Scrutica

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

With no annotations, the description fully covers behavioral traits: it mentions the estimation nature, point estimate + bounds, methodology link, and a subtlety about the sparsity parameter (2:4 sparsity not credited). This adds significant transparency beyond what the schema provides.

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

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

The description is three concise sentences: first states purpose, second specifies outputs and methodology, third sets important usage expectations. No redundant information, each sentence earns its place.

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

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

The description adequately covers the tool's function and usage context, but lacks detail on the exact return format of point estimate and bounds (no output schema), and does not mention error handling or prerequisites. Enough for basic use but gaps remain for complete understanding.

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

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

Schema coverage is 80%, but the description adds key context: the sparsity parameter's note about the deliberate lack of speedup credit, and the utilization parameter's calibration values (0.20–0.50, with examples). This goes beyond the schema default descriptions, enriching understanding.

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

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

The description explicitly states the tool's function: 'Compute peak BF16 FLOP estimates for a hardware configuration. Returns point estimate + bounds.' This clearly distinguishes it from sibling tools, which are all 'get' operations for specific entities or search.

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

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

The description gives clear context on when to use the tool (for FLOP estimation) and provides important usage guidance: outputs are estimates, not exact measurements, and should be presented with bounds and the is_estimated flag. However, it does not explicitly list when not to use or mention alternatives, but siblings are all different in function.

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

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 clearly indicates a read operation (fetch) and lists the return fields, implying no destructive side effects. However, it does not explicitly state safety (e.g., 'read-only') or mention any required permissions, which would elevate it to 5.

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

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

Three sentences with no filler. First sentence clearly states purpose and content, second lists return fields, third provides alternative tools. Highly efficient and front-loaded.

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

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

Given the tool's simplicity (single parameter, well-documented schema, no output schema but return fields listed), the description is complete. It covers what the tool does, its inputs, outputs, and how it relates to siblings. No gaps.

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

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

The input schema already provides a thorough description (format, resolution instructions) for the sole parameter. Schema coverage is 100%, so baseline is 3. The description adds no additional parameter detail beyond what is in the schema.

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

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

Clearly states the verb 'Fetch' and resource 'organization' (company, government entity, holding company) by canonical ID. Lists specific return fields. Distinguishes from siblings by explicitly mentioning alternatives like scrutica_query_export_controls and scrutica_get_supply_chain.

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

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

Explicitly tells when to use alternatives: use scrutica_query_export_controls for BIS details, scrutica_get_supply_chain for edge graphs. Also, the input schema description advises to resolve ID via scrutica_search first, providing clear when-not guidelines.

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

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

No annotations provided, so description carries full burden. Lists returned fields and clarifies what it does not compute (BIS exposure). Does not mention read-only nature or error handling, but overall transparent for a fetch operation.

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

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

Three sentences: purpose, return fields, usage guidance. Front-loaded, no wasted words, well-structured.

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

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

No output schema, so description compensates by listing all return fields explicitly. Covers facility details and data-quality flags, and excludes missing BIS calculation. Complete for a single-facility lookup.

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

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

Schema coverage is 100% with detailed parameter description. Tool description repeats 'canonical ID' but does not add new semantics beyond schema. Baseline 3 applies.

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

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

The description clearly states it fetches complete details for a single Scrutica facility, distinguishing it from sibling tools like scrutica_search (ID resolution) and scrutica_query_export_controls (BIS checks).

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

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

Explicitly instructs to resolve IDs via scrutica_search first and points to scrutica_query_export_controls for BIS exposure, providing clear when-to-use and when-not-to-use guidance.

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

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

No annotations provided, but the description implies a read-only lookup operation. It discloses that it returns documentation (URL, anchor, summary) and lists accepted topics. It does not mention any side effects, errors, or auth requirements, but for a simple retrieval tool, this is adequate.

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

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

Two sentences: first states purpose, second lists topics and return format, and ends with a clear usage hint. Highly efficient with no fluff.

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

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

Given the tool's simplicity (one enum parameter, no nested objects, no output schema), the description covers purpose, parameters, output, and usage context thoroughly. No gaps.

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

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

Schema description coverage is 0%, but the description explicitly lists all enum values for the 'topic' parameter, providing context beyond the schema. It also clarifies the return format, adding meaning. The single parameter is well explained.

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

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

The description clearly states it returns methodology documentation for a Scrutica metric or index, lists all possible topics, and specifies the return format (URL + section anchor + summary). It distinguishes from sibling tools which retrieve entities, not documentation.

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

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

Explicitly states when to use: when a user asks 'how did you calculate X'. While no explicit when-not-to-use or alternatives are given, the sibling tools are obviously different, so the context is clear enough.

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

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

With no annotations, the description carries full burden. It states 'Fetch' indicating a read operation and describes the output structure (assumptions, affected facilities, etc.). However, it does not disclose potential side effects, idempotency, or rate limits, which are minor for a simple fetch tool.

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

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

The description is two sentences: the first states the purpose, the second lists scenarios and output. No wasted words. The most important information is front-loaded.

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

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

For a tool with one parameter and no output schema, the description covers the input options and output structure well. It lacks error handling or pagination details, but these are not critical for a simple fetch scenario.

