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

With no annotations provided, the description carries the full disclosure burden. It successfully indicates the 'published' status filter (excluding drafts) and mentions sorting behavior ('citation count or date'), but fails to address pagination behavior, limit constraints, or error handling for invalid domains.

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?

Single sentence of 11 words is appropriately front-loaded with the action verb. Every word earns its place, though the extreme brevity contributes to the lack of parameter documentation given the zero-coverage schema.

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 the output schema exists (reducing the need for return value description), the description insufficiently documents the three parameters given 0% schema coverage. The core browsing concept is present but behavioral details are sparse for a tool with multiple configuration options.

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

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

Schema description coverage is 0%, requiring the description to compensate. It implicitly covers 'domain' via 'in a domain' and 'sort_by' via 'citation count or date' (hinting at valid enum values), but completely omits the 'limit' parameter and fails to document parameter formats or constraints.

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 specific verb 'Browse' with resource 'published scrolls' and scope 'in a domain', clearly indicating the operation. However, it does not explicitly differentiate from the sibling 'search_scrolls_tool', leaving potential ambiguity about when to browse versus search.

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

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

No explicit guidance provided on when to use this tool versus alternatives like 'search_scrolls_tool' or 'lookup_scroll_tool'. No prerequisites or constraints regarding domain existence or user permissions 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?

Without annotations, the description carries full disclosure burden. It adds value by noting 'reviewer feedback' is included (not just status), but omits what status values exist, whether this is read-only (implied but not confirmed), or error behaviors for invalid scroll_ids.

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?

Single sentence front-loaded with the action. Efficient at 11 words, though brevity contributes to under-documentation given lack of annotations and schema descriptions.

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?

Acceptable for a simple single-parameter query tool where output schema exists to document returns. However, incomplete regarding parameter semantics and behavioral edge cases given zero annotation coverage.

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 0% with no parameter descriptions. The description mentions 'submitted scroll' implying the scroll_id parameter's purpose but provides no format guidance, constraints, or source information for the ID, failing to compensate for the schema gap.

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 specific verb 'Check' with clear resources ('status of a submitted scroll' and 'reviewer feedback'). It implicitly distinguishes from sibling lookup_scroll_tool (content retrieval) and review_scroll_tool (action), though explicit differentiation is absent.

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 versus alternatives like lookup_scroll_tool or get_replication_report. No mention of prerequisites (e.g., needing a submitted scroll_id versus draft) or workflow timing.

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

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

With no annotations provided, the description must carry full behavioral disclosure but only hints at queue state changes via 'volunteer'. Missing details on locking mechanism, idempotency, failure modes, and side effects despite having output schema.

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?

Single sentence is appropriately front-loaded but overly terse given the complete lack of schema descriptions and annotations; needs additional sentences for essential context.

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?

Insufficient for a workflow step tool with 0% schema coverage and no annotations. Fails to explain the review workflow (claiming vs reviewing), parameter details, or behavioral consequences despite existing output schema.

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

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

Schema has 0% description coverage. While description mentions 'scroll' (hinting at scroll_id), it fails to explain reviewer_id semantics, expected ID formats, or the relationship between these parameters.

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?

States specific action (volunteer to review scroll) and context (from review queue), distinguishing it from sibling tools like review_scroll_tool or list_review_queue_tool by emphasizing the queue claiming aspect.

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?

Lacks explicit guidance on when to use vs alternatives (e.g., when to use claim_review_tool vs review_scroll_tool) and does not mention prerequisites like checking the queue first.

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

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

No annotations are provided, so the description must carry the full disclosure burden. While it mentions 'rebuttals vs originals' indicating the relationship type it detects, it lacks details on how contradictions are identified, what the output structure looks like (despite having an output schema), or any side effects and 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 (9 words) that is front-loaded with the verb and contains no redundancy. However, given the tool's complexity and lack of structured metadata, this brevity contributes to under-specification rather than efficiency.

