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 only says 'Analyze', which implies a read-only investigation, but it does not state whether the tool modifies anything, what it returns, what permissions are needed, or how the optional connection string behaves. The gap between the vague description and the tool's actual behavior is significant.

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

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

The description is a single concise sentence with no filler, and it front-loads the verb and resource. It is efficient, though arguably too terse to be fully informative on its own.

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

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

With no output schema and no annotations, the description needs to explain what the analysis produces, whether it is read-only, and when to prefer it over sibling tools like mssql_monitor_database or mssql_debug_database. It does none of this, and it also omits the 'security' analysis option entirely, leaving the tool incomplete from an agent's perspective.

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 even though the description adds no parameter-level detail. The schema already documents schema, analysisType, and connectionString, including the enum values and the --allow-tool-connection-string requirement. The description's mention of 'configuration and performance' covers only two of the three enum values and adds little beyond the schema.

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

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

The description names a specific verb ('Analyze'), a resource ('SQL Server database'), and a scope ('configuration and performance'), so an agent can tell it is an analysis tool. However, it does not distinguish it from sibling tools like mssql_monitor_database or mssql_debug_database, and it omits the 'security' analysis type that appears in the analysisType enum.

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

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

The description gives no guidance on when to use this tool over alternatives such as mssql_monitor_database, mssql_debug_database, or mssql_execute_query. There is no when-to-use, when-not-to-use, or mention of prerequisites like the connection string flag. The available enum values hint at use cases, but the description itself does not provide selection guidance.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It only says 'Copy data,' which implies a write to the target, but it omits important traits such as transactionality, target table prerequisites, truncateTarget behavior, and the --allow-tool-connection-string requirement.

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

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

The description is a single, front-loaded sentence with no wasted words. It is concise, though it sacrifices useful operational context.

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

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

For a tool with 7 parameters, no output schema, and no annotations, the description is too minimal. It does not explain table existence requirements, transaction scope, batching, truncation behavior, or connection string permissions, leaving significant gaps for correct invocation.

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

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

Schema description coverage is 86%, so the schema already documents most parameters. The description adds no parameter-level detail, but the baseline of 3 applies because the schema carries the load; only batchSize lacks a schema description.

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

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

The description states a specific verb and resource: 'Copy data between two SQL Server databases.' This clearly conveys the core operation, though it does not explicitly differentiate itself from sibling tools like mssql_import_table_data or mssql_export_table_data.

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

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

No guidance is provided about when to use this tool versus alternatives, nor are any prerequisites or exclusions mentioned. An agent would have to infer usage context from the tool name and schema alone.

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

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

With no annotations, the description carries the full burden of disclosing behavior, but 'Debug common SQL Server issues' does not say whether the tool runs read-only diagnostics, changes server state, requires a connection string, or what output to expect. The only behavioral detail is hidden in the schema's logLevel note that it is ignored.

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 sentence is short and front-loaded, with no wasted words. However, its brevity is partly under-specification: it skips purpose details, usage context, and behavior while only broadly naming the tool's intent.

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 three parameters, no output schema, and no annotations, the description is incomplete. It does not explain what 'debug' produces, whether side effects are possible, how connection string handling works, or how this differs from the extensive set of sibling tools.

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

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

Schema description coverage is 100%, so the schema already explains 'issue', 'logLevel', and 'connectionString'. The main description adds no parameter semantics beyond the generic 'common SQL Server issues' phrase, yielding the baseline score.

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

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

The description states a verb and resource ('Debug... SQL Server') and the issue enum (connection, performance, locks, replication) suggests scope, but 'common SQL Server issues' is vague and does not distinguish 'debug' from sibling tools like mssql_analyze_database or mssql_monitor_database.

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

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

No guidance is given about when to choose this tool over the many sibling mssql_* tools. The enum values hint at problem categories, but the description never states conditions for use or 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure, and it falls short. It restates the operation enum but never warns that DELETE removes rows irreversibly or that UPDATE/DELETE without a WHERE clause could affect an entire table. The only behavioral detail (values bound as parameters, connection-string flag requirement) lives in the schema, not in the description.

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

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

The description is a single sentence plus one example, with the action verb front-loaded. It is compact and readable with no filler. The pseudo-code example is slightly informal (operation=... data={...} is not valid JSON), but it still earns its place as a quick orientation for the most common call.

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?

