Partuno

Server Quality Checklist

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Latest release: v4.0.1
Disambiguation3/5
Many tools target the same resource (e.g., product, quote, MyList) with different actions, but the descriptions clearly differentiate purposes such as pricing comparisons versus standard pricing, or full BOM analysis versus lifecycle-only audit. Some overlap exists between analyze_bom and audit_lifecycle, but the detailed descriptions help an agent choose correctly.
Naming Consistency5/5
All tool names follow a consistent snake_case verb_noun pattern (e.g., list_quotes, create_mylist, optimize_bom_pricing). Varied verbs are present but the structure is uniform, making the naming predictable and easy to navigate.
Tool Count2/5
With 50 tools, the server is heavily over-scoped even for a broad domain covering DigiKey and Mouser integrations, BOM management, and barcode processing. Many tools are granular (e.g., get_product_media, get_alternate_packaging) and could be consolidated into broader operations, making the count excessive.
Completeness4/5
The tool surface is quite comprehensive for component research, BOM analysis, and quote/MyList management, covering search, details, pricing, lifecycle, substitutions, and cross-supplier comparisons. Minor gaps exist, such as the absence of update/delete operations for quotes, but the overall domain coverage is strong.
Average 3.5/5 across 50 of 50 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 27 commits in the last 12 weeks
- Last stable release on August 12, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not contradict the annotations (readOnlyHint=false aligns with 'Add'), but it adds no behavioral context beyond the basic action. It does not mention the requirement for confirm=true, the mutating nature of the operation, or potential side effects, despite openWorldHint=true indicating possible undocumented behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, making it concise and front-loaded, but it is sparse and lacks structured detail. It is not verbose, but it provides minimal useful information beyond the basic purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a nested request object with many fields and no output schema, yet the description is only one sentence. It omits critical information such as the list_id parameter, the confirm boolean required to be true, insertion_index, and the 100-part limit, making the description insufficient for reliable tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, and the tool description only vaguely references 'products, packaging, and quantities'. It does not explain critical parameters like list_id and confirm, nor the nested request structure, leaving the agent without sufficient information to construct a valid request.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the verb 'Add' and the resource 'to a DigiKey MyList', along with the subject 'approved products, packaging, and quantities'. This distinguishes it from sibling tools like create_mylist and update_mylist_part, though it does not explicitly contrast them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, when to prefer alternatives, or any prerequisite conditions such as having a valid list_id or confirming the operation. It leaves the agent to infer usage entirely from the schema.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds no behavioral context beyond the annotations. The annotations already declare the tool as read-only, open-world, and idempotent, but the description does not mention return format, required identifiers, or how account_id influences behavior. It provides no additional transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, consisting of a single sentence with no filler. However, it is under-specified and sacrifices critical information for brevity, making it minimally adequate but not appropriately sized for the tool's needs.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and only two parameters, the description is too thin. It does not explain what a MyList is, what the response will contain, or the role of account_id, leaving the tool incomplete for confident invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description makes no mention of list_id or account_id. With 0% schema description coverage, the agent receives no guidance on parameter semantics. The description fails to compensate for the schema's lack of documentation, leaving parameter meaning entirely unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and the specific resource ('one DigiKey MyList'), indicating it retrieves a single list. However, it does not distinguish from sibling tools like list_mylists or get_mylist_parts, so it lacks sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 description does not mention when to use get_mylist instead of list_mylists (to list all lists) or get_mylist_parts (to fetch parts of a list), leaving usage context entirely absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, openWorld, and idempotent hints. The description adds a specific behavioral detail: retrying once without filters on 404/500 responses and marking the result. This is genuinely extra context, but it is ambiguous what 'marked' means and whether it affects the response. Overall, it contributes some transparency beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence and front-loaded with the main purpose, which is good. However, the semicolon-separated retry clause is dense and awkwardly phrased, mixing error-handling detail with the primary purpose. It is reasonably concise but not optimally structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 4 parameters, no output schema, and minimal parameter documentation, the description leaves significant gaps: no explanation of what the response contains, how parameters influence recommendations, or how this tool relates to similar ones. The retry behavior is niche but does not fill the emptiness. The description feels incomplete for a tool with this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 4 parameters (limit, product_number, search_options, exclude_marketplace) with 0% documentation coverage in the schema itself. The description does not explain any of these parameters, nor does it map 'explicit filters' to specific schema fields. There is no compensation for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a clear verb+resource ('Get DigiKey recommendations'), but the resource is vague: it does not specify what kind of recommendations or what input is used (e.g., product number). It also does not differentiate from sibling tools like 'recommend_components' or 'get_substitutions'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 retry-behavior clause implies a context where filters may be rejected, but it does not explain typical use cases, prerequisites, or when a different recommendation tool would be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds little beyond the tool name; it does not explain what constitutes 'alternate packaging' or what data is returned. The readOnlyHint, openWorldHint, and idempotentHint annotations cover the safety profile, but the description itself contributes no additional 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no unnecessary words. It is efficiently structured and easy to parse, though its extreme brevity leaves content gaps.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and overlapping siblings, the description is incomplete: it fails to explain what alternate packaging means, what the response contains, or how it differs from similar product lookup tools. The one-parameter schema and read-only annotations mitigate risk, but the description leaves too much to inference.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, and the description does not mention the product_number parameter at all. There is no information about acceptable formats, meaning, or required input semantics beyond the schema's bare property name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('alternate packaging for the same component'), clearly indicating that the tool returns packaging variants for a given component. It distinguishes from sibling tools like get_substitutions by emphasizing 'same component,' though it does not explicitly name those alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 get_substitutions, get_product_associations, or other product lookup tools. The description implies a simple lookup by product number but lacks any explicit context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, covering the safety profile. The description adds no extra behavioral context, such as what 'associated' means, whether results are flat or nested, or how missing products are handled. It essentially restates the tool name without enriching agent understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence with no wasted words. It is front-loaded and efficient, which is appropriate for a simple read-only tool with one parameter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the large number of sibling tools, the description is incomplete because it does not differentiate this tool from others that also deal with product relationships. It also lacks any explanation of what kind of associations are returned (e.g., direct vs. transitive, category-specific) or any usage guidance, leaving the agent without enough context to choose it confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for the single parameter product_number, and the description does not mention the parameter at all. It only implies that a product number is needed by the tool name and description, but provides no format, semantics, or examples. This is insufficient compensation for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (get) and resource (associated products and accessories), making the purpose understandable. However, it does not differentiate from similar sibling tools like get_substitutions or get_recommended_products, so it falls short of the top tier.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 description lacks any qualifying conditions, exclusions, or contextual hints to help an agent decide between this and related tools such as get_alternate_packaging or get_recommended_products.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, openWorldHint, and idempotentHint, so the description adds no further behavioral context beyond what annotations offer. It does not mention edge cases (e.g., invalid product numbers, quantity limits) or output behavior, so it fails to add value beyond the structured annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no superfluous words. It is as concise as possible while still conveying the core purpose, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simple nature (3 params, no output schema), the description is still underwhelming. It fails to clarify how this tool differs from get_pricing_by_quantity or get_product_pricing, and does not describe expected return values or any behavioral nuances. The lack of contextual guidance makes it incomplete for safe and correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not compensate. It mentions 'requested quantity' but does not clarify the role of product_number or account_id, nor does it explain any value constraints or formats. The description essentially restates the parameter name without adding semantic meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('Calculate') and resource ('DigiReel pricing'), plus the scope ('for a requested quantity'). It differentiates itself from sibling tools like get_product_pricing and get_pricing_by_quantity by specifying the DigiReel packaging type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to choose this tool over the many pricing-related siblings (e.g., get_product_pricing, get_pricing_by_quantity). There is no mention of alternatives, prerequisites, or exclusion criteria, leaving the agent to guess the intended usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, and idempotentHint=true, so the safety and non-mutating nature are clear. The description adds minimal behavioral context beyond 'current' pricing, but does not explain pagination behavior, authentication needs, or how filters like in_stock or exclude_tariff affect results. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that states the action and target without wasted words. It is appropriately concise for the information it conveys.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 8 parameters and no output schema, so the description should provide more context about return values, filtering options, and pagination. It only covers the core purpose, leaving significant gaps for a tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema description coverage at 0%, the description was expected to compensate by explaining key parameters. It only mentions 'one DigiKey product', which loosely implies product_number, but entirely ignores limit, offset, in_stock, includes, account_id, exclude_tariff, and exclude_marketplace. The description adds no value for parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' and clearly identifies the resource: 'current pricing and packaging variations for one DigiKey product.' This conveys the tool's core function. However, it does not explicitly differentiate from sibling tools like get_pricing_by_quantity, 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.
