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

No annotations are provided, so the description carries the full burden. It indicates a read-only summarization operation with no destructive behavior, but lacks details on filtering behavior, performance, or what happens if no data matches. Basic transparency is present but not comprehensive.

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: first clearly states the tool's function with specific details, second highlights its essential use case. No unnecessary words; front-loaded with key information.

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

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

Given the tool is a simple summary report without an output schema, the description does not specify the return format (e.g., counts, amounts). For adequate completeness, it should hint at what the summary contains. The age buckets are well-stated, but more detail on returned data would improve it.

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

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

Schema description coverage is 100% with each parameter described as 'Filter by ... (optional).' The description adds context that results are grouped by currency and entity, providing slight extra meaning. Baseline is 3, and the description meets it without exceeding.

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 summarizes open breaks by specific age buckets (0-2, 3-5, 6-10, 11-30, 30+ days) grouped by currency and entity. It also mentions the use case (daily ageing review), distinguishing it from sibling tools that likely provide raw break 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?

The description says 'Essential for daily ageing review,' implying when to use it, but does not explicitly state when not to use it or mention alternatives like im_get_aged_breaks for detailed data. The guidance is implied but not fully explicit.

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

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

No annotations are provided, so the description carries the full burden. It indicates a read-only operation showing schema details, but does not disclose potential side effects (none expected), permissions needs, or response format. Adequate but not rich.

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, front-loaded with the action, no redundant words, clearly structured. Every sentence provides 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?

For a simple tool with one parameter, no annotations, and no output schema, the description is sufficiently complete. It tells what the tool does and when to use it. Could mention that the output is a table-like result or that it is safe to call repeatedly.

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% with description for table_name including example usage. The tool description adds no additional meaning beyond the schema; it restates the purpose. Baseline of 3 is appropriate.

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

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

The description explicitly states the tool shows column names, data types, nullability, and default values for a given table, and adds context about helping understand table structure before writing queries. This clearly distinguishes it from sibling tools like im_list_tables (lists tables) and im_execute_select (runs queries).

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 when understanding table structure before writing queries ('Helps understand IntelliMatch table structure before writing queries'), but does not explicitly state when to avoid the tool or mention alternative tools for similar tasks. No explicit guidance on prerequisites or 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?

No annotations provided, so the description fully carries the burden. It clearly discloses that only read operations are permitted and lists all blocked operations. This gives the agent a complete safety picture.

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, front-loaded with the core action, and no redundant words. Every sentence adds 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?

Given the tool's simple nature (2 parameters, no output schema), the description is complete: it explains what it does, constraints, and when to use it. No missing information.

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 descriptions in the schema are already clear. The tool description repeats the same information (e.g., 'Comments are not allowed', max_rows cap) without adding new parameter-level detail. Thus it does not add value 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 clearly states that the tool executes ad-hoc SELECT queries and positions it as an escape hatch when dedicated BAU tools are insufficient. This distinguishes it from sibling tools like im_get_breaks or im_search_items.

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?

Explicitly states that only SELECT and WITH…SELECT queries are allowed, blocking INSERT, UPDATE, DELETE, DDL, EXEC, and comments. It also guides when to use it: as an escape hatch when BAU tools don't cover the query.

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. It states the tool finds items, implying a read-only operation, but does not explicitly confirm idempotency, lack of side effects, or any authorization needs. The description is adequate but could be more transparent about its read-only nature and whether it returns summary or detailed data.

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 long, front-loading the core purpose and adding a brief usage context. Every word is useful; there is no redundancy or unnecessary detail, making it highly efficient for an AI agent.

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

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

Given the tool has 4 parameters, no output schema, and no annotations, the description adequately covers its purpose and context for aging reviews. However, it lacks detail on output format (e.g., whether it returns a list or counts) and default behavior (e.g., ordering). For a simple filter tool, this is reasonable but slightly incomplete.

