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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It states that the tool returns all fields, relationships, and field properties, which clarifies the scope of information. It does not mention side effects, authentication, or output structure, but for a read-only describe operation this is minimal yet acceptable.

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

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

The description is two sentences, with the primary action and resource in the first sentence and concrete examples in the second. It is front-loaded and contains no filler, making it highly scannable.

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

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

Given a single parameter and no output schema, the description provides a sufficient overview of both input and output: it explains what the agent must provide (objectName) and what will be returned (all fields, relationships, field properties). It could detail the response format further, but for a simple describe endpoint this is adequate.

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

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

The single parameter objectName is fully described in the schema with examples, yielding 100% schema coverage. The tool description adds its own examples ('Account', 'Case') that are redundant with the schema but do not introduce additional semantics. Thus the description contributes little beyond the structured field definition.

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

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

The description uses the specific verb 'Get' and identifies the resource as 'detailed schema metadata' for a Salesforce object. It clearly distinguishes from sibling tools like query_records or search_objects by focusing on object structure rather than data or search results. Examples with 'Account' and 'Case' reinforce the purpose.

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

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

The description conveys its use case: retrieving schema metadata for any Salesforce object. It does not explicitly reference alternative tools or when to avoid using it, but the context is clear enough for an agent to select it when needing object structure. The examples provide practical guidance but no exclusion statements.

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

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

With no annotations provided, the description carries the full behavioral burden. It adds useful context like 'requires Id' for update/delete and 'external ID field' for upsert, but doesn't disclose potential side effects (e.g., permanent deletion), permission requirements, or error handling behavior. This is a meaningful but incomplete disclosure for a mutation tool.

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

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

The description is well-structured with a clear introductory line, a concise bulleted list of operations, and practical examples. Every sentence contributes meaning, and the format is scannable without excessive length.

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

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

Given the tool's complexity (4 parameters, no output schema, no annotations), the description covers the core operations, prerequisites, and use cases effectively. It lacks details about return values or failure modes, but for a DML tool with clear operation semantics, it provides sufficient context for an agent to select and invoke it correctly.

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

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

Schema description coverage is 100%, so all parameters are documented. The description adds extra semantic value by explaining operation-specific requirements (e.g., update and delete require Id, upsert uses externalIdField), which enhances the schema's basic field descriptions.

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

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

The description clearly identifies the tool as performing DML operations (insert, update, delete, upsert) on Salesforce records, with a specific verb+resource structure. It distinguishes itself from sibling tools like salesforce_query_records and salesforce_search_objects by focusing on data manipulation rather than reading or describing.

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

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

The description provides concrete usage context with examples for each operation (Insert new Accounts, Update Case status, Delete old records, Upsert based on custom external ID). It implicitly contrasts with read-only tools, though it doesn't explicitly state when not to use this tool or name alternatives.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively communicates that this is a metadata mutation tool ('create new custom fields or modify existing fields'), specifies that 'changes affect metadata,' and notes permission requirements. It doesn't mention rate limits, side effects on existing data, or whether operations are reversible, but covers the essential safety and scope aspects for a metadata tool.

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

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

The description is efficiently structured with a clear opening statement followed by bullet-point categorization and specific examples. Every sentence earns its place by providing distinct value: the first sentence states the core purpose, the bullets organize parameter concepts, the examples illustrate use cases, and the note adds critical behavioral context. No wasted words.

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

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

For a complex metadata mutation tool with 17 parameters and no annotations or output schema, the description does well by covering purpose, scope, permission requirements, and parameter categories. It could be more complete by explicitly mentioning that this tool doesn't handle data values (unlike salesforce_dml_records) or describing typical response formats, but it provides sufficient context for an agent to understand the tool's role and basic usage.

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

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

The schema description coverage is 100%, so the schema already documents all 17 parameters thoroughly. The description adds some value by categorizing parameters into 'Field Types,' 'Properties,' and 'Relationships,' which helps conceptual organization, but doesn't provide additional syntax, format, or constraint details beyond what's in the schema. This meets the baseline for high schema coverage.

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

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

The description clearly states the tool's purpose with specific verbs ('create new custom fields or modify existing fields') and identifies the resource ('any Salesforce object'). It distinguishes this tool from siblings like salesforce_dml_records (data manipulation) and salesforce_describe_object (metadata inspection) by focusing on field-level metadata management.

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

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

The description provides clear context for when to use this tool through examples ('Add Rating__c picklist to Account, Create Account lookup on Custom Object') and notes about prerequisites ('require proper permissions'). However, it doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools, though the context implies it's for field metadata rather than data operations.

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

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

The note 'Changes affect metadata and require proper permissions' discloses the mutation nature and permission requirement. However, the claim 'with fields, relationships, and settings' is not supported by the input schema (no fields or relationships parameters), which could mislead an agent about capabilities. This prevents a higher score.

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

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

The description is compact and well-structured: a clear verb phrase, bulleted operations, illustrative examples, and a critical permission note. Every sentence contributes meaning without redundancy.

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

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

The tool has 9 parameters, no annotations, and no output schema, so the description must carry more weight. It gives high-level operations but fails to explain return behavior, error conditions, or the full scope of parameter usage. The unsupported 'relationships' claim further reduces completeness and trustworthiness.

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

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

Schema description coverage is 100%, so baseline would be 3. However, the description mentions creating objects 'with fields, relationships, and settings' but the schema offers no such parameters, adding misleading information. This overstates the tool's functionality and could lead to incorrect invocation, warranting a score below baseline.

