DeltaSignal ATLAS-7

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

The description adds the behavioral detail that the tool is 'subscription-gated,' which is not in the annotations. It also implies a read-only screen, consistent with readOnlyHint and idempotentHint. However, it does not explain the semantics of 'semantic' or what happens with filters.

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 a single short phrase, making it very concise and front-loaded. However, it is so brief that it may sacrifice clarity for brevity.

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 rich schema and annotations, the description provides a minimal but sufficient glimpse of the tool's purpose and gating. It lacks usage context and differentiation from many related alpha-candidate tools, so it is 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?

All three parameters (limit, stress_field, signal_filter) are already described in the schema with coverage at 100%. The description adds no parameter-level meaning beyond what the schema provides.

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 states it is a 'semantic alpha-candidate screen,' which indicates it presents alpha candidates, but it lacks a clear verb (e.g., list/search) and does not distinguish from sibling tools like deltasignal_alpha_opportunities or atlas7_signal_board.

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?

No guidance is provided about when to use this tool versus alternatives. The description only mentions subscription gating, with no mention of scenarios, exclusions, or alternative tools.

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?

Annotations already provide readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds the 'subscription-gated' access constraint, which is a useful behavioral detail beyond the annotations. However, it doesn't disclose other traits like pagination, result limits, or whether searches span multiple data sources.

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 a single, concise sentence with no filler words. It front-loads the important access constraint and clearly names the resource.

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 availability of a rich output schema and strong annotations, the description only needs to clarify the search scope, but 'archive and history' remains ambiguous. With many sibling tools, it's unclear what data sources are searched and how this differs from similar tools like atlas7_recent_history. The description is under-specified for an agent deciding which tool to invoke.

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 schema covers all three parameters (cik, limit, ticker) with descriptions, so the baseline is 3. The description adds no additional parameter-specific meaning beyond the schema, and doesn't clarify how the parameters interact (e.g., whether cik or ticker is preferred).

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 uses the verb 'search' with the resource 'archive and history', making the basic action clear. However, it doesn't differentiate from sibling tools like atlas7_recent_history or atlas7_semantic_query, which also search for historical data. The 'subscription-gated' modifier adds a constraint but not enough to uniquely identify this tool's purpose.

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?

There is no guidance on when to use this tool versus alternative archive/history searches. The only contextual hint is 'subscription-gated', which implies an access requirement but doesn't explain selection criteria. No alternatives are mentioned.

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?

Annotations already convey safe read-only, idempotent, non-destructive behavior. The description adds that access is subscription-gated and data is filing-backed, which is useful context, but it does not describe return behavior, pagination, or what happens when access is denied.

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 very short and contains no filler, but it is under-specified and uses vague jargon like 'surface.' Its brevity is not backed by substance, making it only minimally acceptable as a concise description.

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 tool benefits from strong annotations (read-only, idempotent, open-world) and a full output schema, which lowers the description's burden. However, the description still lacks a clear operation and usage context, so it is only minimally complete for a low-complexity 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 description coverage is 100%, with every parameter (cik, limit, ticker) explicitly documented. The description itself adds no parameter-level meaning, so the schema baseline of 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 is a noun phrase ('Subscription-gated filing-backed fundamentals surface') with no verb; it never states that the tool retrieves or lists company fundamentals. It largely restates the title with modifiers, so it does not clearly convey the tool's operation or distinguish 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.

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

There is no guidance on when to use this tool versus alternatives, no exclusions, and no mention of how it differs from similarly named tools like deltasignal_company_fundamentals or atlas7_company_report_inputs. The agent is left without context for tool selection.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, covering the safety profile. The description adds the 'Subscription-gated' access constraint, which is useful context, but does not disclose what the tool actually returns or how it behaves beyond that. No 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 a single sentence with no wasted words, but it is under-specified. It is concise yet content-poor, offering only a label rather than actionable context. This is neither a model of efficient clarity nor an egregious length issue.

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?

Even though annotations and an output schema exist, the description leaves the tool's fundamental purpose ambiguous. An agent cannot tell what data this tool provides, how it relates to a Company Report, or when to choose it over similar 'input' tools in the sibling list. The overall context remains incomplete.

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%: cik, limit, and ticker each have clear descriptions. The tool description adds no extra meaning beyond calling it a 'bundle', so it does not elevate beyond the schema baseline. There is no additional semantic nuance for the agent.

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 'Subscription-gated structured Company Report input bundle' is vague and noun-heavy. It restates the tool name ('input bundle' ≈ 'inputs') without specifying an action or outcome. It does not distinguish this from sibling tools like atlas7_morning_brief_inputs or deltasignal_company_report.

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?

No guidance is given on when to use this tool versus alternatives. 'Subscription-gated' hints at a prerequisite but does not explain the intended context, such as preparing data for a company report or enriching issuer analysis. Sibling tools with similar patterns remain undifferentiated.

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?

Annotations already cover read-only and idempotent behavior, so the description adds value by disclosing subscription gating and that raw SQL is not exposed. This goes beyond the structured annotations and provides important context for safe usage.

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 concise sentences, front-loaded with the primary purpose, and contains zero redundant information. Every word 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?

Given full schema coverage and rich annotations, the short description sufficiently covers the tool's purpose, key output (public plan and SQL fingerprint), and a notable constraint (no raw SQL). It could mention the relationship to executing a semantic query, but the available structured data compensates.

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 baseline is 3. The description adds no parameter-level detail beyond what the schema already provides, such as 'sort', 'limit', 'fields', 'intent', 'filters', and 'model_key'.

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 the tool performs 'validation of a governed semantic query' with a specific verb and resource. It distinguishes itself from siblings by noting it 'returns the public plan and SQL fingerprint without exposing raw SQL', which is a unique scoping.

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 a usage context (subscription-gated validation) but does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. There's no reference to sibling tools like atlas7_semantic_query for comparison.

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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering safety. The description adds 'Subscription-gated', which is a meaningful behavioral constraint not present in annotations, indicating potential access restrictions.

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 a single, concise sentence with no wasted words. It front-loads the key qualifier 'Subscription-gated' and remains highly scannable.

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 is adequate given the output schema and annotations, but it lacks context on scope, input expectations, or what differentiates this tool from similarly named siblings. It does not explain what data universe or stress metrics are included, making it harder to select correctly among many stress-related tools.

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 clear descriptions for all three parameters, so the description does not need to compensate. The description adds no additional parameter-level detail, but the schema is sufficient.

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 identifies the resource ('covenant, debt, and liquidity stress view') and implies a read-only retrieval operation, though it lacks an explicit verb like 'get' or 'list'. It does not differentiate from similar sibling tools such as deltasignal_covenant_stress or atlas7_top_stress.

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?

There is no guidance on when to use this tool over alternatives, nor any mention of prerequisites or use cases. The description only states what the tool is, not when it should be invoked.

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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is clear. The description adds the 'Subscription-gated' context, but it does not disclose other behavioral traits like how filters combine or what a 'drilldown' returns. 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.

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

The description is a single, compact sentence with no filler or redundant praise. It reads clearly, though 'drilldown' is somewhat terse and the description largely echoes the tool name.

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?

With all parameters optional and no explanation of behavior when no filters are provided, the description leaves ambiguity. The output schema exists, but the description doesn't convey what the lineage drilldown returns or how subscription gating affects usage.

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?

All five parameters are already described in the input schema with 100% coverage, so the description doesn't need to repeat them. It also doesn't add extra meaning beyond the schema, such as how multiple optional parameters interact.

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 'Subscription-gated evidence and provenance lineage drilldown' identifies a specific resource (evidence/provenance lineage) and action (drilldown), making the core purpose clear. However, it does not differentiate the tool from its sibling 'atlas7_lineage_audit', which could overlap in purpose.