Usage Guidelines2/5
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 such as get_pricing_by_quantity or search_products. It simply states what the tool does without any contextual usage scenarios, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, covering the safety profile. The description adds a minimal behavioral note ('Shipping is unavailable') but does not disclose pagination behavior, return format, or other potential surprises. It provides slight value beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences and front-loaded with the core purpose. The second sentence about shipping is short and relevant but slightly disconnected. No wasted words overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a nested request object with multiple filtering options and records pagination, yet the description provides no details about these. It doesn't mention how to specify search mode, pagination, or filtering by manufacturer, in-stock, or RoHS. The output is not described, and the description is too sparse for a search tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 parameter meaning. It mentions availability, lifecycle, compliance, and price breaks, which loosely maps to schema fields like in_stock and rohs, but it does not explicitly explain the request object structure or how to use parameters like mode, manufacturer, or starting_record.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Mouser catalog data covering availability, lifecycle, compliance, and price breaks. It does not explicitly distinguish itself from sibling tools like search_products or get_product_details, but the focus on Mouser catalog data makes its purpose clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 such as search_products or get_product_details. The description merely states what it does, providing no context for tool selection or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, covering the safety profile. The description adds some context about the data (raw API dates, diagnostics) but is vague and does not mention limitations or response structure. It adds marginal value beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single 11-word sentence, extremely concise and front-loaded with 'Get PCNs.' However, the phrase 'additive description-date diagnostics' is jargon-heavy and may obscure meaning, making it slightly less effective than it could be.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and sparse parameter descriptions, the description should explain return content and parameter effects. It only hints at raw dates and diagnostics, and the 'includes' parameter is undefined, leaving the tool insufficiently specified for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has zero descriptions for parameters and the description mentions neither product_number nor includes. The optional 'includes' parameter is completely unexplained, leaving the agent without any clue about its purpose or valid values. With 0% schema coverage, the description fails to compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as retrieving Product Change Notifications (PCNs) and adds specifics about raw API dates and additive diagnostics. It is distinct from sibling tools which focus on pricing, products, orders, or other domains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no explicit guidance on when to use this tool versus alternatives. It does not mention that it is the only PCN-related tool or contrast it with other getters like get_product_details, leaving the usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already state the tool is read-only, open-world, and idempotent. The description adds context about the 'limit' parameter being enforced both upstream and locally, which is a useful behavioral trait beyond the annotations. However, it does not disclose other behavioral aspects such as response structure or filtering behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundant verbiage. Every word contributes to the meaning, making it efficiently sized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with four parameters and no output schema, this description is too sparse. It does not explain what constitutes a 'substitution', how the search options work, or what the return value contains. The good annotations help, but the description itself leaves significant gaps in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 by explaining parameter meanings. It only touches on the 'limit' parameter indirectly ('with the requested limit enforced upstream and locally') and says nothing about 'product_number', 'search_options', or 'exclude_marketplace'. This leaves most parameters semantically unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('Find replacement products') and resource, making it easy to understand the core purpose. However, it does not explicitly distinguish this tool from similar siblings like 'get_alternate_packaging' or 'get_recommended_products', 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.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. The phrase 'with the requested limit enforced upstream and locally' describes a technical detail rather than usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and openWorldHint=true, so the safety profile is clear. The description adds no extra behavioral detail (e.g., pagination, return format), but it is consistent with annotations, warranting a neutral score.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. However, given the tool has three parameters and a complex context, a slightly more detailed description would be more appropriate; still, it is not verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description should clarify what the list returns (e.g., full quotes or summaries) and how account_id affects results, but it does not. It also omits any pagination behavior, making it incomplete for a list operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not compensate. It mentions 'for an account' but does not explain the limit, offset, or account_id parameters, their optionality, or their formats.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List'), a clear resource ('DigiKey quotes'), and a scope ('for an account'), which clearly differentiates it from siblings like get_quote (singular) and get_quote_products (products within a quote).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 does not explicitly state that it returns multiple quotes or that get_quote should be used for a single quote, leaving the usage context entirely implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool as read-only, open world, and idempotent. The description adds no further behavioral details beyond the core action, such as return format, limitations, or dependencies on account permissions. It does not contradict annotations, but it also doesn't enrich them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence beginning with the verb 'compare'. It is concise and front-loaded, with no unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the nested schema, lack of output schema, and the presence of many sibling tools (e.g., diff_mylist, sync_mylist), this description is too minimal. It does not explain what the tool returns, how it differs from similar tools, or what the output looks like, making it incomplete for an agent to use effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description must compensate. It gives high-level meaning by relating 'scanned received quantities' to the barcodes array and 'required quantities' to the MyList, but it does not explain the account_id parameter or the barcode_type enum values. This leaves significant gaps for an agent trying to construct valid inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: comparing scanned received quantities against required quantities in a DigiKey MyList. The verb 'compare' is specific, and the resources (scanned barcodes and MyList) are named, distinguishing it from siblings like get_mylist or diff_mylist.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It does not mention exclusions or recommend another tool for different scenarios. The context is only implied by the action, not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only and idempotent behavior. The description adds the qualifier 'metadata' and singleton scope, but doesn't disclose what fields are returned or how missing quotes are handled. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One short, front-loaded sentence; every word carries meaning and there is no waste or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Description is too terse: no output schema exists and the description does not indicate what metadata is included or how account_id affects the request. This leaves significant operational gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description provides no explanation of quote_id or account_id beyond their names in the schema. It does not compensate for the missing parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly specifies verb 'Get', resource 'one DigiKey quote's metadata', which distinguishes it from list_quotes (all quotes) and get_quote_products (quote line items).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives; it does not mention list_quotes or get_quote_products, nor any context in which one should be preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint, openWorldHint, and idempotentHint, establishing the safety profile. The description adds behavioral context by contrasting 'compact' (bounded, default) with 'full' (raw DigiKey shape), but 'bounded' remains vague and does not explain pagination, auth needs, or response structure beyond this hint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the core purpose. It is appropriately brief, though the term 'bounded' is imprecise and could be clearer. Overall, it is compact without unnecessary verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 10 parameters and no output schema, the description is incomplete. It does not explain what 'bounded' means, what the compact vs. full responses contain, or how parameters like include_images and substitution_limit affect results. The description leaves too much to be inferred.