This is a high-complexity tool (9 parameters, 4 operation modes, upsert with conflictColumns, parameterized WHERE placeholders) with no output schema and no annotations, yet the description only illustrates the simplest insert path. It never explains default return behavior without the returning parameter, the where/whereParameters pairing at tool level, or destructive-operation safeguards. The detailed schema compensates partially, but the tool-level description leaves an agent under-informed.

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

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

Schema description coverage is 100% with detailed per-parameter text (e.g., where: 'Use @w1, @w2 (or $1, $2) with whereParameters'), so the baseline is 3. The description's example adds a concrete invocation shape for operation+table+data but only demonstrates 3 of 9 parameters, leaving where/returning/conflictColumns to the schema. Net added value over the schema is marginal.

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

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

The description opens with a specific verb and resource: 'Execute data modification operations (INSERT/UPDATE/DELETE/UPSERT)', reinforced by a concrete example (operation="insert", table="Users", data={...}). This clearly conveys scope and sets it apart from read-oriented siblings like mssql_execute_query. However, it never explicitly contrasts with mssql_execute_sql, which could also run DML, so sibling differentiation is implicit rather than explicit.

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 worked example implies the invocation pattern: pass operation, table, and data for an insert. But the description gives no explicit guidance on when to prefer this structured tool over the raw mssql_execute_sql sibling, and no exclusion conditions (e.g., use mssql_execute_query for SELECT-only needs). Usage context is inferred from the example, not stated.

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 burden of disclosing behavior. It communicates that this is a read/retrieval tool and shows parameter binding via @p1, which is useful. However, it does not mention default row limits, timeout behavior, or explicit read-only guarantees beyond the word 'SELECT'.

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

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

The description is a single focused sentence followed by a representative example. Every element earns its place, and the core purpose is front-loaded.

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

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

The description plus schema covers the required inputs, operation modes, and example syntax adequately for a query tool. It does not explicitly differentiate from the similar sibling mssql_execute_sql, and there is no output schema, but the missing output information is inherently query-dependent.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds meaningful value by showing a concrete example with @p1 and clarifying the relationship between operation, query, and parameters, which helps an agent assemble valid calls.

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

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

The description opens with a specific action and resource: 'Execute SELECT queries and data retrieval operations', and further defines the allowed operation set (select/count/exists). This clearly distinguishes it from the mutation-oriented sibling mssql_execute_mutation.

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 stated scope (SELECT queries and data retrieval) gives a clear context for when to use this tool, and the example reinforces the intended pattern. It does not explicitly name alternatives or exclusion conditions, but the boundary is evident from the operation enum.

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 behavioral disclosure burden and does reveal key behavior: arbitrary SQL execution, GO batch splitting, optional parameters, and transaction support. However, it does not mention potential destructive side effects, result/return behavior, or permission requirements, so transparency is partial.

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: one clear declarative sentence followed by two illustrative examples. There is no filler, and the core behavior is front-loaded.

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

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

The schema covers all parameters and the description covers invocation patterns and transaction behavior, which is adequate for basic use. However, there is no output schema, and the description does not state what the tool returns (rows, affected counts, etc.), leaving a notable gap for a generic SQL executor.

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 schema already documents all six parameters. The description adds only a high-level mention of optional parameters and a transactional example, providing no additional meaning beyond what the input schema already states.

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 executes arbitrary T-SQL, with examples spanning DDL (CREATE INDEX) and a CTE SELECT, so its generic scope is evident. However, it does not explicitly contrast itself with siblings like mssql_execute_query or mssql_execute_mutation, leaving some boundary inference to the agent.

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 phrase 'arbitrary T-SQL' and the examples imply this is the general-purpose runner, but the description never states when to prefer it over the specialized sibling tools or when not to use it. No exclusions or alternative routing guidance is provided.

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

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

No annotations are provided, so the description carries the full behavioral disclosure burden. It only says 'Export table data' and does not disclose that this creates a file on disk, respects overwrite=false by default, or that an optional connection string requires --allow-tool-connection-string. These are important side-effect and permission details that are left entirely to the schema.

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

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

The description is a single, front-loaded sentence with no filler. It is concise and immediately states the core operation. It loses a point because it is so terse that it omits the file-writing nature and any usage distinction, which may be more important than brevity for a tool with nine parameters.

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

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

Given no annotations, no output schema, nine parameters, and many sibling tools, this description is not complete enough for reliable invocation. It does not explain output file behavior, overwrite semantics, the optional connection string flag, or how this differs from query/import tools. The schema fills some gaps, but the description itself provides only a high-level label.