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 provides no guidance on when to use this tool versus alternatives. It only notes that it is 'Subscription-gated', which is an access constraint rather than a usage recommendation, and no sibling tools are referenced.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context by disclosing that the tool is 'Subscription-gated' and that it does not return raw SQL, which are behavioral traits not covered by annotations. No contradictions found.

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 a single, front-loaded sentence of 13 words: 'Subscription-gated explanation of fields, evidence requirements, and SQL fingerprint without raw SQL.' Every phrase adds meaningful information, with no wasted words or repetition.

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 presence of an output schema and comprehensive annotations, the description sufficiently explains the tool's purpose. It covers key aspects (fields, evidence, SQL fingerprint) and the subscription constraint, making it complete enough for an agent to decide on invocation. A slightly richer description of what 'signal' means would push this to 5, but it is not necessary.

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 has 100% description coverage for all six optional parameters, so the description does not need to explain them. Baseline 3 applies since the schema carries the full burden and the description adds no extra parameter-level semantics.

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 the tool provides 'explanation of fields, evidence requirements, and SQL fingerprint without raw SQL', using a specific verb (explain) and resource (signal). The phrase 'without raw SQL' distinguishes it from SQL-returning tools like atlas7_compile_query, making the purpose uniquely identifiable.

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 when to use (when an explanation is needed) and gives a clear exclusion ('without raw SQL'), but it does not explicitly name alternative tools or state 'when not to use'. Usage context is implicit rather than explicit, so it falls short of a 4 or 5.

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?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is established. The description adds the 'Subscription-gated' constraint, which is a meaningful behavioral condition not captured by the annotations. This provides useful context about access requirements beyond what the schema or annotations communicate.

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 a single sentence that front-loads the most important attribute ('Subscription-gated') and packs in the key contents (field, metric, filter, sort, evidence) without waste. Every word contributes to understanding the tool's scope and constraint, making it highly concise and 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?

Given the tool's narrow scope (retrieving a catalog for one model) and the presence of an output schema that likely details the return structure, the description is sufficient. It lists the types of components covered and the subscription gate. It does not describe pagination or detailed usage, but these are not necessary for a catalog tool with a rich output schema and full parameter documentation.

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% because the only parameter, model_key, is described as 'Required governed semantic model key.' The description's phrase 'for one governed semantic model' reinforces that the parameter identifies a model, but it does not add syntax, format, or additional meaning beyond the schema. With full schema coverage, a baseline score of 3 is appropriate.

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 identifies the tool as a 'field, metric, filter, sort, and evidence contract' for a specific semantic model, which conveys its role as a catalog for query components. It does not use a verb+resource construction, but the scope is specific enough to distinguish it from sibling tools like atlas7_model_catalog. The phrase 'for one governed semantic model' signals that it is per-model, adding clarity.

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 that this tool is used to retrieve the catalog of fields, metrics, filters, sorts, and evidence for a given model, but it does not explicitly state when to prefer it over alternatives like atlas7_semantic_query or atlas7_compile_query. No exclusions or direct comparisons are provided, so the usage context is inferred rather than 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?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description adds value by noting the subscription gate and the canonical nature of the data, which are not captured in annotations. This is useful behavioral context beyond the structured hints.

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 a single, front-loaded sentence with no filler. It efficiently communicates the tool's purpose, access constraint, and input options, earning its place without redundancy.

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 rich annotations, complete parameter schema, and presence of an output schema, the terse description is largely sufficient. It includes the key subscription-gating and canonical identity aspects, though it could optionally mention when to use this versus sibling tools for a more complete picture.

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 schema covers all three parameters with descriptions, so the description's mention of 'by ticker or CIK' adds little beyond the schema. Since schema coverage is 100%, a baseline score of 3 is appropriate; the description does not introduce new parameter-level meaning.

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 identifies the tool as a canonical issuer identity lookup by ticker or CIK, using a specific verb and resource. It distinguishes itself from sibling tools like atlas7_issuer_signal by focusing on identity lookup rather than signals.

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 use when an issuer identity is needed by ticker or CIK, but it does not explicitly state when to prefer this tool over alternatives or mention any exclusions. The 'Subscription-gated' phrase hints at access requirements but provides no direct comparison to sibling tools.

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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, reducing the description's burden. The description adds meaningful context about subscription-gating and lookup by ticker or CIK, which are not in the annotations. It does not cover response structure, rate limits, or error behavior, but this is acceptable given 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.

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

The description is a single sentence with zero filler. It Front-loads the key qualifier ('subscription-gated') and the two input dimensions, making it concise and 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?

Rich annotations and an output schema reduce the description's burden, but the description still lacks a clear definition of what a 'signal' is and does not differentiate from nearby siblings like deltasignal_alpha_signals or atlas7_signal_board. Given the tool's moderate complexity, this is adequate but leaves gaps around exact usage context.

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 provides descriptions for all three parameters (cik, limit, ticker) with 100% coverage, meeting the baseline. The description's phrase 'by ticker or CIK' restates the schema's existing parameter relationships without adding new semantics, so no bonus is earned.

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 identifies the resource (issuer signal) and the two lookup keys (ticker, CIK), which makes the tool's purpose understandable. However, it lacks an explicit verb like 'get' or 'retrieve', and does not explicitly contrast it with siblings such as atlas7_issuer_identity or atlas7_explain_signal, so it falls short of a 5.

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 only notes that the tool is 'subscription-gated,' which implies a prerequisite but gives no guidance on when to use this tool versus the many sibling tools. It provides no 'when to use' or 'instead of' instructions, 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.

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

The annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description's main contribution is the 'subscription-gated' access constraint, which is useful. However, it does not describe the audit's scope, return format, or any limitations. This adds some value beyond annotations but is not rich.

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 a single compact phrase with no filler and is easy to parse. It is front-loaded, but its brevity comes at the cost of explicitness, making it less informative than it could be while still being concise.

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?

Despite strong annotations and a complete schema, the description is too terse to orient the agent within a large sibling set. It lacks context about calculation lineage audit semantics, prerequisites beyond subscription, and typical usage scenarios, so the overall tool definition feels incomplete.

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 has full description coverage for all five optional parameters, so the schema already documents their semantics. The description adds no parameter-level meaning, and the baseline of 3 is appropriate since the schema carries the burden.

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, 'Subscription-gated calculation lineage audit,' uses a noun phrase rather than a clear action verb. It indicates the tool's domain but does not specify what the agent can do with it (e.g., retrieve, run, inspect). It vaguely distinguishes from sibling lineage tools like atlas7_evidence_lineage by adding 'calculation,' but remains under-specified.

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?

No guidance is provided for when to use this tool versus alternatives such as atlas7_evidence_lineage or deltasignal_atlas7_audit_status. The only hint is 'subscription-gated,' which implies access restrictions but gives no context on preferred use cases or exclusions.

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?

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint, so the description doesn't need to repeat those. The description adds 'subscription-gated,' which is a behavioral constraint, but it doesn't explain what an 'overlay context' does or what the output represents. This is acceptable but minimal.

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 extremely short, which aligns with conciseness, but it's a fragment lacking a clear sentence structure and fails to convey useful information. It's not front-loaded with a verb or action, making it less effective.

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?

Even though an output schema exists and annotations are present, the description doesn't clarify the tool's core function. 'Overlay context' and 'market and instrument' are ambiguous, and there's no usage guidance. This leaves the agent with insufficient context to select the tool 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 description coverage is 100%, with both 'limit' (max rows) and 'instrument' (optional market instrument) described clearly. The tool description adds no additional parameter semantics, so the 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 'Subscription-gated market and instrument overlay context' is a noun phrase without a verb, so it doesn't state what the tool does. It largely restates the name (market context) and adds vague terms like 'overlay context' that don't differentiate it from sibling tools such as atlas7_quick_ticker_check or atlas7_signal_board.