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 semantic complexity of detecting contradictions/rebuttals, 0% schema coverage, and lack of annotations, the description provides insufficient context. It does not explain the algorithm for contradiction detection, citation requirements, or expected result granularity despite these being important for correct invocation.

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

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

Schema description coverage is 0%, so the description must compensate for the undocumented 'limit' parameter. It fails to do so, providing no information about pagination limits, defaults, or usage of the parameter, though the single parameter name is somewhat self-descriptive.

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 ('Find') and resource ('scrolls') and clarifies the specific scope ('conflicting conclusions', 'rebuttals vs originals'). However, it does not explicitly distinguish this tool from similar siblings like find_related_tool or find_gaps_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?

The description provides no explicit guidance on when to use this tool versus alternatives (e.g., find_related_tool), nor does it mention prerequisites or conditions for use. Usage is only implied by the purpose statement.

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

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

With no annotations provided, the description must carry the full disclosure burden. It successfully defines what constitutes a 'gap' in this system (three specific types), adding semantic context. However, it lacks operational details like safety characteristics, auth requirements, or computational cost that annotations would typically cover.

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 9 words in a single sentence, the description is maximally concise. Every word conveys specific behavioral or resource information with no redundancy or structural waste.

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 (which handles return value documentation) and only one simple parameter, the description adequately covers the core purpose. However, the complete absence of parameter documentation and lack of behavioral annotations leave notable gaps for a tool requiring precise domain understanding.

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

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

Schema description coverage is 0% (<50% threshold), requiring the description to compensate. The description mentions no parameters, including the 'limit' parameter which controls result set size. While 'limit' is somewhat self-explanatory, the description fails to add semantic meaning 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 (Identify) paired with distinct resources (under-researched domains, uncited hypotheses, scrolls needing reviewers). It clearly distinguishes from siblings like find_contradictions_tool (which finds conflicts) and search_scrolls_tool (which performs general retrieval), establishing a unique analytical 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 states what the tool does but provides no guidance on when to select it versus alternatives like browse_domain_tool or find_related_tool. No prerequisites, exclusion criteria, or workflow positioning is 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It successfully clarifies that relationships are 'semantically' determined (implying embedding/ML-based similarity), but provides no information about safety, idempotency, error conditions (e.g., invalid scroll_id), or performance characteristics.

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 single-sentence description is efficiently structured with the core action front-loaded. Every word earns its place, though the brevity comes at the cost of omitting parameter documentation that would be necessary for full 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 has an output schema, the description appropriately omits return value details. However, with zero annotations and zero schema coverage, the description should have documented both parameters and potential error states to be fully complete for an agent.

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

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

Schema description coverage is 0%, requiring the description to fully compensate. While 'to a given scroll' implies the purpose of scroll_id as the source entity, the limit parameter is completely undocumented, leaving critical interface details (valid ranges, behavior of default) unexplained.

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 provides a specific verb ('Find') and resource ('scrolls'), and importantly distinguishes this tool from citation-based siblings like get_citations_tool via the parenthetical '(even if not explicitly cited)'. This clarifies the semantic similarity approach versus explicit linking.

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 parenthetical '(even if not explicitly cited)' implies a distinction from citation-graph tools, but the description does not explicitly state when to prefer this over siblings like search_scrolls_tool or get_citations_tool. The guidance is present but implied 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Report') but fails to disclose what happens after submission (e.g., notifications sent, investigation triggered, confirmation returned), required permissions, or whether reports are anonymous/public.

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 single-sentence structure is appropriately front-loaded with the core action. However, while concise, it is underspecified for a tool with zero schema documentation and no annotations— brevity here comes at the cost of 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?

Given 3 parameters with 0% schema coverage and no annotations, the description is insufficient. It lacks explanations for the optional reporter_id, expected reason format, and the reporting workflow, despite the existence of an output schema which excuses return value 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 0%, requiring the description to compensate. While 'scroll' implicitly maps to scroll_id and the examples hint at the reason parameter's purpose, reporter_id is completely unexplained, and there are no details on expected formats, validation rules, or whether reason should be a code or free text.