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 high at 89%, so the parameter definitions already carry most of the meaning. The description adds only the high-level format idea ('JSON or CSV'), which is already present in the format enum. With this coverage level, the baseline of 3 is appropriate; the description neither substantially helps nor hurts 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 states a specific verb ('Export'), a resource ('table data'), and the target formats ('JSON or CSV'). This clearly distinguishes it from read/query tools like mssql_execute_query and from the inverse mssql_import_table_data. However, it does not explicitly say 'to a file' or mention filtering, so it is clear but not maximally differentiating.

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

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

The description implies the tool is for exporting table data into JSON/CSV, which is a reasonable inference from both the name and the phrasing. But it provides no explicit guidance about when to choose this tool over mssql_execute_query or mssql_import_table_data, and no exclusions or prerequisites are mentioned.

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

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

With no annotations present, the description carries the full burden of behavioral disclosure. It only says 'Import data', which hints at a write operation, but it does't disclose that the table may be truncated first, that inserts are batched, that a connection string may be required, or that the operation is transactional. These meaningful behaviors are left to the schema or entirely undisclosed.

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?

A single, front-loaded, waste-free sentence conveys the essential operation. There is no repetition of schema details, no filler, and the key semantic elements (import, format, file, table) appear in the expected order.

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 8 parameters, no output schema, no annotations, and many sibling tools, the description is underspecified. It does not clarify whether this is a mutating operation beyond the word 'import', when truncateFirst would be relevant, how connection strings are resolved, or what failure modes exist (e.g., file not accessible, schema mismatch).

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 75%, so most parameters are already explained in the input schema. The description reinforces that the file is JSON/CSV and the target is a table, but it adds no new meaning for batching, delimiter, truncation, or connection string semantics. The two bare schema parameters (format and batchSize) receive no help from the description either.

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

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

The description names the action (Import), the source data type (JSON or CSV file), and the target (table), making the core purpose clear. It is semantically distinct from the obvious sibling mssql_export_table_data, but it doesn't explicitly call out the difference from generic mutation tools such as mssql_execute_mutation.

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

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

The description provides no guidance about when to choose this tool over alternatives like mssql_execute_mutation or mssql_execute_sql, nor does it mention prerequisites such as accessible file paths or connection string requirements. Usage is only vaguely implied by the word 'Import'.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not state that remove is destructive/deletes extended properties, whether set overwrites existing comments, what permissions are required, or what the tool returns. The description mostly restates the operation names rather than revealing side effects or runtime behavior.

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

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

The description is a single focused sentence followed by compact examples. It front-loads the core purpose and operation set, and the examples are informative rather than filler.

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

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

The description gives enough examples to make basic calls correctly, and the schema covers parameter details. However, with 10 parameters, no annotations, and no output schema, it omits return-value behavior, error cases, permission prerequisites, and the destructive impact of remove, leaving an agent under-informed for edge cases.

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

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

The schema already documents all parameters with 100% coverage, but the description adds useful examples that clarify parameter relationships, such as using operation='set' with comment text and operation='bulk_get' for discovery. It does not explain all conditional dependencies like tableName for index/constraint/trigger, but the schema already handles those.

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 manages SQL Server object descriptions via MS_Description extended properties, with explicit get, set, remove, and bulk_get operations. Examples with operation/objectType/objectName make the tool's scope concrete and help distinguish it from sibling tools that manage indexes, constraints, triggers, or functions.

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 operation examples that imply when the tool is useful, but it never explicitly says when to use this tool versus alternatives like mssql_execute_query, mssql_execute_mutation, or other mssql_manage_* tools. There is no exclusionary guidance or mention of 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.

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

No annotations are provided, so the description and schema carry the full behavioral burden. The description does disclose the operation set, and the schema documents several genuine behavioral traits: CASCADE is accepted but ignored, RESTRICT maps to NO ACTION, deferrable/initiallyDeferred are rejected with true, and clustered defaults differ per constraint type. However, tool-level effects such as the irreversibility of drop operations, transaction/commit behavior, and what the get operation returns are left undisclosed.

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

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

Two sentences with no filler; the operation enumeration is front-loaded and the example sentence carries dense invocation knowledge. The dash-heavy structure is slightly crammed and would scan better as a list, but every phrase earns its place.

