWorldHint, but the description adds the crucial ETag-revalidation behavior, explaining that additive feature ids become visible to long-running agents. This goes beyond the annotations and provides useful 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?

  Three sentences, each with a distinct purpose: enumerating contents, instructing to call first, and explaining caching behavior. No filler words; all sentences contribute essential information.

  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 thoroughly enumerates what the response contains, including feature ids, dtypes, ranges, operators, window aggregates, sequence rules, limits, sort fields, and error-code lists. It also justifies the 'call first' guidance and caching, making it fully self-contained for a read-only registry tool.

  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 baseline is 4. The description does not need to elaborate on parameters; instead, it focuses on the richness of the response. It conceptually mentions 'pinned feature_version' but does not treat it as an input parameter.

  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 closed registry for the pinned feature_version, enumerating the specific contents (feature ids, dtypes, ranges, operators, etc.). This distinguishes it from sibling tools like list_instruments, which likely return a different registry.

  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 instructs 'Call this FIRST' and explains why: using only ids from this registry prevents inventing field names. This provides clear guidance on when to use it, though it doesn't name alternative tools explicitly, the context implies it is the foundational reference.

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

• run_cohortA
  4.9/5.0
  Behavior5/5

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

  Even though annotations declare readOnlyHint=true, the description adds substantial behavioral detail: exact byte output, absence of ratios/lift/averages, completeness rule, cache behavior with X-Research-Cache header, and mandatory caveats in the result. It also discloses error conditions like OUTCOME_IN_PREDICATE and the contract to echo document/key. No contradiction with 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 long but every sentence adds critical operational information, from return format to error handling to caching. It is front-loaded with the core purpose, then systematically adds caveats. The density is justified by the tool's complexity, and no sentence feels redundant.

  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?

  With no output schema, the description compensates by detailing the cohort_result.v2 bytes, time windows, MFE/MAE summary, and what is absent. It also covers error scenarios, contract requirements, and cache semantics, making the tool fully understandable. The description is complete given the tool's 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 coverage is 100%, so baseline is 3. The description enriches the document parameter by requiring WHERE-ONLY and explaining predicate-complement semantics, and clarifies if_none_match by describing ETag revalidation and 304 responses. Full_counts is not further elaborated in the description, but the schema description is already sufficient, so the added value is above baseline but not maximal.

  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 it executes a research_query.v2 document as a predicate-complement comparison, returning canonical cohort_result.v2 bytes with treatment vs baseline side-by-side. It explicitly names the alternative run_scan for sequence documents, distinguishing it from that sibling. The verb-resource-object structure is explicit and 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?

  Explicitly instructs to use run_scan for sequence documents (WHERE-ONLY refusal with 422), provides a when-not for covariate matching, and warns against outcome field filtering. It also describes cache revalidation semantics for if_none_match, giving clear decision boundaries for when to invoke this tool.

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

• run_scanA
  4.9/5.0
  Behavior5/5

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

  The description richly discloses behavioral traits beyond the readOnlyHint and openWorldHint annotations: caching and 304 revalidation behavior, absence of horizons in outcomes_summary, context size overflow risks, zero-count omission semantics, contract to echo document/key, and the OUTCOME_IN_PREDICATE error. No contradiction with annotations; in fact it elaborates on the read-only, cache-friendly nature.

  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 front-loaded, starting with the core purpose before diving into caveats. While lengthy, every sentence adds value for a complex tool. A slight structural improvement could be collapsing some repeated warnings, but it is well-organized and not redundant.

  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?

  Without an output schema, the description fully explains return values, the meaning of outcomes_summary across horizons, the role of page rows as examples, and the caveat about absent horizons. It also covers size limits, pagination, and zero-count handling—everything an agent needs to correctly invoke and interpret results.

  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?

  Despite 100% schema coverage, the description adds significant meaning beyond the schema: the document must contain 'stated chips only', full_counts returns 'verbatim canonical bytes' with size implications, and if_none_match is a weak ETag that can be revalidated. It also provides crucial domain semantics (e.g., exact lowercase Binance symbols) that the schema's brief descriptions lack.

  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 a specific action: 'Execute a research_query.v2 document over the deterministic engine' and enumerates the outputs (counts, denominators, outcomes_summary, reproducibility key, page-1 rows). It distinguishes this from sibling tools by explicitly naming interpret_prose, list_features, next_page, and run_cohort as alternatives for different needs.

  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?

  Provides explicit when-to-use guidance: use interpret_prose first for prose input, call list_features for grammar, use next_page for row-level evidence, and set page.limit 1-5 unless needed. It also clarifies when to pass full_counts: true and explicitly warns against filtering outcome fields. This is strong usage guidance with named alternatives and exclusions.

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