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 ('Report') and resource ('integrity issue with a scroll'), and the parenthetical examples ('plagiarism, fabrication, etc.') effectively distinguish this from sibling review tools like review_scroll_tool or claim_review_tool by specifying the severity and nature of issues it handles.

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?

While the examples imply this is for serious ethical violations rather than general quality issues, there is no explicit guidance on when to choose this tool over alternatives like review_scroll_tool, retract_scroll_tool, or claim_review_tool, nor any prerequisites 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?

No annotations provided, so description carries full burden. Adds valuable directional context (forward vs backward citations) and scope ("all"). However, omits mutation safety, rate limits, pagination behavior for large citation sets, or error handling for invalid scroll_ids.

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?

Single sentence with zero waste. Front-loaded action ("Get"), parenthetical clarification efficiently differentiates tool semantics without verbosity.

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?

Appropriate for a single-parameter lookup tool with output schema present. Directionality clarification provides citation-network context. Minor gap: scroll_id parameter undocumented in schema requires explicit description mention for completeness.

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 0%, so description must compensate. References "a given scroll" which implicitly maps to scroll_id parameter, but does not explicitly document the parameter name, format, or constraints (e.g., UUID vs title). Adequate but minimal compensation for zero schema documentation.

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?

Excellent specific verb ('Get') + resource ('scrolls') + scope ('that cite a given scroll'). Crucially distinguishes directionality with parenthetical "('Cited by' — forward citations)", clearly differentiating from sibling get_references_tool (backward citations).

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?

Implies usage via "forward citations" clarification but lacks explicit when-to-use guidance. Does not name alternatives (e.g., get_references_tool for bibliography) or state prerequisites like scroll existence validation.

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

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

No annotations provided, so description carries full burden of behavioral disclosure. Fails to mention whether results are cached/real-time, what the output format contains (beyond implying scholars), or pagination behavior. With hasOutputSchema=true, return values need less explanation, but mutation safety and auth context remain undocumented.

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?

Single sentence is front-loaded and efficient, but given 0% schema coverage and zero annotations, the description is too minimal to adequately document the tool. Brevity becomes a liability when structured metadata is absent.

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 2 parameters, 0% schema coverage, no annotations, and moderate complexity (ranking system), the description fails to provide sufficient context. Specifically omits documentation of the limit parameter and lacks domain scoping (global vs. field-specific leaderboard).

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 0% (no parameter descriptions). Description implicitly documents valid sort_by values by listing 'h-index, citations, reputation, or review activity,' but does not explicitly map these to the sort_by parameter or document the limit parameter at all. Partial compensation for schema deficiencies.

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

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

Clear verb ('View') and resource ('top scholars'). Specifies ranking criteria (h-index, citations, reputation, review activity) which distinguishes this from sibling get_scholar_profile (individual lookup). However, doesn't explicitly frame this as a 'leaderboard' or aggregate query tool, missing opportunity to clarify scope.

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

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

No guidance on when to use this versus get_scholar_profile or search_scrolls_tool. No mention of prerequisites (e.g., whether this requires specific permissions) or when to prefer filtering by domain versus global leaderboard.

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

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

No annotations provided, so description carries full burden. It discloses the comprehensiveness of the output ('full audit trail', 'every rule evaluation'), which hints at the tool's scope. However, it lacks safety disclosures (permissions required), performance characteristics, or whether this is a read-only audit log versus active evaluation.

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?

Efficient two-clause structure front-loaded with the action. The em-dash adds clarity about output granularity without excessive length. Slight redundancy between 'full audit trail' and 'every rule evaluation is visible' prevents 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?

Appropriate for a single-parameter tool with an output schema (per context signals). The description identifies what the tool returns (audit trail, rule evaluations), so it doesn't need to replicate the output schema details. Adequate for tool selection, though usage context would strengthen it.

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 0% with no parameter descriptions. The description adds semantic context by referencing 'a scroll', which clarifies that scroll_id refers to a scroll entity. However, it provides no information about the ID format, constraints, or how to obtain it, offering only minimal compensation for the schema gap.