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description must compensate, but it only clarifies the response_detail parameter via the compact/full distinction. Nine other parameters (e.g., include_substitutions, substitution_limit, account_id) receive no explanatory context. This is insufficient given the parameter count and lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get every MyList part,' using a specific verb and resource. It distinguishes from sibling tools like get_mylist by focusing on the parts within a list. The compact/full detail adds further specificity about the response format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is given about when to use this tool versus alternatives. The description does not mention alternatives or exclusions, leaving the usage context entirely implied by the name. This is a clear gap for a tool with many sibling list/part tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds valuable behavioral context by noting that partial failures are returned under errors without discarding successful results, which is not covered by annotations. This is a meaningful addition to the tool's operating characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that states the main purpose and then adds the key behavioral caveat. It contains no filler, repetition, or unnecessary detail, 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (nested request object, nine sub-parameters, many enrichment options) and lack of an output schema, the description is too sparse. It does not specify how returned data is structured, what the enrichments actually return, or how this tool relates to sibling getter functions, leaving significant gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, and the description only vaguely refers to 'optional enrichments' without explaining the specific include_* flags, the request object structure, or the account_id parameter. It groups the enrichment flags into one term, providing minimal semantic help beyond the parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets product details with optional enrichments, using a specific verb and resource. However, it does not distinguish itself from the sibling tool 'get_product_details', leaving some ambiguity about when the two differ.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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_product_details or the various get_* enrichment tools. It does not mention any specific use case, prerequisites, or exclusions, leaving the agent without a clear decision framework.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, and open-world behavior. The description adds useful input-domain context (product-bag vs. packing-list, 1D vs. 2D) but does not disclose return format, error behavior, or how the 'includes' option affects output. It provides some value beyond annotations but not a rich 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. Every word contributes to understanding the tool's purpose and scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description does not explain what the decoded result contains or looks like. It also omits guidance on when to use this tool versus batch_decode_barcodes. Despite helpful annotations, the description is too terse to be considered complete for an agent that must invoke it confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only partially compensates. It clarifies the meaning of barcode_type values ('product-bag or packing-list 1D or 2D'), but it does not explain the 'request' wrapper structure or the optional 'includes' parameter. The barcode parameter is self-evident, but the overall parameter semantics remain under-specified.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Decode') and names the exact resource ('DigiKey product-bag or packing-list 1D or 2D barcode'). The singular 'a barcode' distinguishes this from sibling batch_decode_barcodes, 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.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance about when to use this tool versus alternatives like batch_decode_barcodes. The description does not state that this is for single barcodes only or mention any exclusions, leaving selection to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool read-only, idempotent, and open-world. The description adds one behavioral nuance—that parent availability is distinct from package stock—but does not explain the meaning of the pricing options or any output format, so it adds limited value 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that front-loads the core action and adds a relevant edge case. No redundant filler; every word contributes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With four parameters and no output schema, the description is too sparse. It fails to clarify the semantics of the optional parameters (includes, account_id), the meaning of the pricing options, or the return structure, leaving the agent to infer too much.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has four parameters with zero description coverage. The description does not explain what product_number, requested_quantity, includes, or account_id represent; it only implies quantity relevance through the tool name. There is no compensation for the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Compare' and identifies concrete pricing option types (exact, effective-MOQ, BetterValue, maximum-order), clearly distinguishing it from sibling tools like get_product_pricing and get_digireel_pricing. The added nuance about parent availability vs package stock further clarifies scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
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 like get_product_pricing or get_alternate_packaging. The description implies it is for comparing multiple pricing tiers for a requested quantity, but lacks 'use this when' or 'instead of' directives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, and idempotentHint=true, so the safety profile is clear. The description adds minimal behavioral context beyond the annotations; it mentions 'locked pricing' indicating the quote pricing is fixed, but does not disclose pagination behavior, sorting, or other operational details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The entire description is a single sentence with no redundant words. It is front-loaded with the action and resource, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 4 parameters and no output schema, the description is too sparse. It doesn't explain pagination semantics, the meaning of account_id, or what a response would look like. While annotations cover safety, the description fails to provide sufficient operational context for an agent to correctly invoke the tool and handle results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no information about the parameters (quote_id, limit, offset, account_id). It only partially references quote_id through the phrase 'in a DigiKey quote'. This does not compensate for the lack of schema descriptions, so parameter semantics are poorly documented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies the action 'Get' and the resource 'products and locked pricing in a DigiKey quote', clearly distinguishing from sibling tools like get_quote which likely returns quote header info. The verb+resource construction is concise and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
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 such as get_quote or list_quotes. The description only states the function, leaving the agent to infer its usage from the name. No exclusions or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, covering safety and idempotency. The description adds the scope ('authenticated user's') and date-filtering behavior, which provides some value beyond annotations. However, it does not disclose pagination behavior or that multiple accounts might be involved (openWorld), so it stops short of being rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with no redundant information. It conveys the core purpose efficiently, earning high marks for conciseness and structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With six optional parameters, no output schema, and no parameter descriptions, the description is too sparse. It does not explain what the response looks like, how pagination works, or the role of 'shared' and 'account_id', leaving significant gaps for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only clarifies the date-related parameters (start_date, end_date). It does not explain the meaning or usage of 'shared', 'account_id', 'page_size', or 'page_number', leaving most parameters ambiguous and under-documented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Search'), identifies the resource ('DigiKey orders'), and scopes it to the 'authenticated user' with a filtering criterion ('by date'). This clearly distinguishes it from siblings like get_sales_order, which likely fetches a single order.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for date-based order searches but provides no explicit guidance on when to choose this over alternatives (e.g., get_sales_order for a specific order) or any exclusions. No mention of using account_id for multiple accounts or pagination, leaving usage context vague.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already mark this as a read-only, idempotent operation. The description adds the 'authenticated user's' scope, which clarifies that results are limited to the current user's MyLists. However, it does not elaborate on pagination behavior, response contents, or any other 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence consisting of seven words. It is front-loaded with the action and resource, and every word contributes meaning without unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, but the description leaves some gaps. It does not mention that pagination is controlled by limit and start_index, nor does it clarify whether the response includes list metadata only or also parts. Given no output schema, the description could be more complete by hinting at what the return value contains, though the annotations help fill the safety profile.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has three parameters (limit, account_id, start_index) with no descriptions, and the schema description coverage is 0%. The description does not explain any of these parameters, leaving the agent to infer their meaning from names only. It provides minimal additional semantic value beyond the schema fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action ('List') and a specific resource ('the authenticated user's DigiKey MyLists'). It distinguishes itself from sibling tools like get_mylist (which likely fetches a single list) and create_mylist by focusing on listing all of the user's lists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It does not mention any exclusions or reference sibling tools, such as using get_mylist for a single list or search_products for product searches. The usage context is only implied by the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly=false, so the mutation is known. The description adds the nuance 'explicitly approved,' hinting at a confirmation requirement, but it does not disclose potential side effects, reversibility, or error behavior. It provides minimal added behavioral 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is clear and free of fluff. It quickly conveys the core purpose without unnecessary words or details, fitting the criteria for concise, front-loaded communication.