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?

There is no guidance on when to use this tool versus alternatives. The phrase 'subscription-gated' implies access restrictions but doesn't help an agent decide between this and other context tools. No exclusions or alternative tool names are mentioned.

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?

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds the 'subscription-gated' access requirement and lists the health dimensions, but it doesn't elaborate on how health is computed, what the response structure looks like (though output schema exists), or any additional behavioral nuances.

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 a single, dense sentence with no redundant words, effectively front-loading the key scope. However, it is a noun phrase rather than a clear explanatory sentence, which slightly impairs immediate comprehension.

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 provides a high-level scope but lacks context on what 'health' means, how the metrics are derived, or how to interpret the results. It also doesn't address selection among sibling tools. The presence of an output schema covers return structure, but the overall operational context is incomplete.

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%: the only parameter, 'limit', has a clear description ('Maximum health rows'). The tool description adds no additional parameter semantics, so the baseline of 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 identifies a specific health surface covering semantic metadata, source freshness, row-count, and evidence contracts, which clearly distinguishes it from raw data retrieval tools. However, it is phrased as a noun phrase rather than an explicit verb-driven action, and it doesn't explicitly differentiate from sibling tools like atlas7_readiness or atlas7_evidence_lineage.

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?

There is no guidance on when to use this tool versus alternatives. The phrase 'Subscription-gated' hints at access constraints but doesn't explain usage context or when this should be preferred over similar atlas7 health/readiness tools.

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?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior, so the safety profile is covered. The description adds valuable context about the 'subscription-gated' access requirement, which is an auth-related trait not captured in annotations. This extra context goes beyond what annotations provide, warranting a 4.

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 a single, compact sentence that front-loads the key access constraint ('Subscription-gated') and enumerates the catalog's contents. Every phrase carries meaning, with no redundant or filler text. This is an ideal length for a no-parameter tool.

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 there are no parameters, rich annotations (read-only, open world, idempotent), an output schema, and a clear description of contents, the tool is fully specified. The description covers the essential aspects (catalog contents, access restriction) without needing to explain parameters or return values. It is complete for its scope.

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 tool has zero parameters, so the baseline is 4 per the rubric. The description adds context about the contents of the catalog (semantic models, intents, evidence requirements, freshness policies), which helps interpret the output. Since there are no parameters to explain, the description need not compensate further.

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 identifies the tool as a catalog of governed semantic models, intents, evidence requirements, and freshness policies. This specific scope differentiates it from sibling tools like atlas7_field_catalog, which focuses on fields. Though it lacks an explicit verb, the noun phrase 'catalog' implies a listing operation, and the resource is precisely defined.

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 context—if you need model catalog information, this is the tool—but it does not explicitly state when to use it over alternatives or provide exclusions. No alternative tools are named, and the 'subscription-gated' note only hints at access restrictions, not selection criteria.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the 'Subscription-gated' access constraint, which is useful context, and 'structured' suggesting a defined output format. However, it does not disclose any further behavioral traits such as pagination, rate limits, or error conditions, so the extra value beyond annotations is limited.

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 a single short noun phrase, which is efficient in length but under-specified. It lacks a verb and essential context, making it more of an under-specification than a concise, informative statement. The phrase does not earn its place because it fails to clarify the tool's function.

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 (3 optional params, output schema, and annotations), the description should explain what the Morning Brief input bundle is used for and when to call it. It only states a noun phrase, which is insufficient for an agent to understand its role relative to the many related sibling tools. The description is incomplete for a tool that appears to be a data retrieval utility.

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 provides full descriptions for all three parameters (limit, stress_field, signal_filter), giving 100% coverage. The description does not add any additional meaning about how these parameters affect the 'input bundle'; it merely labels the tool as 'structured'. Since the schema already documents parameters well, the description adds little semantic value.

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 'Subscription-gated structured Morning Brief input bundle' conveys that the tool provides inputs for a Morning Brief, but it lacks a clear verb (e.g., 'retrieve' or 'list') and does not specify the tool's action. It distinguishes itself partially by referencing 'Morning Brief' and 'subscription-gated', but it doesn't differentiate from sibling tools like atlas7_company_report_inputs or deltasignal_morning_brief.

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?

There is no guidance on when to use this tool versus alternatives, no exclusions, and no prerequisites beyond the subscription gate. The description does not mention any related tools or contexts where this would be preferred, leaving the agent without decision-making information.

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?

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe, read-only operation. The description adds the behavioral detail that it is 'subscription-gated', which is useful context not present in the annotations. However, it does not disclose what 'relative pressure' entails or how the ranking is computed, so the informational gain is minimal.

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 extremely short, but it is an under-specified fragment rather than a well-structured sentence. 'Subscription-gated peer ranking and relative pressure' is a noun phrase that reads more like a label than an explanation. While it is concise, it sacrifices meaningful content for brevity, crossing from conciseness into under-specification.

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?

Despite having an output schema and rich annotations, the description fails to explain core concepts: what a 'peer' is, how 'relative pressure' is defined, and what the returned ranking looks like. The description is not sufficient for an agent to correctly select and invoke this tool with confidence, especially given the availability of sibling tools that may appear similar. The presence of an output schema helps, but the description itself lacks essential context.

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 covers 100% of the parameters with descriptions (cik, limit, ticker), so the schema already provides the required semantic details. The description adds no additional parameter context, such as how to choose between cik and ticker or what the limit controls. Baseline 3 is appropriate because the schema carries the full burden and the description offers no supplementary value.

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 'Subscription-gated peer ranking and relative pressure' is a noun phrase rather than a clear verb+resource statement. It vaguely suggests the tool provides comparative ranking data, but lacks a specific action verb (e.g., 'get', 'list', 'compare') and does not explain what 'peer ranking' or 'relative pressure' concretely means. It does not distinguish itself from siblings like atlas7_pressure_board or deltasignal_peer_ranking, which likely offer overlapping capabilities.

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 provides no guidance on when to use this tool versus alternatives. It only mentions 'Subscription-gated' as a restriction, but does not state prerequisites, intended use cases, or exclusions. There is no mention of what inputs are needed or when a user would prefer this over a sibling tool. This is completely absent.

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?

Annotations cover read-only/idempotent/non-destructive, and the description adds valuable context: 'subscription-gated' reveals an access requirement, and 'MVO accepts ticker or CIK filters until watchlist persistence is enabled' discloses the tool's temporary/future behavior. This exceeds what annotations alone convey, without contradicting them.

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 with no filler. The first is a compact noun phrase, the second effectively communicates the current limitation. It is concise and well-structured, though the purpose could be more action-oriented.

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 does not explain what 'watchlist analysis' actually produces, what criteria are analyzed, or how the saved watchlist relates to the ticker/CIK filters. With an output schema present return shape is defined, but core behavioral context is missing. The sibling set includes many similar analysis tools, so this ambiguity makes it hard to know when to invoke.

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 descriptions are complete (100% coverage), explaining cik, ticker, and limit. The description only reiterates 'ticker or CIK filters' without adding new syntax, mutual exclusivity rules, or format details beyond what the schema already provides. Baseline 3 is appropriate.

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 uses a noun phrase 'Subscription-gated saved watchlist analysis' rather than a clear verb, making the action ambiguous. It mentions ticker/CIK filters but not what the tool does with them. It distinguishes itself from siblings via 'saved watchlist' and 'subscription-gated' but lacks an explicit operation like 'list' or 'analyze'.

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?

No explicit guidance on when to use this tool versus alternatives. The MVO note about filters implies current usage (pass a ticker or CIK) but doesn't state when this is better than quick_ticker_check or issuer_signal, and no exclusions or prerequisites are provided.