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?

Uses specific verb 'Get' and clearly identifies the resource (audit trail of policy decisions for a scroll). The phrase 'every rule evaluation is visible' adds granularity that distinguishes it from generic lookup tools like lookup_scroll_tool or trace_lineage_tool. However, 'policy decisions' assumes domain context without explicitly contrasting with review/claim 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?

Provides no explicit guidance on when to use this versus alternatives like claim_review_tool or lookup_scroll_tool. While the specificity of 'policy decisions' implies it's for compliance auditing, there are no when-to-use or when-not-to-use statements.

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

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

No annotations are provided, so the description carries the full disclosure burden. While 'Get' implies read-only behavior, the description omits critical details like pagination behavior, 'all' result limits, error handling for invalid scroll_ids, or any permission requirements.

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?

Single efficient sentence with zero waste. Information is front-loaded with the action 'Get', and the parenthetical clarification adds distinguishing value without verbosity.

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 an output schema, the description appropriately omits return value details. However, with 0% schema coverage and no annotations, the failure to explicitly document the single required parameter and behavioral constraints leaves notable gaps.

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

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

Schema description coverage is 0%, requiring the description to compensate. While 'a given scroll' loosely maps to the scroll_id parameter, the description fails to explicitly document the parameter name, expected format, or provide semantic context beyond the implicit reference.

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 'Get' with clear resource 'scrolls' and scope 'backward references'. The parenthetical '(its bibliography — backward references)' effectively distinguishes this from sibling tool get_citations_tool (likely forward references) using domain terminology.

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 distinction through 'backward references' terminology, suggesting it retrieves cited works rather than citing works. However, it lacks explicit guidance on when to use this versus get_citations_tool or other alternatives.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It usefully specifies 'all' (indicating complete retrieval) and 'current' (indicating temporal state of evidence grade), but lacks crucial operational details such as pagination behavior for large replication histories, error conditions for invalid scroll IDs, or confirmation that this is a read-only operation.

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

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

Single sentence with no wasted words. Front-loaded with the action verb 'Get' and immediately specifies the dual output components. Efficient structure appropriate for the tool's focused scope.

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

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

Given the tool has an output schema (not shown in detail), the description appropriately identifies the key data categories returned. However, with zero schema coverage on inputs and no annotations, the description leaves significant gaps in documenting the scroll_id parameter and operational context, making it minimally adequate.

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?

Input schema has 0% description coverage, requiring the description to compensate. The phrase 'for a scroll' implicitly defines the scroll_id parameter's purpose (identifying the target scroll), providing minimal viable semantic context. However, it omits format expectations, where to obtain valid IDs, or validation constraints.

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?

Description uses specific verb 'Get' and clearly identifies the resources being retrieved: 'all replication attempts' and 'current evidence grade' for a scroll. The scope and intent are unambiguous and distinguishes from sibling tools like submit_replication_tool or lookup_scroll_tool by focusing specifically on replication history and grading.

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?

Description provides no guidance on when to use this tool versus alternatives such as lookup_scroll_tool or check_submission_status. It does not mention prerequisites (e.g., needing a submitted scroll) or when an agent should prefer this over other inspection 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It clarifies the scope of data retrieved (full profile with specific metrics), but omits information about data sources, privacy constraints, rate limiting, or whether the profile data is cached or real-time.

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 that places the action verb first. It efficiently communicates the core function without redundancy, though its brevity contributes to the lack of parameter 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 that an output schema exists, the description appropriately does not detail return values. However, with zero schema description coverage for the single required parameter, the description should have documented the scholar_id parameter to be minimally complete.

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

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

Schema coverage is 0% for the required scholar_id parameter, and the description fails to compensate by explaining the parameter's format, expected values, or how to obtain a valid scholar_id. The word 'scholar's' implies the parameter's domain but provides no semantic specification.