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has nested objects, a required confirm flag, and no output schema, the description is too sparse. It omits context such as the need to provide account_id, the existence of a confirmation step, or what happens after successful addition. An agent lacks enough information to invoke the tool correctly in varied situations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only mentions 'product quantities' without explaining the request structure, quote_id, account_id, or the confirm flag. Since the description does not compensate for the schema's lack of descriptions, it adds little value in explaining parameter meaning beyond what the schema already shows.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Add') and a clear resource ('product quantities to a DigiKey quote'), making it easy to distinguish from siblings like create_quote or list_quotes. The phrase 'explicitly approved' adds a relevant qualifier that signals the operation is intended for pre-approved items.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used for adding products to an existing quote, but it does not explicitly state when to use it versus alternatives (e.g., create_quote_from_source) or mention any prerequisites. The intended context is inferable but not directly communicated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds the aggregation behavior of totaling quantities by product number, which is useful beyond the readOnly/idempotent annotations. However, it does not disclose return format, error handling, or behavior with invalid/mixed barcode types. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that conveys the primary purpose and aggregation behavior without excess words or redundancy. It is well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core behavior and aggregation, and annotations provide safety profile. However, with no output schema and a nested request object, additional context about return values or barcode type semantics would improve completeness. Generally adequate for a read-only batch tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no parameter details. The nested 'request' object, 'barcodes' array, and 'barcode_type' enum are left entirely to the schema. Given the low coverage, the description fails to compensate by explaining how to specify barcodes or the meaning of barcode types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('Decode a batch'), resource ('DigiKey barcodes'), and outcome ('total received quantities by product number'). It distinguishes itself from the sibling 'decode_barcode' by emphasizing batch processing and aggregation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies using this tool for batch decoding and totaling, but it does not explicitly explain when to choose it over 'decode_barcode' or other barcode-related tools. No exclusions, conditions, or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and openWorldHint=true, which covers the safety profile of the operation. The description adds value by enumerating the categories of rows the diff will show (additions, updates, removals, duplicates, unchanged), providing more behavioral detail than the annotations alone. It does not mention auth or rate limits, but the annotation coverage lowers the burden.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the key verb and resource. It is concise with no redundant words or filler, and every word contributes to the understanding of the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a nested request object with many fields, and the description gives no details on how to construct the request or what the actual return structure looks like. It mentions high-level diff categories, but with no output schema and no parameter explanation, the description is insufficient for an agent to invoke the tool correctly without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides almost no parameter guidance. It mentions 'proposed BOM' but doesn't explain list_id, request, or the nested proposed_items structure. The schema itself documents defaults and constraints, but the description should compensate for the lack of coverage and fails to do so.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Dry-run' and clearly states the resource (a proposed BOM against a MyList) and the output (additions, updates, removals, duplicates, unchanged rows). It distinguishes this from sibling tools like sync_mylist or get_mylist, which either apply changes or retrieve list contents without diffing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for previewing changes ('Dry-run'), which suggests it should be used when you don't want to mutate the MyList. However, it does not explicitly state when to use this vs. alternatives like sync_mylist or add_parts_to_mylist, nor does it mention exclusions like 'do not use if you want to apply changes'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the operation as read-only, idempotent, and open-world. The description adds context about the type of content returned (datasheets, images, documents, video links), but does not disclose potential limitations or behaviors beyond that. This is useful but not rich, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the purpose with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with one input and annotations confirming safety and open-world behavior, the description adequately conveys the scope of return values. However, it does not specify whether all listed media types are always included or if some may be null/empty, which could be relevant for an agent. Being a simple tool, it is mostly complete but could be clearer.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description should compensate for the single product_number parameter. It implies context by saying 'a product's' but does not explain what product_number is, its format, or how to obtain it. This adds minimal value over the schema's parameter name and type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a product's datasheets, images, documents, and video links, using a specific verb and resource. It distinguishes from sibling tools like get_product_details by scoping to media types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like get_product_details or research_product. The description only states what it does, leaving the agent to infer the appropriate context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, and idempotentHint=true, covering the safety profile. The description adds no additional behavioral context (e.g., auth requirements, rate limits, or side effects). It does not contradict the annotations, so a mid-range score 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, 14-word sentence that front-loads the core action and lists the analysis categories without any fluff. Every word earns its place, 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is complex with a nested request object and many boolean options, but the schema provides detailed parameter information. The description clearly states the tool's purpose and the analysis dimensions, offering a sense of expected output. However, since there is no output schema, the description does not explain return values or error conditions, and it lacks guidance on optional filters. This is adequate but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 but does not. While the schema property names (e.g., exclude_tariff, maximum_lead_weeks) are somewhat self-descriptive, the description adds little meaning to the nested request structure or specific parameters. It only lists analysis dimensions, which loosely map to some parameters but without explicit clarification.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Analyze' and resource 'BOM', and clearly lists the analysis dimensions (cost, stock, lifecycle, lead time, compliance, PCNs, alternate packaging, substitutes). This distinguishes it from siblings that focus on individual products or specific aspects, making it clear that this is a comprehensive BOM analysis tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for BOM-level multi-faceted analysis, but it does not explicitly state when to use this tool versus siblings like get_product_details, audit_lifecycle, or get_substitutions. There is no mention of exclusions or alternatives, leaving the agent to infer the usage context from the name and the listed dimensions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=false, idempotentHint=false, and destructiveHint=false. The description adds 'after explicit approval' and 'empty', which provide some behavioral context but largely reinforce schema constraints (confirm const true). No additional side effects, authentication needs, or return behavior are disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the tool's purpose ('Create an empty DigiKey quote') and includes a necessary precondition. Every word adds value, with no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple and annotations cover the safety profile, but the description omits any mention of return values or what happens after creation. Since there is no output schema, a brief note on the returned quote or confirmation would improve completeness. The nested parameter structure is also not addressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, and the description provides no parameter explanations. It does not clarify the semantics of account_id, quote_name, or the confirm flag beyond what is inferred from names. The description fails to compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action (create), a resource (DigiKey quote), and a distinguishing characteristic ('empty') plus a precondition ('after explicit approval'). This differentiates it from sibling tools like create_quote_from_source, which creates from a source, and add_products_to_quote, which adds products to an existing quote.