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?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds 'subscription-gated' and 'semantic' as useful access and query-mode context beyond the annotations. However, no additional behavioral details (e.g., response format, data scope, auth specifics) are disclosed, so it remains minimally transparent.

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 extremely concise and front-loaded, with zero wasted words. However, a single noun phrase is under-specified for a tool with three optional parameters and multiple sibling tools; it lacks the structured content needed to be genuinely helpful.

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?

Despite having annotations, a complete schema, and an output schema, the description fails to convey what the 'pressure board' actually provides or how it differs from similarly named tools. Given the large sibling list (e.g., atlas7_signal_board, atlas7_top_stress, deltasignal_pressure_board), this description is not complete enough for an agent to select the correct 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?

The input schema has 100% description coverage for all three parameters, including limits, stress field override, and signal filter. Since the schema already documents each parameter, the tool description adds no extra semantic value for parameters, and the baseline of 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 'Subscription-gated semantic pressure board' is a noun phrase with no verb and largely restates the tool's name/title. It does not specify what action the tool performs (e.g., retrieves, lists, computes) or what a 'pressure board' is, making the purpose vague.

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?

No usage guidance is provided. There is no mention of when to use this tool versus siblings like atlas7_signal_board or deltasignal_pressure_board, and no exclusions or alternative recommendations. The only hint is 'subscription-gated,' implying an access prerequisite.

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?

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds the subscription-gated access restriction and hints at the semantic/analytical nature of the check, providing useful context 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.

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

At four words, the description is extremely concise but under-specified. It reads as a tagline rather than a functional description and omits critical context that would help an agent select and invoke the tool correctly.

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 output schema and annotations cover some aspects, the description is too skeletal to fully support tool selection. It does not explain what 'triage' entails, what kind of results to expect, or when this tool is the appropriate choice among the many siblings.

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 provides complete descriptions for all three optional parameters, so the schema already covers parameter semantics. The description adds no parameter-specific detail or usage nuance, warranting the baseline score.

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 'semantic ticker triage' identifies the resource (ticker) and an action (triage), but it is vague about what the triage actually produces or accomplishes. It does not clearly distinguish this tool from the similar deltasignal_quick_ticker_check or other atlas7 tools.

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?

No guidance is provided on when to use this tool versus alternatives. The only contextual clue is 'subscription-gated', which is an access constraint, not a usage directive.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds valuable context about subscription gating and the availability of the DeltaSignal readiness path through x402, which goes beyond what annotations provide. It does not describe the output format, but an output schema exists and the tool is a simple status check.

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 concise sentences. The first sentence states the tool's purpose and gating, and the second provides the alternative path. Every clause earns its place, with no redundant or filler content.

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 simple, read-only, status-check tool with one optional parameter and an output schema, the description covers the key contextual aspects: what the tool reports (readiness/entitlement), the subscription requirement, and the relationship to the DeltaSignal route. No additional behavioral detail is necessary for an agent to select and invoke it 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?

The only parameter, 'limit,' is fully described in the schema with a clear description ('Maximum readiness rows') and min/max constraints, so schema coverage is 100%. The description does not add any further semantic detail about the parameter, and none is needed beyond what the schema already provides.

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 identifies the resource as ATLAS-7 semantic readiness and entitlement status, and distinguishes it from the existing DeltaSignal readiness surface by noting the subscription gate. However, it lacks an explicit action verb (e.g., 'get' or 'check'), relying on the noun phrase 'readiness and entitlement status' to imply a status/readiness query.

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?

It explicitly mentions the alternative 'Existing DeltaSignal readiness remains available through x402' and states that the semantic surface requires a Marketplace subscription, giving a clear condition for when to use this tool versus the alternative. It stops short of explicitly saying 'use this when you have a Marketplace subscription,' but the context strongly implies it.

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?

Annotations already cover safety (readOnly, idempotent, non-destructive). The description adds 'subscription-gated' which is an access-control behavior not present in annotations, earning some credit. However, it omits other traits like response pagination or rate limits, so transparency is minimal but not absent.

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 extremely brief, but brevity here equates to under-specification rather than conciseness. It is a fragment, not a sentence, and the key verb is missing. The structure does not front-load important operational details.

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 large sibling toolset with similar names (e.g., atlas7_archive_search, deltasignal_atlas7_point_in_time_history), the description fails to clarify the unique use case or data scope. The output schema exists but is not enough to compensate for the missing contextual differentiation.

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%, with all three optional parameters (cik, limit, ticker) clearly described in the schema. The tool description adds no additional parameter meaning or usage nuance, so the baseline of 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 is a noun phrase ('Subscription-gated recent point-in-time issuer trajectory') without a verb, so it does not explicitly state what action the tool performs. It hints at historical issuer data but is vague about the specific metric and does not distinguish it from similar tools like deltasignal_atlas7_point_in_time_history.

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?

There is no guidance on when to use this tool or when to prefer alternatives. It does not mention any exclusions, prerequisites other than subscription-gating, or contextual triggers. The agent is left without direction to choose this tool among numerous siblings.

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?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds valuable behavioral context: it is subscription-gated and governed, and it only returns evidence envelopes, never raw SQL. This goes beyond the annotations by clarifying the response format and access constraints.

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 a single sentence, front-loaded with 'Subscription-gated governed semantic query', and contains no fluff. Every word adds value, making it extremely concise while still conveying the core purpose and key constraints.

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?

With a rich input schema and annotations, the description provides the essential behavioral disclosures (subscription, evidence-only, no raw SQL). It is sufficient for an agent to understand the tool's basic function, though it could be more complete with a brief example or a more explicit statement of what a semantic query is. Overall, it is well-rounded given the structured context.

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 has 100% description coverage, with each parameter described as 'Optional validated...' or 'Maximum rows to return'. The tool description itself does not add any parameter semantics, but the schema already provides sufficient meaning, so the baseline of 3 is appropriate.

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 identifies it as a semantic query tool that returns ATLAS evidence envelopes and explicitly excludes raw SQL, which distinguishes it from query compilation or raw access tools. The action is implied via 'semantic query' and the resource is 'ATLAS evidence envelopes', but it doesn't explicitly state the verb 'query' or explain what a semantic query entails.

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?

No guidance is given on when to use this tool versus its many siblings (e.g., atlas7_compile_query). It mentions 'Subscription-gated' but doesn't say when to choose this over alternative query approaches or what scenarios it is best suited for. No exclusions or alternatives are provided.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds only 'Subscription-gated', which is a useful behavioral constraint but does not explain what happens without a subscription, what output to expect, or any other dynamic behavior. With annotations, this is acceptable but minimal.

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 extremely short (one phrase) but it is under-specified, not concise. It lacks essential information, so the brevity is a deficit rather than a strength.

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 existence of many sibling signal-board tools (e.g., atlas7_pressure_board, atlas7_top_stress, atlas7_alpha_candidates), the description does not provide enough context to understand what makes this board unique or what data it surfaces. The presence of an output schema partially compensates, but the description still leaves the tool's function ambiguous.

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 input schema documents all three parameters (limit, stress_field, signal_filter). The description adds no additional parameter semantics beyond the schema, which is the baseline case for high coverage.

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 is a noun phrase ('Subscription-gated latest issuer signal board') with no clear verb or action. It suggests a board of latest issuer signals but does not state what operation the tool performs (e.g., listing, fetching, searching). It also does not differentiate from sibling tools like atlas7_pressure_board or atlas7_top_stress.

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?

There is no guidance on when to use this tool vs alternatives. No context, prerequisites, exclusions, or alternative tool mentions. The phrase 'signal board' loosely implies a use case, but it is 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?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds a meaningful non-obvious behavioral constraint: 'Subscription-gated' indicates access control requirements, which is valuable context beyond the annotations. No contradictions are present.