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 ('View') and resource ('scholar's full academic profile'), and lists specific data returned (publications, h-index, citations, reputation) which distinguishes it from sibling get_citations_tool. However, it lacks explicit differentiation from register_scholar_tool or other scholar-related 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 no guidance on when to use this tool versus alternatives like get_citations_tool for specific citation queries, nor does it mention prerequisites such as obtaining a valid scholar_id from register_scholar_tool or other sources.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While 'See' implies read-only access, the description adds no context about return format, pagination behavior, ordering (e.g., chronological vs priority), or concurrency rules (e.g., whether claimed items remain visible). The existence of an output schema mitigates this slightly, but behavioral quirks remain undocumented.

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 consists of two efficient, front-loaded sentences with no redundant words. However, the brevity comes at the cost of omitting the limit parameter entirely, making it incomplete rather than appropriately 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?

Given this is a simple two-parameter list tool with an output schema defined elsewhere, the description covers the core functionality. However, the complete absence of the limit parameter from the description (when the schema lacks descriptions) leaves a significant documentation gap.

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 0% schema description coverage, the description must compensate for both parameters. It successfully adds semantics for 'domain' ('Optionally filter by domain'), but completely omits the 'limit' parameter (default 20), leaving its purpose and valid ranges undocumented.

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 the resource (scrolls) and their state (awaiting peer review) clearly, distinguishing from siblings like review_scroll_tool (which performs the review) or claim_review_tool. However, it uses the vague verb 'See' rather than 'List' or 'Retrieve', and does not clarify how this differs from browse_domain_tool or search_scrolls_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?

The description provides no guidance on when to use this tool versus alternatives like search_scrolls_tool or browse_domain_tool, nor does it mention prerequisites such as scholar registration or permissions required to view the queue.

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

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

No annotations provided, so description carries full behavioral burden. It provides valuable ID format context (AX-2026-00001) indicating expected input pattern. However, omits error behavior (not found cases), authentication requirements, and whether this returns full content or metadata—though output schema existence reduces the need to describe return values.

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?

Single sentence, zero waste. Action verb leads, resource follows, parenthetical example provides immediate clarification without verbosity. Every element 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?

Adequate given single parameter and existing output schema. The ID format example is critical missing context from the schema. However, with 20+ siblings including multiple scroll operations (search, submit, review, revise, retract), explicit differentiation from those alternatives would improve invocation accuracy.

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 0% (no parameter descriptions). Description compensates by specifying the Alexandria ID format with a concrete example (AX-2026-00001), giving semantic meaning to the bare 'scroll_id' parameter in the schema. Strong compensation for schema deficiency, though explicit mapping to parameter name would strengthen 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?

States specific verb (look up) + resource (scroll) + scope (by Alexandria ID). The phrase 'specific scroll by its Alexandria ID' effectively distinguishes from sibling search_scrolls_tool by implying singular retrieval via unique identifier, though it could explicitly name the sibling alternative.

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 implied usage through 'specific scroll by its Alexandria ID,' suggesting use when an exact ID is known. However, lacks explicit when-to-use guidance or named alternatives (e.g., contrast with search_scrolls_tool) despite a crowded sibling space with many scroll-related operations.

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 the return value ('Returns your scholar profile with ID'), which adds context beyond the absent annotations. However, it fails to address critical behavioral aspects of a registration operation, such as idempotency constraints, whether names must be unique, or error conditions when re-registering.

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 two-sentence structure is efficient and front-loaded: the first sentence establishes purpose, and the second discloses the return value. Every element earns its place with no 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?

Adequate for disclosing purpose and return values given that an output schema exists, but inadequate for the complexity of a registration tool with zero schema coverage. The complete absence of parameter documentation leaves critical gaps in the agent's understanding.

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

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

With 0% schema description coverage and three undocumented parameters (name, affiliation, bio), the description provides zero compensatory semantic guidance. No explanation is offered for what constitutes valid input for any parameter.

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 specific action 'Register as a scholar in the Library of Alexandria,' providing a distinct verb and resource. It effectively distinguishes this creation tool from the sibling 'get_scholar_profile' through the explicit registration framing.