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

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

Given the high complexity (19 parameters, 5 operations, destructive DDL, no annotations, no output schema), the definition is adequate but gapped. The schema descriptions cover per-parameter requirements for every operation, which compensates substantially. But the tool-level description omits return semantics for get, provides no warning about the referential-integrity impact of drops despite having no safety annotations, and only exemplifies two of five operations.

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%, establishing a baseline of 3. The description adds co-occurrence semantics above that baseline: the create_fk example binds constraintName, tableName, columnNames, referencedTable, and referencedColumns into a single valid parameter group, which is relational knowledge a flat schema does not directly convey. It loses a point because only two of the five operations get such grouping examples.

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

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

The description names a specific resource ('SQL Server constraints') and enumerates the five supported operations (get, create_fk, drop_fk, create, drop) followed by worked examples. This makes the tool clearly distinct from constraint-adjacent siblings like mssql_manage_indexes. It loses the top mark because the verb 'manage' is broad and the opening clause partially restates the tool's own name without naming what the tool is not.

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?

Usage context is implied rather than stated: the constraint-specific resource and the per-operation examples suggest when to invoke it, and the sibling set (mssql_manage_indexes, mssql_manage_triggers, mssql_manage_schema) makes the division of labor inferable. However, there is no explicit statement of when to use this tool versus alternatives, no exclusion criteria, and no guidance on how it composes with mssql_execute_query or mssql_analyze_database.

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 behavioral disclosure burden. It only restates the operation labels (get, create, drop) which are already documented in the schema, and offers no warning about destructive side effects, permissions, reversibility, or what the operation actually does to the database. The example illustrates inputs but not behavioral consequences.

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 on sentence with a front-loaded purpose and an illustrative example, with no filler or redundant content. It is appropriately sized for the tool's scope and 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.

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

The rich schema compensates for much of the missing detail, but the description alone leaves gaps for a 14-parameter, no-annotation tool. It shows only a CREATE FUNCTION example, mentions stored procedures without any example, and does not surface conditionally required fields like functionName for create/drop. Get and drop behavior would rely entirely on the schema. Overall it is adequate but not complete.

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

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

Schema coverage is 100%, so the structured fields already document all 14 parameters. The description adds value by showing a concrete composed CREATE FUNCTION example that demonstrates how functionName, parameters, returnType, and functionBody relate to each other. This is genuinely useful beyond the per-parameter schema 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 names a specific resource (SQL Server functions and stored procedures) and gives explicit verbs (get, create, drop), so an agent can clearly tell what this tool does. It also distinguishes itself from sibling tools like mssql_manage_triggers or mssql_execute_query by targeting function/procedure DDL management. The example reinforces the purpose with concrete operation usage.

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

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

The description clearly implies when to use this tool: when managing SQL Server functions or stored procedures via get/create/drop operations. It does not explicitly contrast against alternatives such as mssql_execute_query or mssql_manage_schema, but the resource scope is a sufficiently clear routing signal. It provides context without explicit exclusions.

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

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

With no annotations provided, the description carries the full burden of disclosing behavior. It only lists operation names and gives a few examples; it does not warn about destructive drop behavior, rebuild/reorganize locking or availability impact, permission requirements, or the connectionString restriction that requires --allow-tool-connection-string.

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: two sentences covering scope and representative examples. It front-loads the tool's purpose and avoids filler. A bulleted list or operation table might be more scannable, but the current structure wastes little space.

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

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

Despite rich schema coverage, this is a 21-parameter, five-operation tool with no annotations and no output schema. The description covers examples for only three operations and omits drop and reindex guidance, operation-specific parameter combinations, destructive-operation cautions, and any indication of what the tool returns. That is a significant gap for an agent selecting among many sibling tools.

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

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

Schema description coverage is 100%, so the baseline is 3. The description's examples add marginal clarity by pairing operation='create' with indexName, tableName, and columns, but this largely repeats what the schema already documents as required-for-create. It does not add meaningful new meaning for most of the 21 parameters.

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

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

The description clearly identifies the resource (SQL Server indexes) and enumerates the specific operations: get, create, drop, rebuild/reorganize, and analyze usage. It establishes an index-focused scope that distinguishes it from sibling tools like mssql_manage_schema or mssql_execute_query, though it leans on the broad verb 'manage' rather than a single precise action.

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 examples imply usage: operation='get' for listing indexes, operation='create' for creating, and operation='analyze_usage' for performance analysis. However, there is no explicit statement about when to prefer this tool over alternatives, no when-not guidance, and no mention of related tools such as mssql_execute_query or mssql_analyze_database.