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

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

Schema coverage is 100% with clear parameter descriptions, so the description adds little semantic value. It mentions 'older than a specified number of days' which duplicates the age_days parameter description. No examples or additional usage guidance for the filter parameters are provided, making the description redundant with 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 clearly states 'Find break/exception items older than a specified number of days' with a specific verb (Find) and resource (aged breaks/exception items). It distinguishes from siblings like im_get_breaks (all breaks) and im_break_aging_report (likely a report) by focusing on aged items and being a direct retrieval tool.

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

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

The description provides clear context: 'Critical for break ageing reviews and escalations,' indicating when to use this tool. However, it does not mention when not to use it or provide explicit alternatives among the listed siblings, which include im_break_aging_report and im_get_breaks.

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

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

No annotations provided, so description carries the burden. It discloses output content ('both sides, amounts, differences, and history') but lacks mention of permissions, rate limits, error cases, or whether it modifies state (implicitly read-only).

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 fluff. Every word adds value: identifies action, resource, key identifier, and output highlights.

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 output schema, the description compensates by listing key output fields (amounts, differences, history). Input is sufficiently described. Could mention if it returns a single object or multiple, but overall complete for a detailed view tool.

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

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

Schema coverage is 100% and the parameter description already states 'The exception/break ID'. The tool description adds no additional meaning or format details, so baseline 3 is appropriate.

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

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

The description clearly states the tool gets full details of a specific break/exception by ID, distinguishing it from sibling tools like im_get_breaks (list) and im_get_aged_breaks (aging report). The verb 'Get' and resource 'break details' are specific and unambiguous.

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 when you have an exception ID, but does not explicitly state when not to use or mention alternatives among the 19 sibling tools lacking differentiation criteria.

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

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

No annotations provided, so description carries burden. It lists returned fields (references, amounts, currency, age, status) but does not disclose safety (read-only), pagination limits (from schema), or rate limits. Adequate but not comprehensive.

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: first states purpose, second adds key context and output fields. No fluff, front-loaded with critical information.

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?

Tool has 6 optional parameters, no output schema. Description covers purpose, output fields, and usage context. Could benefit from defining what a 'break' is, but sufficient for agents with domain knowledge.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds no new meaning beyond 'optional filters' and return fields; it doesn't elaborate on parameters or provide examples. Schema already covers each parameter well.

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 action ('Retrieve open break/exception items') and resource ('break items'). It adds context ('Key morning-check tool') but does not explicitly differentiate from siblings like im_get_aged_breaks or im_get_break_details.

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

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

Implies morning use ('Key morning-check tool') but lacks explicit guidance on when not to use this tool or mention of alternatives such as im_get_aged_breaks for aged breaks.

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. It mentions that the password is never shown, which is good, but does not disclose other behavioral traits such as whether the configuration is cached, if any side effects occur, or if it requires special 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 exceptionally concise with two sentences that convey the essential purpose and a key constraint (password hidden). It is front-loaded and every sentence adds 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?

Given no parameters and no output schema, the description adequately covers the tool's function. It could mention the nature of the output (e.g., 'returns a JSON object'), but is otherwise sufficient for a simple read-only configuration tool.

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

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

The input schema has zero parameters and 100% coverage trivially. With 0 parameters, the baseline is 4. The description does not need to add parameter meaning, and it does not provide any extra detail, which is acceptable.

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

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

The description clearly states the tool's purpose: 'Show current MCP server configuration', specifying the resource (configuration) and the action (show). It distinguishes from sibling tools that focus on breaks, tables, and other specific tasks.

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

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

The description implies usage for retrieving configuration, but does not provide explicit guidance on when to use this tool versus alternatives like im_test_connection or im_list_tables. No exclusions or conditions are given.

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 full burden but only states that the tool generates a summary. It does not disclose read-only nature, permissions, or behavior for missing data, leaving significant gaps in transparency.

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

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

The description is a single sentence that front-loads the action and includes key elements. It is extremely concise with no wasted words.

