mcp-oracle-db

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose: schema/table metadata (list_schemas, list_tables, describe_table), SQL operations (query, execute, ddl), query planning (explain_plan), and session/admin monitoring (session_info, active_sessions, locks). No overlaps exist.
Naming Consistency4/5
Most names are clear and follow a verb_noun pattern (list_schemas, describe_table, explain_plan), but a few are single verbs (query, execute) or bare nouns (ddl, locks), creating minor inconsistency. Still readable and predictable overall.
Tool Count5/5
10 tools is well-scoped for a database server, covering metadata exploration, SQL DML/DDL, query analysis, and session/lock monitoring without excess. Each tool earns its place.
Completeness4/5
The set covers the core database lifecycle: schema discovery, querying, data modification, DDL, and monitoring. Minor gaps like a dedicated index-listing tool or multi-statement runner exist, but agents can work around them via DDL and query.
Average 3.7/5 across 10 of 10 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on March 20, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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?
With no annotations, the description carries the full burden of behavioral disclosure. It states that an execution plan is generated but does not mention whether the operation is read-only, requires permissions, has side effects, or what the output format is.
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 wording. It efficiently conveys the basic purpose without unnecessary detail.
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 the tool's simplicity, the lack of annotations and output schema means the description should provide more context about expected behavior and returns. It only covers purpose, leaving usage, safety, and result format unaddressed.
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 already describes the single parameter 'sql' as 'SQL query to analyze', and the tool description essentially repeats this. With 100% schema description coverage, the description adds no extra meaning, so the baseline score of 3 is appropriate.
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 ('Generate') and resource ('execution plan') for a SQL query. It distinguishes from siblings like 'query' and 'execute' by focusing on plan generation rather than execution.
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 such as 'query' or 'execute'. The description does not specify contexts, exclusions, or mention sibling tools.
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?
Without annotations, the description carries the full burden of behavioral disclosure. It does add context by specifying that the query is a SELECT (implying read-only) and that output is JSON, but it does not explain details like result size limits, error handling, or potential performance impacts. This is partial transparency but leaves significant gaps.
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 extremely concise and well-structured. Two short sentences clearly state the purpose ('Execute a SELECT query') and the output format ('Returns results as JSON'), with no filler or repetition. Every word contributes meaning, making it an exemplary model of 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?
While the tool is relatively simple, the description lacks important context such as the structure of the JSON return value, any default query limits, or how it relates to sibling tools like execute. Given the absence of an output schema and annotations, a bit more detail would improve completeness, though the current description covers the core function adequately.
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 provides 100% coverage of all three parameters (sql, binds, max_rows) with descriptive text. The tool description adds no parameter-specific information beyond what the schema already states, so with this high schema coverage, a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool executes SELECT queries against an Oracle database and returns results as JSON. This provides a specific verb (Execute), a resource (SELECT query, Oracle database), and output format, making the purpose clear and distinct from siblings like ddl or explain_plan, though it does not explicitly compare itself to the similarly named 'execute' tool.
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 execute or list_tables. It does not mention any restrictions, prerequisites, or scenarios, leaving the agent to infer usage solely from the tool's name and basic purpose.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It merely restates the tool's function without detailing required privileges, output format, or whether it filters by session state. It adds little beyond the tool's name and title.
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 conveys the tool's purpose. It is concise, front-loaded, and contains no unnecessary wording.
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 simplicity of the tool (no parameters, no output schema, no annotations), the description provides a basic understanding of what the tool does. However, it omits details like which session fields are returned or any system privileges required to access V$SESSION, which could be relevant for an agent. It is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, making schema coverage trivially 100%. According to the rubric, a tool with 0 parameters receives a baseline score of 4, as there is no parameter semantics to document.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' and clearly identifies the resource as 'active sessions' in the Oracle database, referencing the V$SESSION view. This makes the tool's purpose unambiguous and distinct from sibling tools like list_schemas or list_tables.