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 behavioral disclosure burden. It does state what each operation does, including that reset_stats clears statistics, which hints at mutating behavior. But it does not warn that reset_stats is destructive, that explain with analyze=true executes the query, or that some operations may require elevated permissions.

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

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

The description is a single dense sentence that front-loads the tool's purpose and then lists all four operations with their purposes. It wastes no words, though the long dash-separated enumeration could benefit from a more structured format for readability.

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

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

The description gives a sufficient high-level operation map for a 15-parameter dispatcher tool, and the rich schema fills in most invocation details. It lacks guidance on output shape, side effects, connection requirements, and when to choose this tool over database-level analysis tools, so it is complete enough only in combination with the schema.

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

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

Schema description coverage is 100%, so the input schema already documents every parameter, including enums, defaults, and operation-specific applicability. The tool description adds no parameter-level detail, which is acceptable given the strong 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 maps the tool to SQL Server query analysis and performance and enumerates four concrete operations: explain, get_slow_queries, get_stats, and reset_stats. It is much more specific than a mere restatement of the tool name, though it does not explicitly differentiate it from overlapping siblings like mssql_analyze_database or mssql_monitor_database.

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?

Each operation has an implied use case ('operation="explain" for execution plans', 'operation="get_slow_queries" for slow query analysis'), which gives reasonable context. However, there is no explicit guidance about when to use this tool instead of related siblings, nor any when-not-to-use or exclusion notes.

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

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

With no annotations provided, the description must carry behavioral disclosure, but it only says 'Manage' and 'generated predicate functions'. It does not mention that create/edit/drop/replace operations are persistent DDL changes, that get_policies is a read operation, or that connectionString requires an explicit flag. Even the replace and ifExists behaviors are left entirely to the schema rather than the description.

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 brief and front-loaded: the purpose is stated first, followed by a single illustrative example. There is no filler, but the example's internal inconsistency slightly tarnishes its structural value.

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

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

The tool is complex (13 params, 6 operations, no output schema) and has no annotations, yet the description is quite sparse. It provides a high-level orientation and one create_policy example, while the rich schema descriptions cover the operational details; however, it omits any sense of what operations return and does not orient the agent to edit/drop/get flows, making it only minimally complete.

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

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

The schema covers all 13 parameters (100%), setting a baseline of 3, but the description's attempt to illustrate parameter use is flawed: it uses predicateColumns=['TenantId'] while the using expression references '@TenId', contradicting the schema rule that columns are referenced as @Column. This mismatch could lead an agent to generate an invalid predicate, so the example does more harm than good.

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

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

The description states a specific domain ('SQL Server Row-Level Security') and an actionable verb ('Manage'), and reinforces it with a concrete create_policy example that names the key parameters. Among eighteen sibling tools, only this one targets RLS policies, so it is clearly distinguishable.

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 example demonstrates a valid invocation (operation='create_policy', tableName, policyName, predicateColumns, using), which gives an agent a concrete usage pattern. However, it never explicitly says when to prefer this tool over the many other mssql_manage_* siblings, or when not to use it. The guidance is implied by the RLS scope rather than stated.

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 exist, so the description carries the full burden of behavioral disclosure, and it discloses essentially none. It never warns that create_table, alter_table (whose schema supports 'drop' operations), and create_enum are permanent DDL mutations, nor does it mention privilege requirements, transactional behavior, or failure modes. An agent gets no behavioral context beyond the operation names.

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?

A single front-loaded summary sentence followed by four thumbnall examples with zero filler. The content is scannable in one pass, and no sentence wastes the agent's attention.

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 10-parameter, 5-opration tool with nested objects, no output schema, and no annotations, the description covers 4 of 5 operations in examples - alter_table is only named, never exemplified. It also omits any behavioral or permission guidance and any sibling delegation advice. The extensive schema masks these gaps, but the description alone would give an agent an incomplete picture.

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

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

Schema coverage is 100% and the schema already documents per-operation requirements ('required for create_enum', 'required for alter_table'), so the baseline is 3. The description's examples restate those groupings ('operation="create_table" with tableName and columns'), which is helpful but largely redundant with the schema's own per-parameter notes. No parameter is left undocumented across both sources.

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

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

The description states a specific scope - 'get schema info, create/alter tables, manage enum-style CHECK constraints' - and backs it with four concrete examples ('operation="get_info" for table lists', 'operation="create_table" with tableName and columns'). This clearly separates it from raw-execution siblings like mssql_execute_query and mssql_execute_sql, which lack a DDL operation grammar of their own.