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

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

The description names the four components of the summary, which is adequate for a simple reporting tool with two optional parameters and no output schema. However, it lacks any indication of the return format or structure.

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% with descriptions for both parameters. The tool description adds context about the report purpose but does not enhance parameter semantics beyond what the schema already provides. Baseline score of 3 is appropriate.

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

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

The description clearly states the tool generates a daily BAU reconciliation summary with specific components (items loaded, match rates, open breaks, job status). However, it does not explicitly differentiate from sibling tools like im_get_recon_summary or im_get_match_statistics.

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

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

The description implies usage for daily summaries via 'for a given date', but provides no guidance on when not to use it or alternatives among the many sibling reporting tools.

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

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

No annotations provided. The description implies a read-only operation (retrieving logs) but does not confirm side effects, permissions needed, or behavioral traits like pagination. It is adequate but 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.

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

Description is a single sentence that covers purpose and key filters. It is appropriately sized for the tool's complexity, though adding a second sentence on output could improve structure without reducing conciseness.

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

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

With no output schema and no annotations, the description should provide more detail about return format, pagination, or example usage. The current description is too brief for a tool with 5 parameters and moderate complexity.

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% with clear parameter descriptions. The description adds minimal extra context (e.g., 'partial match' for job_name) beyond what the schema already provides. Baseline of 3 is appropriate.

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

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

The description clearly states the action (retrieve) and the resource (errors and warnings from IntelliMatch error log), with filtering capabilities, distinguishing it from sibling tools that focus on breaks, tables, or other 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?

No guidance on when to use this tool versus alternatives like im_get_break_details or im_get_item_details. The description lacks explicit context for when not to use it or mention of prerequisites.

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

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

The description discloses the output (columns, match result, linked exception) but does not address side effects, authorization needs, rate limits, or error handling. With no annotations provided, the description carries the full burden, and this is acceptable for a simple read operation 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.

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

The description is a single sentence of 19 words, which is concise and front-loaded with the main action. It could be slightly expanded for clarity but is efficiently structured.

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 simple parameter set (1 required) and no output schema, the description adequately specifies the return content. However, it lacks context on potential errors or behavior when the item does not exist, which would improve completeness.

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

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

The schema covers the parameter item_id with 100% description, and the tool description adds that the tool returns full details for that item. However, it does not elaborate on the parameter's format or provide examples, so it adds minimal value 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 clearly states the verb 'Get', the resource 'IntelliMatch item', and specifies the scope 'full details including all columns, match result, and linked exception'. It differentiates from sibling tools like im_get_break_details or im_get_breaks by targeting a specific item's comprehensive 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?

The description implicitly suggests using this tool when you need complete details of a single item, but it does not provide explicit guidance on when not to use it or what alternative tools (e.g., im_get_breaks for break-focused queries) are better suited for other needs.

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

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

Without annotations, description only implies read-only nature but does not explicitly state it, nor disclose other behaviors like authentication needs or rate limits.

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

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

Two sentences, front-loaded with action and resource, no wasted words.

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

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

Adequate for a status check tool, but lacks mention of return format or behavior of the limit parameter; could be more 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 already covers all parameters with descriptions; description adds no extra semantic value 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?

Clearly states the tool checks status of IntelliMatch batch jobs/processes, distinguishing it from other im_* tools like im_get_breaks or im_get_daily_summary.

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?

Implied usage for verifying overnight runs and identifying failures, but no explicit when-to-use or alternative 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. It discloses that the tool shows records received, loaded, and errors, implying a read-only operation. It does not mention side effects, permissions, or rate limits, but for a status check, the behavior is adequately conveyed.

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 three concise sentences with no fluff. It front-loads the purpose, then details output, then gives a use case. Every sentence adds value, making it efficient and clear.

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 output schema and 4 optional parameters, the description covers the main purpose and typical use case. However, it does not describe the return format or pagination behavior, which would be helpful for an agent using the output. It is mostly complete for a status check tool.