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 only states what the tool does and provides no guidance on when to use it versus alternatives such as session_info or locks. There is no mention of exclusions, prerequisites, or the appropriate context for selecting this tool.
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 are absent, so the description must disclose behavioral traits. It states it lists 'all tables and views,' which conveys the scope, but it does not mention whether the operation is read-only, how results are formatted, whether system tables are included, or any error behavior. Only minimal behavioral context is provided.
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 and object, containing no filler or redundant phrasing. 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter and no output schema or annotations, so the description is largely sufficient. However, it does not explain the return format (e.g., just names vs. metadata) or edge cases like missing schemas. Given the lack of annotations and output documentation, the description is adequate but not fully complete.
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 covers 100% of the parameter detail, describing 'schema' as 'Schema/owner name'. The tool description adds no additional meaning beyond the schema, so the baseline of 3 applies.
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 states a specific verb ('List') and resource ('all tables and views in a schema'), clearly distinguishing it from sibling tools like list_schemas (which lists schemas) and describe_table (which examines a single table). It precisely conveys the function and 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?
The description implies usage by stating it lists tables and views in a schema, which signals when to use it. However, it does not explicitly mention alternatives or exclusions, such as 'use list_schemas to see available schemas' or 'use describe_table for details on a single table.' Thus, usage is implied but not clearly contrasted with other tools.
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?
With no annotations provided, the description carries the full burden of disclosing behavioral traits. It indicates a read-only operation ('Get'), but does not describe what information is returned, whether authentication is required, or any potential side effects. This lack of detail limits the agent's ability to predict tool 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?
A single sentence, directly front-loaded with the verb and resource. Every word carries meaning, with no redundant detail or filler. This is appropriately concise for a simple informational tool.
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 simplicity (no parameters, no output schema), the description is minimally adequate for basic understanding but lacks detail on what 'information' actually includes (e.g., session ID, user, database). It does not compensate for the absence of an output schema by outlining expected return values, leaving some ambiguity for the agent.
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, and per the rubric, a baseline of 4 is appropriate since there is no parameter semantics for the description to clarify. The description adds no parameter-related information, but none is needed.
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 identifies a clear resource ('current database session'), distinguishing it from sibling tools like active_sessions (which likely covers all sessions) and locks. It succinctly states the tool's core purpose without ambiguity.
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. While 'current database session' implies a distinction from active_sessions, it does not explicitly state when to prefer this tool or mention any exclusions, leaving the agent to infer 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?
With no annotations, the description must carry the full burden of behavioral disclosure. It lists the output categories (columns, types, keys, indexes) but does not explicitly state that the operation is read-only, requires table existence, or detail error conditions. The verb 'Show' implies a read operation but is not explicit.
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, grammatically complete sentence that is front-loaded with the verb 'Show' and enumerates the exact metadata returned. It is concise, with no redundant or vague phrasing.
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 describe tool with two parameters and no output schema, the description adequately covers the purpose and the content of the output. It could add notes on prerequisites or error behavior, but given the tool's simplicity and clarity, it is largely complete.
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 already describes both parameters (table and schema) with 100% coverage. The description does not add further semantics about the parameters, but it does clarify their purpose in the operation. This meets the baseline for schema-sufficiently-covered 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 states what the tool does: it shows columns, types, primary keys, foreign keys, and indexes for a table. The verb 'Show' and the specific resource 'table' make the purpose unmistakable and distinguish it from siblings like list_tables and query.
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 is given on when to use this tool versus alternatives, but the description implies its use for inspecting table structure. It does not mention list_tables for discovering tables or query for data retrieval, leaving usage somewhat implicit.
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?
With no annotations, the description carries the full burden of explaining behavior. It communicates a read-only listing operation, but does not disclose details such as whether system schemas are included, required privileges, or any potential performance implications. It is not misleading but is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that directly conveys the tool's function without unnecessary words. It is concise and front-loaded, earning a top score for efficiency.