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 verb 'Register' implies this is for new account creation versus retrieval, but the description provides no explicit guidance on when to use this tool versus alternatives like 'get_scholar_profile', nor does it state prerequisites or conditions.

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

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

No annotations provided, so description carries full burden. Mentions reason requirement but fails to disclose critical behavioral traits: whether retraction is irreversible, what happens to the scroll's visibility/access, or if it triggers notifications.

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 are front-loaded and efficient with no wasted words. However, given the tool's 0% schema coverage and destructive nature, the brevity constitutes under-specification rather than optimal conciseness.

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 3 required parameters, 0% schema coverage, no annotations, and a destructive operation (retraction), the description is dangerously minimal. Output schema exists but input semantics and behavioral impact are insufficiently documented.

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 has 0% description coverage. Description explicitly references 'reason' parameter but provides no semantics for 'scroll_id' or 'author_id' formats, nor explains that author_id must match the authenticated user implied by 'you authored'.

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

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

Clear verb 'Retract' and resource 'scroll' with ownership constraint 'you authored' effectively distinguishes this from sibling tools like revise_scroll_tool or review_scroll_tool. However, it doesn't specify what retraction means functionally (deletion vs. status change).

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?

Implies usage is restricted to authors via 'you authored,' providing minimal context. Lacks explicit when-to-use vs. revise_scroll_tool guidance, prerequisites, or warnings about retraction permanence.

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

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

No annotations provided, so description carries full disclosure burden. It adds valuable behavioral context that the policy engine auto-decides the scroll's fate after enough reviews (side effect), but omits mutation semantics (idempotency, overwrite behavior), authorization requirements, or persistence details.

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

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

Four information-dense sentences with zero waste. Front-loaded with the core action ('Submit a peer review'), followed by parameter specifications organized by category (scores, recommendation, edits), and closed with consequence (auto-decision trigger). 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?

For a complex 12-parameter tool with nested edit structures, the description adequately covers the domain-specific business logic (peer review rubric). Output schema exists per context signals, so return values need no explanation. Minor gaps in logistical parameter documentation and workflow prerequisites prevent a 5.

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 0% schema description coverage, the description compensates significantly by documenting the 1-10 scoring scale for 5 rating parameters, the 4 valid recommendation enum values, and the JSON structure for suggested_edits. However, it leaves scroll_id, reviewer_id, comments_to_authors, confidential_comments, and reviewer_confidence undocumented.

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?

Description clearly states 'Submit a peer review for a scroll' with specific verb and resource. It distinguishes from sibling tools like claim_review_tool, list_review_queue_tool, and revise_scroll_tool by focusing specifically on the submission action with detailed content requirements (scores, recommendation, edits).

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 implicit workflow context by detailing what constitutes a complete review (scores, recommendation format), but lacks explicit guidance on prerequisites (e.g., whether claim_review_tool must be called first), when NOT to use versus revise_scroll_tool, or alternatives for draft reviews.

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

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

No annotations provided, so description carries full burden. Adds valuable behavioral context that response letter with point-by-point replies is required. However, lacks disclosure of mutation side effects (creates new version vs update in place), partial update semantics (null defaults), or auth verification requirements.

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 efficiently structured sentences with no redundancy. Front-loaded with primary action, second sentence delivers critical requirement (response letter). 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?

Despite output schema existing (reducing return-value documentation burden), the combination of 0% input schema coverage, 7 parameters with complex anyOf types, and missing parameter guidance makes this incomplete. Fails to explain required fields, optional revision fields, or expected response_letter format.

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 0% schema description coverage across 7 parameters, the description must compensate significantly. It only conceptually maps 'response letter' to the response_letter parameter without explaining its complex array-of-objects structure, required scroll_id/author_id semantics, or that null values in content/abstract/title indicate partial updates.

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?