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

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

Schema coverage is 100%, so baseline is 3. The description adds no additional meaning to the parameters beyond the schema definitions (e.g., load_date, source_system, status, limit). It provides a general overview of output but no param-specific elaboration.

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 verb 'check' and the resource 'data load / file ingestion status'. It explains that it shows records received, loaded, and errors, and identifies it as a key morning check, which distinguishes it from siblings like im_get_job_status.

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 a clear usage context ('key morning check for confirming source data arrived') but does not explicitly exclude alternative tools or give when-not-to-use guidance. The context implies a typical use case.

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

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

No annotations provided, so the description must convey behavioral traits. It implies a read-only, non-destructive operation by stating 'Get... statistics', but does not explicitly confirm safety, discuss side effects, or mention any required permissions. For a simple reporting tool, this is minimally adequate.

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

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

The description is a single sentence that is clear and to the point. It front-loads the essential information (what the tool does) and lists key output metrics. However, some structural separation (e.g., bullet points) could improve readability for an AI agent.

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 three optional parameters, full schema coverage, and no output schema, the description provides sufficient context for a simple tool. It explains the purpose and output fields. However, it does not specify the aggregation level or response format, which would enhance completeness.

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

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

Schema coverage is 100%, so the input schema already documents each parameter. The description adds value by listing the types of statistics returned, but does not elaborate on how parameters affect the output or provide additional meaning beyond the schema definitions. Baseline 3 is appropriate.

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

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

The description clearly states it retrieves match rate statistics for a date range, listing specific metrics (total items, matched, unmatched, exceptions, break amounts by currency). It uses a specific verb 'Get' and resource 'match statistics'. However, it does not differentiate from sibling tools like im_get_break_details or im_get_unmatched_items, which serve related but distinct purposes.

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

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

No explicit guidance on when to use this tool versus alternatives. The description implies usage for obtaining match rate statistics, but lacks context on prerequisites, limitations, or conditions where other tools (like im_get_break_details) would be more appropriate.

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

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

With no annotations, the description carries full burden for behavioral disclosure. It confirms a read-only operation but does not mention pagination, response format, or any potential side effects. The description adds no behavioral traits beyond the tool name.

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 exceptionally concise, consisting of two short sentences that contain no redundant information. Every word adds value.

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

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

Given no output schema and one optional parameter, the description is adequate but not comprehensive. It omits details about return format, pagination, or error handling, which are relevant for a list tool.

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

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

Schema coverage is 100%, and the parameter description in the schema is clear. The description does not add any additional meaning or context for the parameter, so baseline of 3 is appropriate.

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

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

The description clearly states it lists all pending processes/jobs with a specific verb and resource. It distinguishes from siblings by focusing on pending/running status, but does not explicitly contrast with similar tools like im_get_job_status.

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

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

The description gives a use case ('monitoring live processing') but lacks explicit guidance on when not to use it or alternatives. Usage is implied rather than explicit.

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

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

The description implies a read-only operation ('List'), which is adequate but doesn't explicitly state non-destructiveness or any other behavioral aspects beyond the obvious.

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 unnecessary words, efficiently conveying purpose and output fields.

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?

Adequately describes output fields and purpose; minor gap: doesn't mention that default is active-only, but schema compensates.

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 covers the single parameter completely (100% coverage), so description doesn't need to add parameter details; baseline of 3 is appropriate.

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

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

Clearly states the tool lists reconciliation groups/sets and specifies the fields returned (name, type, active status), distinguishing it from siblings like im_get_recon_summary.

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

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

No guidance on when to use this tool vs alternatives (e.g., im_get_recon_summary) or mention of the active_only filter's implicit default behavior.

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

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

No annotations provided. Description only discloses output structure, not behavioral traits like read-only nature, default behavior for missing data, or any side effects. With no annotations, the description should cover these gaps.

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 redundancy. Front-loaded with purpose and output details. Every word earns its place.