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 examples give explicit per-opration routing: 'operation="get_info" for table lists' and 'operation="create_enum" with enumName, tableName, columnName and values'. This is clear context for choosing among the five operations, though it never states when not to use the tool or names alternatives such as mssql_manage_constraints for non-enum CHECK constraints.

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 behavioral disclosure burden. It does disclose the major behaviors: list, create, drop, and enable/disable, and mentions that create can 'EXEC a procedure' as the trigger body. However, it does not describe side effects such as the permanence of drops, required permissions, whether changes persist immediately, or what the operation returns.

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, front-loads the core purpose, and packs the operation examples into a compact, scannable format. Every clause earns its place without unnecessary filler.

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

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

The description plus the detailed schema covers operation selection and parameter usage well, including SQL Server incompatibilities in the schema. However, there is no output schema, and the description does not explain return values, error behavior, or prerequisites/permissions, which leaves the agent with some uncertainty for a tool that can create and drop database objects.

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 value beyond the schema by specifying operation-specific parameter groupings, e.g. 'create' requires triggerName, tableName, and triggerBody (or functionName), and 'set_state' requires triggerName, tableName, and enable. This helps an agent assemble correct calls.

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

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

The description names a specific resource ('SQL Server DML triggers') and enumerates the exact operations: 'get, create, drop, and enable/disable triggers.' This clearly distinguishes it from sibling tools like mssql_manage_indexes or mssql_manage_functions.

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 patterns via examples: 'operation="get" to list triggers', 'operation="create" with triggerName, tableName and triggerBody', and 'operation="set_state" with triggerName, tableName, enable'. This gives clear context for when to use each operation, though it does not explicitly state exclusions or 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions potentially destructive operations like drop and revoke but does not disclose side effects, required privileges, Azure SQL differences, behavior of compatibility-only parameters, or consequences like cascading. The schema fields hint at these but the description itself is thin.

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

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

Two concise sentences with no filler. The first sentence defines the tool's purpose and scope; the second provides concrete example parameter groupings. The most important information is front-loaded.

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

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

This is a complex 21-parameter tool with no output schema and no annotations, yet the description only covers two operation examples. It does not explain operation-specific required parameters, return behavior, Azure SQL behavioral differences, or how unsupported compatibility parameters are handled. Given the tool's complexity, the description is under-specified.

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 value by showing realistic parameter combinations: operation='create' with username/password and operation='grant' with username, permissions, target, targetType. This helps the agent understand how parameters relate to operations beyond the individual schema 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 names a specific resource domain (SQL Server logins, database users, permissions) and enumerates exact operations (create, drop, alter, grant, revoke, get_permissions, list). This clearly differentiates it from sibling tools like mssql_manage_schema or mssql_execute_query by scope and action type.

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

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

The description implies use for user and permission administration through its operation list and examples, but it does not explicitly state when to choose this tool over alternatives like mssql_execute_query or mssql_execute_mutation. No exclusion conditions or alternative tool references are given, 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.

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

With no annotations, the description carries the full burden for behavioral disclosure. It does convey a read-only, current-state operation through 'Get' and 'real-time', but it omits specifics such as connection requirements, how the include flags alter behavior, what metrics are returned, or any side effects.

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

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

The description is a single, front-loaded sentence that is easy to scan and contains no filler. Brevity comes at the expense of substance, but that is a completeness problem rather than a conciseness problem.

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 seven parameters, a nested alertThresholds object, no output schema, and no annotations, yet the description only restates the basic monitoring purpose. It does not explain return data, parameter effects, or prerequisites, so an agent cannot confidently predict behavior from this definition alone.

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

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

The description adds no parameter-specific meaning and does not compensate for the low 43% schema description coverage. The seven parameters, including includeLocks, includeTables, includeQueries, includeReplication, and alertThresholds, receive no explanatory help from the description.

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

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

The description names a specific action ('Get') and a resource ('SQL Server database'), and the qualifier 'real-time monitoring information' gives a clear purpose. It does not explicitly contrast with mssql_analyze_database or mssql_debug_database, and 'monitoring information' remains somewhat generic.

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

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

No guidance is given on when to use this tool versus siblings like mssql_execute_query, mssql_analyze_database, or mssql_execute_sql. The phrase 'real-time' implies operational monitoring, but there is no explicit when-to-use or when-not-to-use direction.

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