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 a single, front-loaded sentence with no wasted words. It packs the key qualifier ('Subscription-gated') and the resource scope into a compact form. It is appropriately concise, though it could arguably include more operational context without becoming bloated.

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 rich annotations and presence of an output schema reduce the burden on the description. However, the description is very brief and does not explain what 'discovery' returns, how filters interact, or when this tool is preferable to similar atlas7 tools. It is minimally viable but leaves the agent to infer important usage context.

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 every parameter (cik, limit, theme, ticker) already has a basic description. The tool description adds no additional parameter semantics beyond labeling the overall operation as discovery, so it does not exceed the schema baseline.

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 names a specific resource ('theme, concept, and taxonomy') and indicates a discovery operation, which is clear enough to understand the tool's domain. However, it does not differentiate this from sibling tools like atlas7_semantic_query or atlas7_field_catalog, both of which could also involve discovery-like behavior.

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 no guidance on when to use this tool versus alternatives. It does not mention typical use cases, exclusions, or relationships to sibling tools, leaving the agent to infer usage from the name and schema alone.

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?

Annotations already set readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the subscription-gating constraint and the 'semantic' nature of the ranking, but it does not disclose any other behavioral traits such as result ordering, pagination, or whether any filters are applied. This is minimal extra context beyond annotations, so a 3 is appropriate.

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 a single concise phrase with no filler or redundant details. It is front-loaded and every word contributes to the core idea. It is appropriately sized given the availability of schema and annotation information.

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?

Despite having annotations and an output schema, the description is too sparse to provide adequate context. It does not define what 'top stress' means, what data is being ranked, or what the output represents. This is especially problematic in a large sibling set with many stress-related tools, leaving the agent with insufficient information to select and use the tool 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?

All three parameters (limit, stress_field, signal_filter) have full descriptions in the input schema, so schema coverage is 100%. The description adds no additional parameter semantics beyond what the schema already explains. Since the schema does the heavy lifting, the baseline 3 is warranted.

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 reads as a noun phrase, 'Subscription-gated semantic top-stress ranking,' which implies the tool returns a ranking of top stress but lacks an explicit verb like 'get' or 'list.' It does not specify what entities are ranked (issuers, signals, etc.) and does not distinguish itself from siblings such as deltasignal_top_stressed or atlas7_covenant_stress, so the purpose remains somewhat vague.

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 only usage hint is 'Subscription-gated,' which is an access prerequisite rather than guidance on when to prefer this tool over alternatives. The description does not provide context about when to use this tool vs. other stress-related tools, nor does it mention any exclusions or alternative recommendations.

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?

Annotations already declare readOnly, idempotent, and non-destructive; the description adds valuable behavioral disclosures: performs one HTTPS read, has no destructive side effects, and does not handle wallets, payments, orders, or account state. It also adds the interpretive caveat that high scores are drilldown candidates, not standalone conclusions.

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 dense but well-structured: a purpose sentence, a parameter summary, and a behavior section. It repeats some annotation terms (read-only, idempotent) and lists many fields, but every clause adds operational context, resulting in minimal waste for the information conveyed.

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?

Despite having an output schema, it provides a full operational picture: default behavior, parameter constraints (limit 1-100, source_date format), side effects, and an interpretation caveat. Combined with rich annotations and output schema, the description leaves no major ambiguity for an agent selecting or invoking this 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?

The schema already provides 100% parameter descriptions, so the baseline is 3. The description elevates this by explaining that source_date 'replays a known slice' and clarifying default behavior for issuer_type and include_funds, enriching the raw schema 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 opens with a specific verb and resource: 'screening tool to rank the active DeltaSignal issuer universe by deterministic Phase 1 alpha score.' It goes on to list concrete returned fields (ticker, CIK, alpha score, board rank, risk tier), which effectively differentiates it from sibling tools like alpha_signals and alpha_sweep.

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?

It provides clear usage context: default returns operating-company issuers, and include_funds=true or issuer_type=etf_trust|fund_vehicle|all should only be used when the user explicitly asks for ETF/trust/fund/product-vehicle screens. It lacks a direct comparison to named sibling tools, but the when-to-use guidance is explicit 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?

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description adds concrete behavioral detail: 'performs one HTTPS read, has no destructive side effects, and does not change board scoring, payments, wallets, files, or account state.' This exceeds the annotation baseline with actionable context.

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 well-structured with logical sections (purpose, parameters, behavior, usage scenarios). Every sentence adds value; there is no fluff or redundancy. It front-loads the core purpose and then supports with necessary detail.

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?

Despite having an output schema and annotations, the description provides a complete picture: what to expect in results, parameter semantics, safety guarantees, and specific use cases. It fully equips an agent to invoke the tool 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 100%, but the description enriches each parameter with behavioral context: limit as bounded samples, source_date as replay, issuer_type as narrowing audit, and include_rows as full rows for explicit debugging. This adds meaning beyond the schema 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 opens with a specific verb+resource: 'explain why the alpha-opportunity board includes, excludes, or demotes rows.' It clearly distinguishes this diagnostic from sibling tools like deltasignal_alpha_opportunities and deltasignal_alpha_sweep, and it enumerates the returned summary types.

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?

Explicit when-to-use guidance is provided with concrete trigger questions ('why a high raw alpha row is missing, why ETF/trust/fund rows are excluded by default, why a row was demoted, or whether a screen is safe to summarize'). It also references sibling tools as alternatives to use after.

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?

The description discloses behavioral traits beyond the annotations: 'read-only and idempotent; it performs one HTTPS read, has no destructive side effects, does not trade, does not store user data, and does not handle wallet secrets.' It also clarifies that source_date replays a historical slice. This significantly enriches the safety and side-effect profile for the agent.

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 well-structured with clear sections ('Parameters:', 'Behavior:', 'Usage guidelines:') and front-loads the purpose. It is somewhat verbose but every sentence contributes meaningful guidance. The structure helps an agent parse it quickly.

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 covers purpose, parameter semantics, behavioral traits, alternatives, and return content ('issuer-level signal evidence such as resilience, treasury pressure, regime fit, phase-one opportunity indicators'). Combined with the output schema and annotations, it provides a complete contextual picture for selecting and using this 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 100%, so baseline is 3. The description reinforces ticker normalization and adds a caveat about avoiding asset symbols. For source_date, it explains 'should be used only to replay a known historical DeltaSignal slice,' which is slightly more explicit than the schema. Overall, it adds modest value 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 uses a specific verb ('retrieve') and identifies the exact resource ('DeltaSignal ATLAS-7 alpha signals') and scope ('for one crypto public company ticker'). It clearly distinguishes itself from sibling tools by focusing on issuer-level signal evidence and explicitly listing supported tickers like COIN, MSTR, and MARA.

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 provides explicit usage guidance: 'Use it for research triage on supported public-company tickers' and warns 'do not pass crypto asset symbols unless they are listed public-company tickers.' It also names specific alternatives: 'call readiness first if you need service freshness, use covenant_stress for covenant-only questions, use company_fundamentals for raw SEC XBRL facts.' This exceeds basic when-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?

The description goes well beyond the readOnlyHint/idempotentHint annotations by disclosing concrete behaviors: three internal HTTPS reads, preservation of partial results on failure, never calls issuer-level tool, and the default operating-company issuer filter. This adds meaningful operational context that annotations alone do not provide.

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 information-dense yet each clause serves a purpose: purpose/scope, internal call plan, parameter constraints, behavior, and usage triggers. No filler or redundancy; it efficiently packs critical guidance into three sentences.