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

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

Schema description coverage is 0%, so the description must compensate. It explains each enum value (e.g., 'taiwan-strait' -> '4 TSMC disruption scenarios'), adding meaning beyond the bare enum list. This provides rich context for input selection.

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

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

The description starts with 'Fetch geopolitical compute risk scenarios,' clearly stating the verb and resource. It then lists all available scenario IDs with brief explanations, distinguishing this tool from siblings like 'scrutica_get_company' which fetch different entities.

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

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

The description implies usage by listing available scenarios but does not explicitly guide when to use this tool over alternatives. No exclusions or prerequisites are mentioned, leaving the agent to infer context from the sibling tool names.

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

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

No annotations are provided, so the description must bear the burden of behavioral disclosure. It fails to state that the tool is read-only, mention error handling, or address what happens for invalid inputs. The description only lists return fields, lacking transparency on side effects or permissions.

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

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

The description is three sentences with no wasted words. It front-loads the purpose and then lists fields. However, it could benefit from structuring the return fields as a bullet list for clarity.

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

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

While it explains return fields and the 'list_all' option, it does not address required parameters interplay (e.g., if list_all is false, must provide country or program_id), error scenarios, or pagination for list_all. This is adequate for a simple tool but not fully complete.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds marginal value by explaining that 'program_id' is used for regional programs, but this information is already partially in the schema. No additional syntax or format details are provided beyond the schema.

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

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

The description clearly specifies the verb 'Fetch' and the resource 'detailed data on a national sovereign AI compute program'. It lists specific return fields and distinguishes from sibling tools like scrutiica_get_company or scrutiica_get_facility by focusing on sovereign programs.

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

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

The description implies usage for fetching a single program or listing all programs via 'list_all', but it does not explicitly state when to use this tool versus alternatives like scrutiica_search, nor does it provide exclusions or prerequisites.

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

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It details data provenance, temporal scope, and output field semantics (e.g., supply_share, price_correlation_3m), but does not mention authentication requirements 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.

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

The description is front-loaded with the core purpose and uses efficient, informative sentences without redundancy. Every clause adds value, such as clarifying data sources and temporal scope.

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

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

Given the tool's complexity, no output schema, and 3 parameters, the description adequately covers output format and data limitations. It is missing pagination details but the limit parameter is documented in the schema.

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

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

Schema description coverage is only 33%, but the description compensates by explaining the direction parameter's meaning ('upstream' vs 'downstream') and the content of each edge, adding significant value beyond the schema's enum and type definitions.

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

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

The description clearly states 'Return supply-chain relationships for one or more organizations', using a specific verb and resource. It distinguishes itself from sibling tools like scrutica_get_company and scrutica_get_facility by focusing exclusively on supply chain edges.

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

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

The description explains the direction parameter but does not explicitly state when to use this tool versus alternatives or provide exclusions. Usage context is implied but not explicit.

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

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

With no annotations, the description discloses the data source (Federal Register anchored), authority tier (Tier 1), coverage classes, and data quality flags. However, there is a contradiction between the description's 'case-insensitive substring match (no alias expansion)' and the schema's 'fuzzy matched against aliases', which could mislead. No annotation contradiction exists.

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

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

The description is front-loaded with purpose and well-structured, though somewhat verbose due to detailed explanations of return fields and data quality. Every sentence adds value given no output schema, but could be slightly tightened.

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

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

Given 4 parameters, no annotations, and no output schema, the description covers return fields, data quality, authority tier, and parameter behavior. Missing a few parameter details (like limit range, though in schema) but otherwise complete for a complex tool.

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

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

Schema coverage is 75% (3 of 4 parameters have descriptions). The description adds nuance to entity_name but contradicts the schema's 'fuzzy matched against aliases' with 'no alias expansion'. The baseline 3 is reduced due to this inconsistency, as it undermines reliability.

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

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

Clearly states the tool looks up BIS Entity List designations for companies or countries. Differentiates from siblings by explicitly naming scrutica_get_company for OFAC SDN/Wassenaar, establishing a specific verb+resource and scope.

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

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

Provides explicit when-to-use (BIS Entity List) and when-not-to-use (OFAC, Wassenaar) with a direct alternative (scrutica_get_company). Also explains matching behavior, making usage boundaries clear.

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

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

No annotations present, so description shoulders the burden. Discloses return fields (id, name, type, summary, URL) and filtering options. Does not explicitly state read-only, but search is implied safe. Lacks mention of pagination or rate limits, but adequate.

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

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

Four sentences, front-loaded with purpose. Every sentence adds value: what it does, what it returns, filtering, and exclusions. No redundancy or fluff.

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

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

For a search tool with 4 parameters and no output schema, the description covers all essential aspects: what is searched, return fields, filtering, and when to avoid. Complete enough for an AI agent to invoke correctly.

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

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

Schema coverage is 75%, and description adds context: 'Filter by entity_type to scope to a single class' and 'Filter by ISO 3166-1 alpha-2 country code'. Describes output format, which compensates for missing output schema.

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

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

Clear verb+resource: 'Search facilities, companies, or sovereign programs'. Distinguishes from siblings by naming alternatives (scrutica_query_export_controls, scrutica_get_supply_chain).

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

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

Explicitly states when NOT to use (BIS Entity List, supply-chain traversal) and provides correct alternative tools. Also gives filtering advice (by entity_type, country).

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