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 (no parameters, no output schema, listing operation), the description is largely complete. However, it omits contextual details like whether 'accessible' includes versus excludes system schemas, which could be relevant for agents working in Oracle. This minor gap prevents a perfect score.
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 there is no schema information to clarify. The baseline for zero parameters is 4, and the description appropriately focuses on the action and scope rather than inventing parameter details.
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 ('List') and resource ('all accessible schemas'), with a specific scope ('in the Oracle database'). This distinguishes it from sibling tools like list_tables, which target tables, 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?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, typical scenarios, or exclusions (e.g., system schemas), leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. The verb 'Show' suggests a read-only operation, but the description does not disclose potential side effects, required privileges, or performance impact. It goes slightly beyond a tautology by naming what is shown, but lacks depth.
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 words. Every word contributes to the meaning, making it highly concise and easy to parse.
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 (no parameters, no output schema, no annotations), the description provides the essential purpose but omits details about return format or privileges. Still, it is mostly complete for a basic diagnostic tool, though additional context would make it fully 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?
This tool has zero parameters, so the schema is trivially complete. The description does not need to explain parameter semantics, and the baseline for 0 parameters is 4.
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 'Show' and clearly identifies the resource: active locks and blocking sessions. This distinguishes it from sibling tools like active_sessions, which focus on sessions rather than lock-specific information.
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 a diagnostic use case for viewing locks and blockers but does not explicitly state when to use it over alternatives such as active_sessions or session_info. There is no mention of troubleshooting lock contention or deadlocks, leaving the context only implied.
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?
With no annotations, the description carries the full burden of behavioral disclosure. It reveals that the tool performs destructive operations (DROP, TRUNCATE) and requires readwrite mode, which is valuable safety-relevant information. It does not mention auto-commit or reversibility, but the destructive examples are a strong signal.
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 sentences, front-loaded with the core purpose and immediately followed by the essential prerequisite. No filler or redundant detail, every word earns its place.
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 single-parameter tool with no output schema and no annotations, the description covers the key elements: what the tool does, what the parameter should contain, and a required environment condition. It lacks details on return values or error behavior, but these are less critical for DDL execution.
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 documents 'sql' as 'DDL SQL statement' (100% coverage), so the baseline is 3. The description adds value by enumerating concrete DDL statement types, clarifying the expected content of the parameter beyond the schema's terse description.
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 'Execute DDL statements' with specific examples (CREATE, ALTER, DROP, TRUNCATE), making the tool's purpose unambiguous. It distinguishes from sibling tools like 'query' and 'execute' by explicitly scoping to DDL.
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 DDL statements and notes the ORACLE_MODE=readwrite prerequisite, but it does not explicitly state when to use this tool versus alternatives like 'query' or 'execute'. No exclusions or alternative recommendations are provided.
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?
With no annotations provided, the description carries the full burden. It discloses critical behavior: the readwrite mode requirement and auto-commit on success. This goes beyond a simple execution statement, though it does not describe error handling or return format.
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, compact sentence set with three clear clauses: purpose, prerequisite, and behavior. Every word contributes meaning, and it is front-loaded with the action.
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 aspects for a DML execution tool: what it executes, the mode requirement, and commit behavior. It does not mention output or error handling, but since there is no output schema, such details are less necessary. Overall, it is adequately complete for its complexity.
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 coverage is 100% for both parameters, and the description adds no additional semantics beyond what the schema already provides. The schema already explicates the sql and binds fields, so the description provides no extra value here.
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: executing DML statements (INSERT, UPDATE, DELETE, MERGE). It uses a specific verb plus resource and distinguishes from sibling tools like query (SELECT) and ddl (DDL).
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 prerequisite (ORACLE_MODE=readwrite) and the statement types covered, implying it is for DML as opposed to other siblings. However, it does not explicitly name alternatives for SELECT or DDL, so it lacks explicit exclusions.
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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