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The context is clear: this tool is for creating a new empty quote, implying it should be used before adding products. However, it does not explicitly mention when not to use it or name alternatives. There are no exclusions, but the guidance is implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, openWorldHint, and idempotentHint. The description adds a concrete behavioral detail: the marked fallback that removes non-matching tariff or Marketplace variations when DigiKey returns them. This goes beyond the annotations and gives the agent insight into result filtering behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence. It starts with the main verb and resource, then appends the fallback behavior in a semicolon clause. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description conveys the primary purpose and one behavioral quirk, but for a complex tool with a nested schema, many filters, and pagination support, it lacks context on how to compose a request or what the response entails. The readOnlyHint and openWorldHint annotations help, but the description leaves gaps about usage patterns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not compensate. The phrase 'native filters' is vague and does not explain the many parameters within the nested request object (e.g., limit, offset, parametric_filters, tariff_filter). The schema itself has some nested descriptions, but the tool description adds no parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Search DigiKey with native filters.' The verb 'Search' and resource 'DigiKey' are specific, and it distinguishes itself from sibling search tools like search_orders (orders) and search_mouser_products (Mouser). The 'native filters' scope further clarifies this is DigiKey's product search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no explicit guidance on when to use this tool versus alternatives. It mentions 'native filters' and a fallback but does not say 'use this when searching DigiKey products' or 'for Mouser products, use search_mouser_products.' Usage context is only implied by the resource name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate this is a non-read operation (readOnlyHint=false) and non-idempotent, so the description does not need to restate those. It adds valuable context by specifying the requirement for user approval and the exact name. It also implies that the tool will create a list with the exact name provided, which is a behavioral trait not captured in annotations. While it doesn't discuss error conditions or side effects, the added confirmation context is useful and goes beyond metadata, justifying 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the main action ('Create a DigiKey MyList') and then adds the essential condition. It contains no unnecessary words and is easy to parse. Perfectly sized for the information it conveys.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having a nested request object and no output schema, the description does not explain the request structure, return values, or potential failure modes. It only provides the user-approval condition. For a mutation tool with 0% schema description coverage and no output schema, the description leaves too much for the agent to infer. The tool is relatively simple, but the missing parameter semantics and lack of return-value information make it incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, and the description does not compensate. It only mentions 'exact name' and 'user approves', which hints at list_name and confirm, but gives no explanation of tags, account_id, created_by, or the nested request structure. Since there is no parameter documentation in the schema and the description adds almost no parameter meaning, this is a major gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Create a DigiKey MyList'. The verb 'Create' and resource 'MyList' are specific. It also adds a key condition ('after the user approves the exact name') that distinguishes this from other mylist operations like rename or delete. Since sibling tools include rename_mylist, delete_mylist, and add_parts_to_mylist, the purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear usage prerequisite: 'after the user approves the exact name'. This tells the agent when it is appropriate to call the tool (only after user confirmation). However, it does not explicitly mention alternatives or situations where this tool should not be used. Given the self-explanatory name and the sibling context, the lack of explicit 'use X instead' is a minor gap. The condition itself is a strong guideline, so it earns a 4.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, openWorld, and idempotent behavior, so the description only needs to add context beyond that. It states that lookup is by either sales-order or web-order number, but does not describe validation behavior when both/neither are supplied or what 'one order' means in the response.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One short, front-loaded sentence with no filler. It immediately states the action, resource, and lookup key, making it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a simple read with good annotations, and the description is enough to select it, but with no output schema and no mention of the required request wrapper or one-of constraint, the agent has incomplete information for fully correct invocation and expected return.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema parameters have no descriptions, so the prose carries the burden. The description names both identifiers and indicates they are alternatives, which adds meaning, but it stops short of stating that exactly one is expected, leaving a critical ambiguity given both fields default to null.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Read' and identifies the resource as a single Mouser order, keyed by sales-order or web-order number. It clearly distinguishes this from sibling search/list tools and from get_sales_order by naming the Mouser context and the one-record semantics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'Read one ... by ... number' implies use when a specific Mouser order identifier is already known, but the description does not explicitly mention when to prefer this over search_orders, search_mouser_order_history, or get_sales_order. No exclusions or fallback guidance are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so the safety profile is covered. The description's 'Get current' is consistent and hints at real-time data, but otherwise adds no behavioral traits beyond annotations (e.g., missing product behavior, auth needs).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence with no filler. The verb 'Get' starts immediately, and the list of data categories is compact and purposeful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 4 parameters (one required) and no output schema, the description doesn't explain parameter usage or the return structure beyond a high-level list. An agent would not know valid `includes` values, how `account_id` affects pricing, or how to disambiguate with `manufacturer_id`, making it insufficient for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 parameter meaning. It implicitly links 'account pricing' to account_id and 'one product' to product_number, but provides no explanation for `includes` choices or `manufacturer_id`, leaving the agent guessing on how to invoke these optional parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Get current specifications, inventory, lifecycle, classifications, variations, and account pricing for one product' – a specific verb and resource with a clear single-product scope. It distinguishes from siblings like search_products (multi-product) and get_product_pricing (pricing-only) by enumerating multiple data categories.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context: use for a single product's comprehensive details, with the listed data categories implying a full snapshot. However, it doesn't explicitly name alternatives or state when not to use it, leaving some ambiguity against similar tools like research_product or get_product_pricing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already flag this as destructive, non-readonly, non-idempotent, and open-world. The description adds the confirm=true approval gate, which is a valuable behavioral control beyond the annotations. However, it does not elaborate on side effects, reversibility, or the extent of modifications, so it only partially augments the annotation-provided safety profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary action, and contains no filler. Every word contributes to understanding the tool's purpose and a key prerequisite.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of the nested request schema and the lack of an output schema, the description is too terse. It does not mention potential failure modes, return behavior, or the practical effects of applying a diff (e.g., whether items not listed are removed). The workflow with diff_mylist is implied but not explicitly linked, leaving gaps for a mutation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only mentions the confirm parameter. The request object includes many fields (proposed_items, remove_unlisted, consolidate_duplicates, etc.) with no explanation of their meaning or relationship to the diff application. This is insufficient compensation for the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Apply') and resource ('MyList diff') that clearly identifies the tool's primary action. It also distinguishes itself from sibling tools like diff_mylist and other mylist functions by focusing on the application step rather than retrieval or creation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states the precondition that the request must contain confirm=true, which indicates that this tool is for executing an approved diff and not for initial diff generation. This gives clear contextual guidance, though it does not explicitly name alternative tools or state when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds the key behavioral nuance of preserving omitted fields, which is not captured by the annotations. Yet it leaves ambiguity about whether explicitly setting a field to null clears it versus omitting it, and it does not address authorization or state requirements beyond 'approved.' With annotations already indicating idempotent and non-destructive behavior, the added value is moderate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that immediately states the action and the key preservation behavior. No filler, redundancy, or unnecessary detail—ideal conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite a complex nested request object and no output schema, the description is minimal. It fails to explain the 'approved' concept, how to obtain list_id/unique_id, the response structure, or the null-vs-omitted distinction. Significant context is missing for an agent to invoke the tool confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has zero description coverage for its 14 request fields, and the description does not enumerate or explain any of them. It only refers generically to 'every field omitted,' forcing the agent to rely on schema types and defaults without guidance on relationships or conditional logic.