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 composite tool with only one parameter and a rich output schema, the description fully covers what the tool does, how it behaves, when to use it, and how to interpret results. It also handles edge cases (partial failures, prohibited params) which is more than sufficient for an agent to invoke it 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 100% for the single output_mode parameter, giving a baseline of 3. The description adds valuable guidance by explicitly restricting to 'compact only' and prohibiting other common parameters (limit, offset, ticker, etc.) because the preset owns them, which helps the agent avoid passing invalid arguments.

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 a specific action: 'composite workflow tool for opportunity and alpha screening across the current DeltaSignal issuer universe.' It distinguishes from siblings by emphasizing the server-enforced preset call plan (readiness, alpha_opportunities with limit 15, daily_changes), making it clear this is an aggregated sweep rather than a single-purpose tool.

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 invocation conditions: 'Use it when the user asks for alpha opportunities, opportunity sweep, clean alpha board, or names worth follow-up research.' It also warns against passing limit/offset/ticker/issuer filters because the preset owns arguments, and clarifies the result is a screen requiring issuer drilldown, implying when to switch to other tools.

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?

The description goes well beyond the annotations by explaining evidence-scoped behavior, Azure Blob resolution, TF-XBRL comparison, explicit ATLAS missing-evidence marking, and return of eight sections. It also clearly lists non-behaviors: no Grok calls, no invented evidence, no mutation, and no SEC-identity treatment.

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 dense sentences deliver the use case, parameter guidance, and behavioral constraints without redundancy. The description is front-loaded with the primary purpose and every 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?

Despite 25 parameters, the description plus full schema annotations and output schema provide a complete picture: when to use, what to pass, how it behaves, and what it returns. No critical gaps remain for an agent selecting or invoking this 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?

With 100% schema description coverage, the baseline is 3, but the description adds value by prioritizing the key parameters (article_tripcode/tripcode, optional prior_article_tripcodes, linked_xbrl_tripcodes, filing_tripcodes, ticker) and explaining the HUT seeded filing pack fallback. It could have clarified parameter relationships further, but the schema already carries the load.

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 identifies this as a read-only synthesis tool for producing the thesis map behind a DeltaSignal article TripCode. It names the specific resource (thesis map) and the input condition (subscriber provides TripCode), distinguishing it from sibling mapping/compare tools.

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?

It states the explicit trigger condition: when a subscriber gives Codex/Claude Code a DeltaSignal article TripCode and asks for the thesis map. It also gives parameter preferences and the HUT seeded fallback. However, it does not explicitly say when to use an alternative tool instead.

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?

Annotations already declare read-only, idempotent, and non-destructive behavior, but the description adds valuable context: it reads an artifact from Azure Blob, reports specific metrics, and 'does not run the audit, mutate data, or access raw issuer evidence.' 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.

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

The description is front-loaded with purpose, then details behavior and usage in three compact sentences. Every sentence carries meaningful information without redundancy or fluff, balancing detail with brevity.

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?

With no parameters, an output schema present, and annotations covering safety, the description is complete. It enumerates the exact fields reported (last successful run time, issuer count, failure counts, etc.), so an agent can confidently use the tool without further clarification.

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?

There are zero parameters, so schema coverage is irrelevant. The description explicitly states 'Parameters: none,' which reassures the agent that no input is required. This is appropriate for a zero-parameter tool, though it adds no extra semantics beyond the empty 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 opens with a specific verb and resource: 'check whether the Azure-native ATLAS-7 full-universe regression audit is healthy.' It clearly identifies the tool's scope (read-only audit status) and distinguishes it from sibling ATLAS-7 tools by focusing on audit health rather than candidate generation, search, or stress analysis.

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 usage context: 'Use this before trusting historical ATLAS-7 surfaces in an agent workflow or when an operator asks whether the nightly 215-issuer audit is current.' This tells the agent when to invoke the tool and what it does not do, making alternatives implicitly 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?

Annotations declare readOnlyHint, idempotentHint, and destructiveHint=false; the description reinforces this and adds domain-specific context: 'it has no destructive side effects and performs no wallet, settlement, or trading actions.' It also clarifies that it 'assembles one calculation-history row from the existing ATLAS-7 precomputed surfaces,' indicating no computation or side effects. This adds value beyond the generic hints.

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 compact—three sentences that cover purpose, components, parameters, behavior, and usage context. The first sentence is goal-oriented and each subsequent sentence adds distinct information without redundancy. The long component list is dense but necessary for completeness.

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 (8 parameters, many bundled surfaces), the description covers the essential context: what it does, how to filter (ticker/CIK/date range), what mode does, and its read-only safety profile. The existence of an output schema relieves it of explaining return values. It could mention limit/offset defaults, but the schema already covers those.

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 has 100% description coverage, but the description adds relational meaning: 'source_date replays one YYYY-MM-DD ATLAS-7 slice', 'source_date_from/source_date_to can page recent slices', and 'ticker or CIK narrows to one issuer.' It also explains the mode parameter's effect ('compact by default and full includes source_fields_json'). This goes beyond bare parameter names.

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 opens with a specific instruction: 'Use this read-only tool when agents need the complete ATLAS-7 calculation bundle for an issuer and source_date.' It names the resource ('complete ATLAS-7 calculation bundle'), the verb ('assembles'), and enumerates the included surfaces (covenant stress, company fundamentals, peer ranking, alpha signals, etc.). This distinguishes it from narrower sibling tools by emphasizing completeness and the historical, point-in-time context.

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?

It states when to use: 'when agents need the complete ATLAS-7 calculation bundle for an issuer and source_date' and 'Use this before historical report rendering so agents do not mix latest-only fields into a historical answer.' It does not explicitly name alternative tools or state when not to use it, but the historical-report context provides a clear usage boundary.

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?

Annotations already declare read-only, idempotent, and non-destructive hints; the description reinforces these and adds key behavioral context: it never returns the raw facts_payload and directs users to fact_source_pointer/evidence_hash for deeper inspection. 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.

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

The description is four dense sentences with no filler, front-loading the purpose, then parameters, behavior, and use case. Each sentence earns its place given the tool's 7 optional parameters.

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?

With an output schema present, the description doesn't need to detail return values. It covers the purpose, usage context, parameter behavior, and key constraints (no raw payload, universe size of 215), making it complete for a read-only retrieval 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 100%, so baseline is 3. The description adds valuable semantic context beyond schema by explaining source_date as replaying a materialization slice, ticker/cik narrowing to one issuer, limit capping at 250, and offset paginating. It does not mention mode or include_summary, but those are self-explanatory in 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 it retrieves compact SEC CompanyFacts/XBRL materialization rows for the crypto public-company universe, with a specific verb (retrieve) and resource. It distinguishes itself from sibling tools by specifying the issuer-level inventory and materialization slice concept.

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 says when to use this tool ('for Mirror Pulse or ATLAS-7 historical joins') and what to use instead for drilldown/audit (fact_source_pointer plus evidence_hash), providing clear alternatives and exclusions.

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?

Annotations already mark read-only, idempotent, and non-destructive, but the description adds substantial behavioral context: it does not fetch live market data, run ATLAS calculations, place trades, or mutate recorder state. It also explains the conceptual guarding behavior ('without promoting legacy compatibility scores or venue context into canonical truth'). This exceeds the annotation baseline.

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 well-structured: a purpose statement, a list of reported layers, a parameter summary, and behavioral notes. Every sentence earns its place, though the second sentence is slightly long and dense. It is appropriately sized for the tool's complexity and front-loaded with the primary use case.

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 output schema exists and the annotations cover safety, the description provides all necessary context: scope (single issuer or paginated universe), the four output levels, parameter options, pagination behavior, and explicit non-behaviors. It is complete for an agent to select and invoke the tool 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?

The schema already documents all six parameters with descriptions and constraints, providing 100% coverage. The description's parameter list adds no new semantic detail beyond what the schema provides. Baseline 3 is appropriate because the schema carries the burden and the description does not need to compensate.