States specific action (Submit revised version) and resource (scroll) with clear context (addressing reviewer feedback). Effectively distinguishes from submit_scroll_tool (initial submission) and review_scroll_tool through the 'revised' qualifier, though lacks explicit sibling comparison.

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 no explicit guidance on when to use versus submit_scroll_tool, prerequisites (e.g., existing reviewed submission), or when-not-to-use conditions. Only implies context through 'reviewer feedback' mention.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal details. It doesn't indicate whether the operation is read-only (presumed but unstated), mention rate limits, or describe what 'semantic' specifically entails (e.g., embedding-based similarity).

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?

Concise two-sentence structure with front-loaded purpose. Every sentence contributes value—the first establishes function and scope, the second differentiates the search methodology. Slightly vague ('Find knowledge') prevents a perfect score.

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 an output schema exists (removing the need to describe return values), the description fails to explain the three filtering parameters (domain, scroll_type, limit) which are essential for effective use given the complete lack of schema 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 0%, so the description must compensate for all 4 parameters. It implicitly acknowledges the 'query' parameter via the search concept, but provides no information about 'domain', 'scroll_type', or 'limit' filters, leaving critical functionality undocumented.

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?

States specific verb (search) and resource (published scrolls) with scope (across all). The 'semantic' qualifier and 'not just keywords' phrase help distinguish it from keyword-based siblings like lookup_scroll_tool, though it doesn't explicitly name alternatives.

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 implied usage guidance through 'Find knowledge by meaning, not just keywords,' suggesting when semantic search is appropriate. However, it lacks explicit when-to-use/when-not-to-use rules or named alternatives from the sibling list.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Submit' implies a write operation, but the description fails to disclose side effects (e.g., whether this triggers immediate verification, creates a queue entry, or notifies reviewers), idempotency, or success/failure semantics. No mention of permissions required for submission.

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 is grammatically efficient and front-loaded with the action. However, given the tool complexity (8 parameters, complex anyOf types), the extreme brevity constitutes under-specification rather than effective conciseness. Every word earns its place, but there are not enough of them.

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 8 parameters with 0% schema coverage, no annotations, and complex input types (arrays, objects, null unions), the description is insufficiently complete. It mentions domain-specific jargon ('empirical scroll') without definition and fails to explain the relationship between the artifact bundle components and the verification process. The existence of an output schema (not shown) reduces but does not eliminate the need for richer input description.

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

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

Schema description coverage is 0%, requiring the description to compensate for 8 undocumented parameters. While 'artifact bundle' provides minimal context for fields like 'code_hash' and 'data_hash', the description fails to explain required fields ('scroll_id', 'submitter_id') or optional complex parameters ('expected_metrics', 'run_commands'). No syntax, format, or relationship guidance is provided.

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 provides a clear verb ('Submit'), resource ('artifact bundle'), and purpose ('reproducibility verification'). It identifies the domain object ('empirical scroll') being acted upon. However, it lacks explicit differentiation from sibling submission tools like 'submit_scroll_tool' or 'submit_replication_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?

No explicit guidance on when to use this tool versus alternatives (e.g., submit_scroll_tool). No mention of prerequisites, preconditions, or workflow context. The phrase 'for reproducibility verification' hints at use case but does not specify trigger conditions or when submission is appropriate.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the submission action but reveals nothing about side effects (e.g., whether this creates a public record, triggers notifications, or updates scroll status) or idempotency 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?

Single sentence with no filler or redundancy. While efficient, it is arguably undersized for the tool's complexity, though this defect is captured in other dimensions.

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?

Grossly insufficient for a 7-parameter submission tool with complex domain logic. While an output schema exists (reducing the need for return value documentation), the complete absence of parameter documentation and behavioral context leaves critical gaps.

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

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

With 0% schema description coverage across 7 complex parameters (including `artifact_bundle_id`, `observed_metrics`, and `success`), the description provides zero semantic assistance for what these fields represent or valid input formats.

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?

States the basic action (submit) and domain object (reproducibility check results) but remains vague about what constitutes 'results' and fails to differentiate its role in the workflow from sibling tools like `submit_artifact_bundle_tool` or `get_replication_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?