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

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

The description uses a specific verb ('Create', 'modify') and resource ('custom objects in Salesforce'), clearly distinguishing this from sibling tools like search/query/describe. It states the two primary operations (create/update) with concrete examples, making the tool's purpose unmistakable.

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

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

Provides clear context for when to use the tool (creating or updating objects) with examples and a permission note. However, it does not explicitly exclude alternatives or mention when to choose sibling tools like salesforce_manage_field or salesforce_describe_object, so it falls short of full 5.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does well by specifying the query language (SOQL), relationship query capabilities, and syntax rules for custom relationships. However, it doesn't mention important behavioral aspects like pagination, rate limits, authentication requirements, error handling, or what happens when queries return large result sets. The examples are helpful but don't cover all behavioral traits.

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

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

The description is appropriately sized and front-loaded with the core purpose statement. The examples are well-organized and directly relevant to understanding the tool's capabilities. While comprehensive, some information could be more concise - the relationship syntax rules might be condensed. Every sentence earns its place by clarifying SOQL query patterns.

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

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

Given the tool's complexity (SOQL queries with relationships, 5 parameters) and the absence of both annotations and output schema, the description does a decent job but has gaps. It covers the core functionality and parameter usage well through examples, but doesn't address return format, error conditions, performance considerations, or how results are structured (especially for nested relationship queries). For a query tool with no output schema, more information about response structure would be helpful.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds significant value through the four detailed examples that show how parameters work together in practice, especially for relationship queries. It clarifies dot notation for parent relationships, subqueries for child relationships, and the '__r' suffix for custom relationships - all semantic details beyond what the schema provides. However, it doesn't cover all parameters equally (orderBy and limit get less attention).

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

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

The description explicitly states 'Query records from any Salesforce object using SOQL, including relationship queries' - this is a specific verb ('Query') with clear resource ('records from any Salesforce object') and distinguishes from siblings like salesforce_dml_records (for data manipulation) and salesforce_search_all/search_objects (for search operations). The mention of SOQL and relationship queries further clarifies the technical approach.

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

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

The description provides clear context about when to use this tool (for SOQL queries with relationship support) and the examples demonstrate various query patterns. However, it doesn't explicitly state when NOT to use this tool or name specific alternatives among the sibling tools (like when to use salesforce_search_all instead). The guidance is strong but lacks explicit exclusion criteria.

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

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

With no annotations, the description carries the transparency burden. It discloses important behavioral details: SOSL syntax, wildcard support, per-object WHERE/ORDER BY/LIMIT, WITH clause types, and access filtering via updateable/viewable. It stops short of stating read-only nature explicitly, but 'search' strongly implies it. Overall, it provides above-average transparency.

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

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

The description is longer than a minimal one, but the length is justified by the tool's complexity. It is front-loaded with a clear purpose, followed by structured examples and a concise bullet list of notes. Every section adds value, though some redundancy exists (e.g., wildcards are mentioned twice).

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

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

The tool is complex with nested object parameters and optional WITH clauses. The description covers the multidimensional usage thoroughly with examples, notes, and feature lists, providing enough context for an agent to construct valid invocations. Given no output schema, the description is sufficiently complete for this search tool.

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

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

Schema coverage is 100%, providing a solid baseline. The description goes beyond the schema by including two detailed examples that show how objects, withClauses, and wildcards are used together, and it clarifies the meaning of updateable/viewable. This significantly enriches parameter understanding.

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

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

The description opens with a precise statement: 'Search across multiple Salesforce objects using SOSL (Salesforce Object Search Language).' This clearly identifies the tool's action, resource, and scope, and distinguishes it from sibling tools like salesforce_search_objects and salesforce_query_records by emphasizing multi-object SOSL search.

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

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

The description gives clear context that this tool is for searching across multiple objects, with examples showing the expected structure. However, it does not explicitly reference alternatives or state when not to use it, so it stops short of a 5.

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

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

No annotations are provided, so the description carries the full burden of disclosing behavior. It explains the search action and gives examples of matches, but doesn't state whether the operation is read-only, its return format, or any limitations (e.g., case sensitivity, wildcard support). For a simple search tool, the core behavior is disclosed, but additional transparency is lacking.

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

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

The description is extremely concise: one sentence stating the purpose and one sentence with examples. It is front-loaded with the verb and resource, and every word earns its place. No fluff or repetition.

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

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

For a tool with one parameter and no output schema, the description covers the main purpose and gives examples. However, it omits specifics about how the pattern matching works (e.g., substring vs. whole word, case sensitivity) and what the output shape is (e.g., just names or full metadata). These gaps prevent it from being fully complete.

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

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

The only parameter `searchPattern` has a 100% schema description coverage, including an example. The tool description reiterates and supplements with examples ('Account' will find Account, AccountHistory), but doesn't add significant new meaning beyond what the schema already provides. Baseline 3 is appropriate.

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

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

The description clearly states the tool's function: 'Search for Salesforce standard and custom objects by name pattern.' It provides concrete examples ('Account' will find Account, AccountHistory), which further clarifies the scope and distinguishes it from sibling tools like describe or query.

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

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

The description gives a clear context of when to use this tool (searching objects by name pattern) and provides examples of the expected input/output. It doesn't explicitly mention alternative tools or exclusions, but the use case is unambiguous enough for an agent to decide when to call it.

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