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 the tool's purpose: determining which ATLAS-7 four-level layers are evidence-backed for one issuer or a paginated universe. It names the specific output levels (Level 1-4) and distinguishes itself from likely siblings by explicitly noting it does not promote legacy compatibility scores or venue context. This is a specific verb+resource+scope statement, with enough detail to differentiate from adjacent tools.

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 evidence-backed ATLAS-7 layer assessment on a single issuer or paginated universe, in read-only mode. It does not explicitly name alternative tools or state when not to use it, but the scope and behavior are well-defined. This earns a 4 rather than 5 due to the absence of explicit exclusions or alternative-tool references.

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?

Beyond annotations (readOnlyHint, idempotentHint), the description details that it performs one HTTPS read, has no destructive side effects, does not generate Natural Language, and never executes trades, wallets, or settlement flows. It also explains point-in-time recomputation logic and lookahead safety flags, adding significant behavioral context.

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 well-structured and front-loaded with purpose, then methodology, then parameters and behavior. It is somewhat long because it restates parameter names already present in the schema, but every sentence adds useful context, so it is not wasteful.

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 that an output schema exists and annotations are rich, the description covers purpose, methodology, behavior, and mode selection. It is complete enough for an agent to invoke the tool correctly without needing to infer additional context.

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?

With 100% schema description coverage, the baseline is 3. The description lists parameter names but adds no new semantic meaning beyond the schema, except for the 'mode' defaults and usage advice, which is already partially 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?

The description clearly states the tool returns daily ATLAS-7 CompanyFacts-derived factor rows keyed by as_of_date, with a specific methodology (filed <= as_of_date) that distinguishes it from other history tools. It also names concrete use cases (Mirror Pulse, backtests, agents), making the purpose unmistakable.

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?

It explicitly says to use this tool when Mirror Pulse, backtests, or agents need daily factor rows, giving clear context. It also provides mode selection guidance (compact for joins, full for audit pages) but does not name alternative tools or explicitly state when not to use it, so a 4 rather than 5.

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?

Beyond the read-only, idempotent, and non-destructive annotations, the description discloses that it performs one HTTPS read, has no destructive side effects, and does not apply the latest ATLAS snapshot retroactively across history. This is substantive behavioral context that helps an agent anticipate side effects and temporal semantics.

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 organized into purpose, return shape, parameters, behavior, and use cases in a compact paragraph. Each sentence adds distinct value and front-loads the most important information.

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 rich input schema, annotations, and output schema, the description adequately covers purpose, return row content, parameter semantics, behavior, and use cases. It is complete for an agent to select and invoke the tool 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?

The input schema has 100% description coverage with detailed parameter descriptions, including defaults/caps, date formats, and inclusive bounds. The tool description only summarizes these parameters and adds no additional semantic detail, so the baseline of 3 is appropriate.

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 identifies a specific verb ('retrieve'), a resource ('historical ATLAS-7 covenant and stress series'), and a scope ('one crypto public company ticker'). It distinguishes this tool from sibling tools by emphasizing dated ATLAS source-date rows and mNAV/Mirror Pulse joins.

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?

It explicitly states when to use the tool: historical ATLAS data, MSTR/Strategy time series, mNAV backtests, Mirror Pulse joins, and dated stress/risk snapshots. It does not name sibling alternatives or when-not conditions, so the guidance is clear but not comparative.

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?

Annotations already declare readOnly, idempotent, and non-destructive. The description adds valuable context by specifying the data source (persisted recorder evidence), the output's venue-pure nature, and explicit exclusions (no live exchange data, no trading, no recorder mutation). This goes beyond the annotations but does not mention error conditions 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 three sentences with no fluff: it front-loads the purpose, summarizes return content, lists parameters, and clarifies behavior. Every 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?

Given the output schema exists and annotations cover safety, the description is complete. It explains the tool's scope, output composition, parameter options, and non-behaviors, making it sufficient for an agent to select and 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 description coverage is 100%, and the description merely lists parameter names and modes without adding deeper meaning. The schema already documents each parameter well, including examples, so the description adds little beyond restating them.

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 the tool retrieves Coinbase INTX perp market-factor history from persisted recorder evidence, with a specific listing of returned fields (contract identity, ATLAS-shaped factors, deltas, quality state). This distinguishes it from siblings like deltasignal_coinbase_perp_factors or deltasignal_coinbase_perp_rankings by emphasizing calculation-history rows.

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 for use: a read-only historical retrieval tool that does not fetch live data or place trades. However, it does not explicitly name alternative tools or provide when-not-to-use conditions, 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.

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

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description adds meaningful context: it returns 'additive curated constituent overlays grouped by source date', preserves the 'evidence boundary' of persisted registry rows, and explicitly states it does not fetch live exchange data, place trades, or mutate recorder state.

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, front-loaded with the core purpose, and every sentence conveys essential information without 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?

Given the read-only nature, the presence of an output schema, and rich annotations, the description covers the necessary behavioral constraints, parameter options, and evidence-boundary nuance. It is complete for an agent to select and invoke the tool 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 description coverage is 100%, so each parameter is already documented. The description restates required product and optional filters (source_date, source_date_from/to, mode, limit, offset) but does not add 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.

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

The description states a specific verb+resource: 'retrieve persisted constituent registries for one Coinbase thematic or index perp product'. It also distinguishes itself by clarifying these are 'persisted registry rows rather than live exchange-native constituent APIs', which differentiates 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.

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

The description clearly establishes when to use the tool ('Use this read-only tool...') and excludes live data fetching, trade placement, and recorder mutation. However, it does not explicitly name alternative tools for those use cases, 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.

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is known. The description adds valuable context beyond annotations: it explicitly states the tool 'does not fetch live exchange state or write recorder artifacts on demand,' and clarifies that the data is 'persisted' and 'venue-pure.' This enriches the behavioral model without contradicting 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.

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

The description is compact (four sentences) and well-structured: opening use-case statement, return content, parameter overview, and behavioral note. It front-loads the most important information and avoids redundancy with the schema. Every sentence contributes useful context, making it a model of concise tool documentation.

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 has a rich output schema and fully documented parameters, the description need not repeat return details. It covers the core purpose, output components, optional modes (compact/full), and behavioral constraints. Minor gaps remain, such as not clarifying the relationship between source_date and source_date_from/to, but overall it is sufficiently complete for an agent to invoke the tool 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 description coverage is 100%, and each parameter already has a detailed description in the schema. The description merely lists parameter names (product, source_date, source_date_from/to, underlying_ticker, mode, limit, offset) without adding new semantics, such as mutual exclusivity or mode differences. Baseline 3 is appropriate because the schema carries the parameter documentation burden.

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 uses a specific verb ('returns') and resource ('persisted Coinbase INTX market-factor history for one perp product'), and lists concrete output contents (factor rows, deltas, quality state, optional full market inputs or lineage). It clearly distinguishes this tool from sibling tools like calculation_history or rankings by emphasizing 'venue-pure factor history' for a single product.

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?

It opens with an explicit when-to-use statement: 'Use this read-only tool when the user wants persisted Coinbase INTX market-factor history for one perp product.' It also clarifies what it does not do (fetch live exchange state, write recorder artifacts). However, it does not name alternative sibling tools or provide explicit when-not-to-use guidance, so it falls just short of a full 5.

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?

Annotations already declare readOnly, idempotent, and non-destructive; the description adds specific behavioral detail by describing the transformation ('converts persisted market-factor history into field pressure...') and explicitly stating what it does NOT do (create factors, reconstruct depth, override rows). This adds substantial context beyond the generic hints.

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 compact and front-loaded. It states the purpose, then the process, then parameters, then behavior, without redundant or unnecessary sentences. Every phrase adds value.