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (update) and the specific resource (an approved MyList part), and the phrase 'while preserving every field omitted from the request' distinguishes it from a full replacement update. This sets it apart from sibling tools like remove_mylist_part or add_parts_to_mylist.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context about a partial-update scenario by emphasizing preservation of omitted fields, which tells the agent when this tool is appropriate. However, it does not explicitly name alternatives or state when not to use it, and the 'approved' requirement is mentioned but not elaborated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false and destructiveHint=false, so this is a write operation. The description adds the 'explicitly approved' requirement and the confirm=true condition, providing useful context. It does not disclose what happens on failure or whether the quote is immediately persisted, but the annotations cover the safety profile partially.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with the action and resource. Every word adds value, with the second sentence highlighting the critical confirmation requirement. No redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a nested object and no output schema, so the description should clarify key behaviors. It states the source and confirmation requirement but does not mention what happens if both items and list_id are provided, how approval is verified, or what the response contains. This leaves gaps for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only vaguely mentions 'BOM or MyList' which maps to list_id and/or items. It does not explain the nested request object, the relationship between items and list_id, or the confirm field's role beyond 'must contain confirm=true' (already in schema). The description fails to compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Create and populate') with a clear resource ('a quote from an explicitly approved BOM or MyList'). It distinguishes itself from sibling tools like create_quote and add_products_to_quote by specifying the source and approval condition.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool: when you have an approved BOM or MyList and need a quote populated. It also includes the mandatory confirm=true condition. However, it does not explicitly mention alternatives or when not to use it, like using create_quote for empty quotes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations (readOnlyHint, idempotentHint, openWorldHint) already indicate a safe read operation. The description adds useful context by mentioning 'parametric-search context' as part of the response, which goes beyond just 'get category'. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that immediately states the tool's purpose. There is no fluff or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description provides minimal detail about the return value. Mentioning 'parametric-search context' is helpful but vague—it doesn't clarify what that context includes or any error behavior. Acceptable for a simple one-parameter read, but with gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the meaning of category_id, how to find it, or any constraints. The parameter name is self-explanatory, but the description fails to compensate for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and the resource ('one DigiKey category'), and adds specificity with 'parametric-search context'. It distinguishes from sibling list_categories by explicitly saying 'one' category, making the singular scope obvious.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the phrase 'one category' and the required category_id parameter, but there is no explicit guidance on when to use this tool versus alternatives like list_categories. 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and openWorldHint=true, so the safety profile is known. The description adds 'does not modify the cart,' which is redundant with readOnlyHint but reinforces the behavior. No additional behavioral traits (e.g., errors, rate limits) are disclosed, so the score stays at the baseline.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences, immediately front-loaded with the core purpose ('Read one Mouser cart') and a clear safety note. Every word earns its place, with zero redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with one parameter and no output schema, the description covers the basic purpose and safety. However, it does not describe what the returned cart data contains or how to obtain a cart_key. Given the absence of an output schema, more detail on the return value would make it more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one required parameter, cart_key, but the description does not mention it at all. Schema description coverage is 0%, so the description should compensate by explaining the parameter's purpose or format. The parameter name is somewhat self-explanatory, but the description offers no guidance beyond that, so compensation is minimal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Read') and the resource ('one Mouser cart'), and explicitly notes it does not modify the cart. This distinguishes it from sibling tools like preview_mouser_cart_change and execute_mouser_cart_change, which involve modifications.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: use this tool when you need to read a Mouser cart without modifying it. This is clear given the 'does not modify' statement, but it does not explicitly name alternatives or exclusions, so it falls just short of a top score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations (readOnlyHint, openWorldHint, idempotentHint) already establish the safety and idempotency profile, so the description carries a lower burden. It adds that the tool returns a category tree and IDs, which is useful context, but does not disclose additional behavioral traits like pagination 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no redundant words. It is front-loaded with the action and resource, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with no parameters and no output schema, but the description sufficiently conveys the purpose and expected output (category tree and IDs). The annotations provide additional context about the nature of the data. While not exhaustive, it is adequate for a straightforward listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameters, which per the baseline rules yields a score of 4. The description naturally has no parameter details to add, and the schema coverage is 100%, so there are no undocumented parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool's function: retrieving the DigiKey product category tree and category IDs. The verb 'Get' is specific, and the resource is well-defined, distinguishing it from sibling tools like get_category which targets a single category.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 such as get_category or search_products. There is no mention of use cases, prerequisites, or exclusions, leaving the agent to infer based on 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, covering the safety profile. The description adds value by specifying the returned data categories (shipment, tracking, backorder, line-item status), which provides context about output scope beyond what annotations convey.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 14 words, front-loaded with the verb 'Get', and contains no superfluous content. Every word contributes to specifying the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple get-by-ID tool with strong annotations, the description adequately covers the main output dimensions. However, with no output schema, it does not describe response structure or error behavior, and the account_id parameter is undocumented. This is a minor gap given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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. However, it provides no information about sales_order_id or account_id. While sales_order_id is implied by 'one... sales order', account_id is entirely unexplained, and the description adds no meaning beyond the schema's field names and types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Get' and clearly identifies the resource as 'one DigiKey sales order', listing the exact aspects returned (shipment, tracking, backorder, line-item status). This distinguishes it from siblings like search_orders and aligns with the read-only, single-order nature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for a single sales order by saying 'for one... sales order', but does not explicitly state when to use this tool versus alternatives like search_orders. There is no mention of exclusions or alternative tools, so guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds the 'bounded page' behavior, indicating pagination, which is not in the annotations. This adds useful context beyond the structured data, though it could be more specific about pagination mechanics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that is front-loaded with the action and resource. Every word adds value; there is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (list with pagination) and the presence of annotations, the description covers the essential purpose and return content. It does not describe return format or pagination details, but no output schema exists and the parameters are simple. A minor gap is the lack of explicit parameter mapping, but overall it is reasonably complete for the tool's scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explicitly mention limit or offset. The phrase 'bounded page' hints at pagination but does not explain how parameters control it. The parameter names are standard, but the description fails to compensate for the lack of schema descriptions, leaving parameter semantics largely implicit.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists a bounded page of DigiKey manufacturers and their manufacturer IDs. The verb 'List' is specific, and the resource is clearly identified, distinguishing it from sibling tools like search_products or list_categories.