Provides no guidance on when to invoke this tool versus alternatives, nor does it mention prerequisites (e.g., whether an artifact bundle must be submitted first) or the expected sequencing of replication workflows.

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

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

With no annotations provided, the description carries the full disclosure burden and successfully documents the post-submission workflow: automated screening with binary outcomes (pass enters review queue, fail triggers desk-rejection with reasons). It does not disclose auth requirements or rate limits.

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

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

The three-sentence structure is logical and efficient: purpose statement, workflow explanation, and enum documentation. Each sentence earns its place, though the scroll_type list is awkwardly appended rather than integrated into parameter guidance.

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 an 11-parameter submission tool with no annotations, the description covers the high-level workflow adequately but leaves significant gaps. The existence of an output schema excuses it from describing return values, yet the complete absence of parameter semantics for 10/11 fields makes this 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?

Given 0% schema description coverage across 11 parameters, the description inadequately compensates by documenting only the scroll_type enum values. Critical parameters like content, abstract, claims, and method_profile remain completely undefined, leaving the agent without guidance on expected formats or content requirements.

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 action (Submit) and resource (new manuscript to the Library of Alexandria), clearly distinguishing this from sibling tools like revise_scroll_tool and review_scroll_tool through the explicit 'new' qualifier.

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?

While the 'new manuscript' phrasing implicitly distinguishes this from revision tools, there is no explicit guidance on when to use this versus alternatives, prerequisites (e.g., author registration), or conditions for successful submission.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure but fails to explain the recursive traversal mechanism, what constitutes 'foundational sources', or that the operation is read-only. It states the goal but not the behavioral characteristics like output structure or stopping conditions.

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 single sentence is efficiently structured and front-loaded with the action verb. Every phrase serves a purpose, though the extreme brevity contributes to gaps in other dimensions. No filler or redundant text is present.

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

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

For a tool with only two simple parameters and an existing output schema, the description is minimally viable but incomplete. It adequately conveys the core lineage tracing concept but lacks necessary detail on the depth limiting behavior and traversal specifics.

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?

Given 0% schema description coverage, the description partially compensates by implying 'scroll_id' ('of a scroll') but completely omits explanation of 'max_depth', which controls the traversal limit. The critical behavioral parameter is undocumented beyond its presence 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 uses the specific verb 'Trace' and identifies the resource ('scroll') and scope ('full citation chain', 'foundational sources'), clearly indicating backward lineage traversal. It implicitly distinguishes from siblings like get_citations_tool through the 'full chain' language, though it does not explicitly name alternatives.

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 explicit guidance on when to use this tool versus alternatives like get_citations_tool or get_references_tool, nor does it mention prerequisites or exclusions. The phrase 'full citation chain' implies deep traversal but does not establish clear usage boundaries.

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?

Lacks annotations, so the description carries full burden of behavioral disclosure. While it mentions the ranking is based on 'recent publication and citation activity,' it fails to disclose caching behavior, rate limits, how 'trending' is calculated, or whether results are real-time.

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?

Single sentence is efficient with no redundancy, but severely under-delivers content given the complete absence of parameter documentation and behavioral context. Structure is adequate but insufficiently detailed.

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 (reducing descriptive burden), the tool fails to document its two optional parameters or clarify temporal scope. For a discovery tool with undocumented parameters, the description is inadequate.

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 0% for both 'days' and 'limit' parameters. The description completely fails to compensate by explaining the time window (days) or result count (limit), leaving critical parameters undocumented.

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?

States a clear resource (trending topics) and methodology (publication and citation activity), distinguishing it from general social media trending tools. However, uses weak verb 'See' rather than 'Retrieve' or 'Get', and could explicitly mention the scholarly/academic domain implied by the 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?

Contains no guidance on when to use this versus alternatives like search_scrolls_tool or browse_domain_tool, nor does it mention prerequisites or constraints. The agent must infer usage from the tool name alone.

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