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 output schema exists, return values need not be described. The description covers purpose, transformation, parameter summary, and limitations (read-only, no side effects). It is complete for an agent to select and invoke the tool 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?

All 6 parameters have detailed schema descriptions, so the baseline is 3. The description adds a useful clarification that source_date is an alternative to source_date_from/source_date_to, implying mutual exclusivity, which is not explicitly stated in the schema. This small addition justifies a 4.

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 a specific action ('retrieve the market SPECTRA field map') and a specific resource ('one Coinbase INTX perp product'). It distinguishes from siblings by emphasizing the Coinbase perp-focused scope and the conversion process into labels.

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 opening 'Use this read-only tool to...' provides clear context for when to use it. It also includes exclusions via 'does not create factors, reconstruct missing depth, or override the underlying factor rows,' but it does not explicitly name alternative tools or contrast with siblings.

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?

Although annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, the description adds valuable context: 'read-only and idempotent with no destructive side effects; it performs no live exchange fetches, order placement, or settlement flows.' This goes beyond annotations by explicitly reassuring the agent that no live market interactions occur, which is important for a ranking tool. It also mentions 'latest persisted market_alpha row' and output fields, further clarifying behavior.

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: purpose, return shape, and parameters/behavior. It is front-loaded with the most important information, and every sentence earns its place. No unnecessary detail or repetition of the title.

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 covers the tool's core function, output structure, filter options, and safety profile. Since an output schema exists, return values are already documented, so the description does not need to list every field. It is sufficiently complete for an agent to decide when and how to invoke this tool, given the rich schema and annotations.

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% and every parameter has a description. The description simply lists the parameter groups ('optional product or underlying_ticker filters, source_date or source_date_from/source_date_to, mode=compact|full, limit, and offset') without adding new meaning or clarifying relationships beyond the schema. This meets the baseline but does not elevate it.

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 the tool's purpose: 'rank Coinbase INTX perp products by the latest persisted market_alpha row per product.' It uses a specific verb ('rank') and resource ('Coinbase INTX perp products'), and the unique focus on 'latest persisted market_alpha row' and the ranking board output distinguishes it from siblings like deltasignal_coinbase_perp_factors or peer_ranking.

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 provides clear context by saying 'Use this read-only tool to rank...' and enumerates optional filters and modes, implying when it's appropriate. It does not explicitly name alternatives or exclusions (e.g., when to use a different rankings tool), but the context is sufficient for an agent to infer typical use cases.

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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, but the description adds valuable specificity: it 'performs one HTTPS read, has no destructive side effects, and does not modify SEC data, accounts, files, or wallets.' It also clarifies that optional containers return availability metadata when facts are not populated, which is useful behavioral context. 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.

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

The description is organized into clear, purposeful sentences: purpose, returned content, parameters, behavior, and usage guidance. It is front-loaded with the main action and avoids fluff. Though slightly longer than minimal, each sentence contributes meaningful information, so it earns a 4 rather than a 5.

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 presence of a comprehensive output schema, detailed parameter descriptions, and a simple read-only tool, the description is complete. It covers what data is returned, when to use the tool, optional parameter behavior, safety guarantees, and directs to alternatives for different use cases. No critical missing context.

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%, with detailed descriptions and examples for all four parameters. The description summarizes parameter roles (e.g., 'ticker is required; period is optional YYYY-MM-DD; include_segments and include_related_party request additional containers') but largely restates schema information without adding new semantic value. Baseline of 3 is appropriate.

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 'retrieve[s] SEC XBRL-backed fundamentals for one crypto public company ticker,' specifying the exact verb, resource, and scope. It also explicitly lists the returned content (filing period, identifiers, filing form, core financial values, provenance) and distinguishes itself from modeled signal tools by indicating 'alpha_signals or covenant_stress' for those use cases.

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?

Explicit usage guidance is provided: 'Use it when the user asks for revenue, net income, assets, cash, liabilities, equity, SEC filing context, or fact provenance; use alpha_signals or covenant_stress for modeled signal interpretation.' This clearly states when to use this tool and names specific alternative tools, leaving no ambiguity.

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?

Even though annotations already provide readOnlyHint, idempotentHint, and destructiveHint, the description adds valuable context: 'performs six internal HTTPS reads, has no destructive side effects, rejects invalid tickers before fan-out, and preserves partial results if a required issuer leg fails.' It also clarifies SPECTRA inclusion logic, which goes 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.

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

The description is longer than average but appropriately so for a composite workflow. It is front-loaded with the core purpose, then covers parameters, behavior, and usage in a logical sequence. Each sentence provides specific information; no wasted words.

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, the presence of an output schema (so return values need not be explained), and rich annotations, the description is complete. It covers purpose, parameter semantics, internal behavior, error handling, partial results, and use cases. The agent has all necessary context to invoke it 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?

The schema already has 100% coverage with descriptions for each parameter. The tool description adds extra meaning by explaining that period is passed to fundamentals, peer ranking, and covenant stress, and that include_segments/include_related_party request containers from company_fundamentals. This enhances the schema without being redundant.

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 this is a read-only composite workflow tool for the default full single-issuer DeltaSignal ATLAS-7 company report. It enumerates the included components (readiness, company_fundamentals, alpha_signals, etc.) and explicitly contrasts with low-level tools for custom drilldowns, making it distinguishable 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.

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

The description provides explicit when-to-use guidance: 'Use it when the user asks for a report, deep dive, issuer brief, or diligence package on one crypto public-company ticker, or when a Morning Brief top-stressed or alpha-screen row needs a separately sold explanation report.' It also states the alternative: 'use low-level tools only for custom drilldowns.' This clearly orients the agent.

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?

Beyond the annotations, the description discloses idempotent and local MVP behavior, absence of destructive side effects, no SEC identity minting, no inference from prose, and no wallet/x402 calls. It also summarizes the returned packet structure, giving a complete behavioral picture.

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 well-organized sentences: purpose, parameters, and behavior. It is front-loaded with the core action and every sentence adds distinct value without filler or repetition.

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 18 parameters, an existing output schema, and rich annotations, the description covers the essential context: what the tool compares, how to invoke the default HUT scenario, key limits, and what the response contains. The schema fills in the remaining parameter details.

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 schema already describes all 18 parameters, so the baseline is 3. The description adds meaningful semantics for article_tripcode, filing_tripcodes, and the ticker=HUT default behavior, going beyond what the schema states without needing to repeat every field.

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 opens with a specific verb and resource: 'compare a TF-SUB article node against resolved TF-XBRL filing evidence objects.' It clearly identifies the input types and the read-only nature, which differentiates it from general-purpose comparison tools and aligns with the tool name.

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 provides explicit invocation guidance: article_tripcode is optional, filing_tripcodes can list one or more TF-XBRL objects, and ticker=HUT with no filing_tripcodes loads the default pack. It lacks an explicit 'when not to use' or direct comparison against sibling tools, but the usage context is 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?

The description adds valuable behavioral details beyond the annotations, such as the possible return states (confirmed, weakened, unresolved, new_claim) and the guarantee that it won't invent evidence. This goes beyond the readOnly/idempotent hints already provided.

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 covering purpose, parameters, and behavior, with no redundant or irrelevant information. It is front-loaded with the core purpose.

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 14-parameter tool with full schema descriptions, the description covers the core usage scenario and return categories. It doesn't elaborate on every optional filter, but the schema handles those details, and an output schema exists, so return structure isn't needed.

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 description highlights the relationship between parameters (claim_text or query, plus river_tripcode or issuer), which is not obvious from the individual schema descriptions. This provides logical grouping that aids correct invocation.

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 the tool compares a claim to River claim records and evidence refs, using a specific verb ('compare') and resource. It doesn't explicitly differentiate from sibling tools like deltasignal_compare_article_to_filing_evidence, but the claim-based focus is distinct.

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