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides the core functionality but no explicit guidance on when to use this tool vs alternatives. There are no sibling comparisons or contextual cues. Usage is implied by the tool's name and description, but no when/when-not guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already communicate readOnly, idempotent, and openWorld behavior. The description adds the scope of lookup keys but does not disclose behavior around include_pdf (e.g., whether it returns a PDF or alters data), response format, or edge cases. It provides some value beyond annotations but not rich context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence that states the action, target, and acceptable inputs. No filler or redundant content, making it highly scannable for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and a nested request object, the description is minimally adequate: it states what the tool returns conceptually ('packing-list information') and the input types. But it fails to mention the include_pdf flag or describe what 'information' entails, so an agent lacks full context for more complex invocations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries some burden. It names all three lookup_type enum values in prose, which helps map free text to the enum. However, it omits the behavior and purpose of include_pdf and does not clarify the 'value' parameter beyond 'number', leaving room for ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Retrieve') with a clear resource ('packing-list information') and explicitly enumerates the lookup keys (invoice, sales order, purchase order). This differentiates it from sibling lookup tools, none of which target packing lists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use the tool: when a packing list needs to be found by one of the three document numbers. It does not provide explicit exclusion guidance or alternative tool names, but the context is unambiguous enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds 'authenticated deployment's' context and the filter/date-range modes, which are useful beyond the readOnlyHint/idempotentHint annotations. However, it does not disclose potential behaviors like result limits, pagination, or error conditions. With annotations covering safety, the added context is minimal but non-zero.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the verb and resource. It contains no filler and every word adds meaning. This is an example of excellent conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a nested request object, multiple date fields, and no output schema. The description provides the essential purpose but does not mention return format, pagination, or the relationship between mode and date fields. Given the moderate schema complexity, the description is barely adequate for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description says 'by filter or date range', which maps to the 'mode' property in the schema, but it does not explain the individual parameters like start_date, end_date, or the meaning of date_filter values. Since schema_description_coverage is 0%, the description bears more responsibility, yet it only offers a high-level hint, not enough to fully understand all parameter interactions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: reading Mouser order history. It specifies the resource (Mouser order history), the verb (Read), and the scope (by filter or date range). This distinguishes it from sibling tools like get_mouser_order (single order) and search_orders (general order search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (when you need Mouser order history) and mentions the two modes (filter/date range), but it does not explicitly exclude alternatives or state when *not* to use it. Since sibling tools like search_orders exist, a more explicit comparison could be helpful, but the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnly, openWorld, and idempotent traits. The description adds contextual behavior by enumerating what the audit covers, which is useful beyond the annotations. It does not contradict annotations, but it does not describe return format or limitations, which is a minor gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that lists the key audit dimensions without unnecessary words. It is front-loaded and efficient, earning a 5 for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a complex tool with a nested request object, no output schema, and no parameter descriptions. The description provides only a high-level summary. It does not explain how to specify the BOM vs MyList, what the response looks like, or any thresholds. For a tool of this complexity, the description is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It hints that 'BOM' correlates with the 'items' parameter and 'MyList' with 'list_id', adding some meaning. However, it does not explain other parameters like maximum_lead_weeks or include_substitutions, nor how to construct the request.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Audit' and clearly identifies the resource (BOM or MyList) and the specific lifecycle risk factors covered (end-of-life, last-buy, shortages, lead times, PCNs, substitutes). It distinguishes itself from sibling tools by focusing on comprehensive lifecycle auditing rather than just substitutions or PCN lookups.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use this tool: when you need a lifecycle risk audit of a BOM or MyList. It names the exact risk categories, providing a strong contextual cue. However, it does not explicitly mention alternatives or exclusions, such as 'for detailed substitution lists use get_substitutions'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint, openWorldHint, and idempotentHint. The description adds a meaningful behavioral detail: unpriceable alternate packages are isolated in candidate diagnostics rather than causing errors. This goes beyond the annotations 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One efficient sentence that front-loads the purpose and immediately adds a valuable behavioral note about diagnostics. Every word earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description conveys the core function and a unique behavior, and annotations cover safety and idempotency. However, it omits information about output structure or prerequisites, and given the nested parameter schema and lack of output schema, the description is somewhat under-specified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description gives no explanation of the 'request' parameter or its nested items structure, and schema coverage is 0%. With a single but complex object parameter, the description should compensate by outlining key fields, but it does not, leaving the agent to rely entirely on the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool optimizes BOM pricing with a specific focus on package choices. Distinguishes from sibling tools like get_alternate_packaging and analyze_bom by targeting pricing optimization rather than alternative listing or general analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context: use this tool when you need to optimize BOM pricing by choosing among package options. Does not explicitly mention when not to use or name alternatives, but the context is specific enough to infer appropriate use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description is consistent. It adds that the tool reads current cart state and computes an exact diff for various operations, reinforcing its non-mutating nature. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise sentence, front-loaded with the tool's primary function, and lists operations efficiently without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 operation types, nested request object, no output schema), a one-sentence description is insufficient. It lacks parameter guidance and details about the diff output format, though the annotations and operation list provide some context. Overall, it's a functional but not comprehensive description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single 'request' parameter is a complex nested object with multiple sub-fields, and the schema has zero descriptions. The description provides no guidance on how to structure the request, what each operation requires, or the relationship between fields. This is a significant gap; the description must compensate but does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs 'read' and 'preview' and enumerates the operation types (add, update, remove, replacement, order-copy, schedule). This clearly distinguishes it from 'execute_mouser_cart_change' which performs changes, and 'get_mouser_cart' which only reads state.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage scenarios through the list of operations, but does not explicitly state when to use it versus alternatives like execute_mouser_cart_change. The context is clear enough: to preview a change before applying it. No explicit exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly, openWorld, and idempotent hints. The description adds value by elaborating on the return format (pass/fail/unknown evidence and Pareto shortlist), which aligns with the openWorldHint. It does not contradict annotations and provides extra behavioral detail 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, two sentences long, and front-loaded with the core action. Every word contributes to explaining the tool's purpose and output. No unnecessary detail or repetition exists.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a complex nested request schema and no output schema, but the description does not explain how to structure the request or interpret results beyond mentioning evidence and Pareto shortlist. While the annotations help clarify safety and open-world behavior, the description alone is insufficient for an agent to fully understand the tool's usage in context, especially given the complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero description coverage and the sole 'request' parameter is a complex nested object with many required subfields. The description only hints at 'critical requirements' without naming or explaining any parameters such as project_summary, search_terms, quantity, or hard_requirements. This fails to compensate for the schema's lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Find' and resource 'project candidates', clearly indicating what the tool does. It also specifies the output ('pass/fail/unknown evidence and a Pareto shortlist'), distinguishing it from sibling tools like get_recommended_products which likely focus on product recommendations rather than project-level candidate evaluation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context by stating 'after critical requirements are known', implying this tool should be used once requirements are finalized. However, it does not explicitly name alternatives or explain when not to use this tool, so it falls short of the most explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds 'permanently' (irreversibility) and 'explicit approval' (confirmation requirement), which go beyond the destructiveHint annotation. It also specifies the operation affects a single part, providing useful behavioral context not fully captured by 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, information-dense sentence with no wasted words. It is front-loaded and every element carries meaning relevant to invoking the tool correctly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the destructive nature, the schema without parameter descriptions, and no output schema, the description is too brief. It doesn't explain how to obtain list_id, what the unique_id format is, or the exact role of confirm beyond 'explicit approval'. The description is minimally viable but leaves notable gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero description coverage, and the description only hints at unique_id as the identified part and confirm as the approval. It does not explain list_id, account_id, created_by, or the required confirm constant, leaving most parameters semantically undefined.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the action ('permanently remove'), the target ('one identified part' from a 'DigiKey MyList'), and the condition ('after explicit approval'). This distinguishes it from sibling tools like delete_mylist (whole list) and add_parts_to_mylist (adding parts).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a single part needs to be removed from a MyList, and the phrase 'one identified part' sets clear context for a focused removal operation. However, it does not explicitly mention alternatives or exclusion criteria, such as using delete_mylist for an entire list or add_parts_to_mylist for additions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description adds that user approval is required, which is a key behavioral constraint, and that the change must be exactly as approved. This complements the schema's confirm field and 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the action 'Rename a DigiKey MyList' and includes the critical approval condition. Every word adds value, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple rename operation, the description plus annotations provide sufficient context: purpose, approval requirement, non-destructive, idempotent, and mutation. No output schema exists, so return values are not expected. It could mention prerequisites like list existence or failure modes, but these are not essential for basic use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% for the two parameters. The description does not explicitly detail parameters, but the phrase 'the exact change' implies new_name must match user approval, and 'after the user approves' maps to the confirm boolean. However, account_id and other nested properties remain unexplained, so the description only partially compensates for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Rename' with the resource 'DigiKey MyList', clearly indicating the operation. It is distinct from sibling tools like create_mylist or delete_mylist, though it does not explicitly name alternatives. The approval qualifier adds precision and helps differentiate it from a simple rename without confirmation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states the intended use case: renaming a list after the user approves the exact change. This implies that user confirmation is a prerequisite and that this tool should be invoked only after approval. It does not mention exclusions or alternatives, but the context is clear enough for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool read-only, open-world, and idempotent. The description adds contextual behavior beyond these: it emphasizes 'strict' matching, indicating only exact manufacturer-plus-MPN matches are considered, and that quantities affect the comparison. This gives insight into the matching logic and scope, which is valuable 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the action and resource, with no filler or redundant wording. Every word contributes meaning: 'strict', 'manufacturer-plus-MPN', 'requested quantities', and 'across DigiKey and Mouser' all add essential clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has one nested parameter and no output schema, the description conveys the core purpose and scope sufficiently. It states the matching criteria and the vendors involved. It could mention the response format or what happens with missing matches, but the annotations cover safety and idempotency, and the purpose is clear enough for an agent to select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description indirectly references the key required fields: 'manufacturer-plus-MPN' corresponds to manufacturer and manufacturer_part_number, and 'requested quantities' maps to quantity. This adds meaning to the schema. However, it does not explain the nested structure of the 'request' object (e.g., that items is an array), so compensation is partial.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: comparing strict manufacturer-plus-MPN matches at requested quantities across DigiKey and Mouser. It uses a specific verb ('Compare') and identifies the exact resource (manufacturer-plus-MPN matches) and scope (DigiKey and Mouser), effectively distinguishing it from siblings like search_products or get_product_pricing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: when you need to compare exact manufacturer and part number matches across two specific distributors at given quantities. However, it does not explicitly state when not to use it or mention alternative tools for similar tasks, so it stops short of full guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, and the description adds the authentication context ('authenticated login'), providing useful additional framing. It does not detail return formatting or multiple-account behavior, but with strong annotations no contradiction or major gap exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence that contains all necessary information with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless, annotated read-only lookup, the description is sufficiently complete: it names the resource and the auth context. An output schema is absent, but the description inherently communicates the return value (Account IDs).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema imposes no burden. The description's mention of 'associated with the authenticated login' adequately conveys the implicit scope without needing parameter-level detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and names a concrete resource ('DigiKey Account IDs associated with the authenticated login'), clearly distinguishing it from the product, order, and list-management sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes clear this is for retrieving account IDs for the currently authenticated login, establishing a clear use context. Since no sibling tool serves the same purpose, explicit alternatives are unnecessary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already indicate destructive behavior (destructiveHint=true), and the description adds useful constraints about the token's one-time nature and expiration, informing the agent of potential failure conditions. No contradiction with annotations exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence (14 words) that front-loads the verb 'Execute' and includes no redundant information. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the essential execution constraints and is well-supported by annotations (destructiveHint, openWorldHint). Without an output schema, the result of execution is not described, but given the simple parameter structure, this is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, but the description adds meaning to the single parameter (confirmation_token) by calling it a 'one-time token' and linking it to a specific preview. This compensates for the lack of schema-level explanation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Execute') and the specific resource ('Mouser cart preview') with constraints ('exact, unexpired', 'bound to the supplied one-time token'). This distinguishes it from sibling tools like preview_mouser_cart_change, which only previews the change.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool (executing a specific preview using a valid one-time token) but does not explicitly name alternatives or say when not to use it. The distinction from preview_mouser_cart_change is implied by the word 'Execute'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (destructiveHint=true), the description explicitly says 'Permanently delete' and 'obtaining explicit approval', which discloses irreversibility and a required confirmation step. This adds meaningful behavioral context not present in 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that conveys the action, permanence, and prerequisite. Every word contributes meaning, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a delete operation with a small parameter set and clear annotations, the description covers the essential behavior. It lacks detail about output/return values, but the absence of an output schema lowers the bar. The mention of approval is crucial given the destructive nature, making the description adequately complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates by implying the need for a list identifier ('identifying it') and a confirmation ('obtaining explicit approval'), directly mapping to list_id and confirm. However, it does not mention the optional account_id parameter, leaving a gap in full parameter coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'delete' with a clear resource 'DigiKey MyList', and the qualifier 'Permanently' clarifies scope. It is distinct from sibling tools like remove_mylist_part, which removes a part rather than the whole list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is for deleting an entire MyList, setting it apart from part-level operations. It also adds a prerequisite ('after identifying it and obtaining explicit approval'), providing clear context on when to use it. However, it does not explicitly name alternatives or state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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