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

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

Adequately describes output (counts, match %) for a tool with 2 optional params and no output schema. Given tool simplicity, missing behavior for missing data is a minor gap.

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

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

Schema coverage is 100% (baseline 3). Description adds meaning: explains that value_date defaults to today and recon_group is an optional filter. Provides format specification (YYYY-MM-DD) beyond 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?

Clearly states verb 'Get', resource 'reconciliation summary', and scope 'for a specific value date' with output details (matched/unmatched/exception counts, match % per group). Distinguishes from siblings like im_get_daily_summary.

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

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

Implies usage when summary statistics for a date are needed, but lacks explicit guidance on when to use vs alternatives like im_get_daily_summary or im_get_match_statistics. No 'when not to use' or exclusion criteria.

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

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

No annotations are provided, so the description carries the full burden. It states the tool retrieves data and shows all items with UNMATCHED status, but does not disclose any side effects, performance implications, or guarantee that it's read-only.

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: first states purpose, second adds a key detail. No redundant words, front-loaded with the main action.

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?

No output schema exists, and the description does not explain the return structure or fields in the items. It is adequate for a simple retrieval tool but lacks detail on what information is returned.

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% with detailed parameter descriptions. The description adds minimal value by noting 'optional filters' but does not elaborate on each parameter beyond what the schema already provides.

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 verb 'Retrieve' and the resource 'unmatched items', specifying the MATCH_STATUS = UNMATCHED condition. This distinguishes it from sibling tools like im_get_breaks or im_get_break_details.

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

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

The description implies usage for retrieving unmatched items by date and optional filters, providing clear context. However, it does not explicitly state when not to use this tool or mention alternatives like im_get_break_details.

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

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

No annotations are provided, so the description must convey behavioral traits. It describes the tool as listing tables (implying a read-only operation) but does not explicitly state readonly behavior, potential side effects, or authorization requirements.

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

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

Two concise, front-loaded sentences with no wasted words. The first sentence conveys action and parameter, the second provides usage 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 simple listing tool with one optional parameter and no output schema, the description fully covers the purpose, parameter, and use case.

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 value over the schema by specifying the default value 'dbo' for the 'schema_name' parameter. With 100% schema coverage, the description meaningfully supplements 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 clearly states the tool's action (list all user tables) and resource (in a given schema), distinguishing it from sibling tools like 'im_describe_table' and 'im_get_breaks' that perform different operations.

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 notes the tool is useful for discovering the IntelliMatch schema layout, providing clear contextual guidance. However, it lacks explicit instructions on when not to use it or mention of alternative tools.

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

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

With no annotations provided, the description should disclose behavioral traits such as read-only status, pagination behavior, or rate limits. It merely says 'Search,' implying a read operation, but does not clarify what happens with the limit parameter or the nature of the results. No side effects or constraints are mentioned.

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 efficient sentence that states the action and resource first, then the purpose. No unnecessary words, perfectly 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?

Given 8 optional parameters and no output schema, the description is too minimal. It does not explain the output format, ordering, or what 'items/transactions' entails. The brief note about 'investigating specific transactions' does not fill the gaps.

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

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

Schema coverage is 100%, so all parameters are documented in the schema. The description lists some parameters (reference, date, entity, currency, match status) but does not add meaning beyond what the schema already provides. Baseline 3 is appropriate.

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

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

The description clearly states the tool's action ('Search') and resource ('IntelliMatch items/transactions'), listing specific filter criteria. It distinguishes itself from more specific sibling tools like im_get_unmatched_items or im_get_break_details by being a general search.

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

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

The description only says 'Useful for investigating specific transactions,' which is vague and provides no guidance on when to use this tool vs alternatives like im_get_unmatched_items or im_get_break_details. There is no mention of when not to use it or any prerequisites.

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 fully bears the burden of behavioral disclosure. It states the tool tests a connection and returns two specific pieces of information, implying a non-destructive read operation. While it doesn't explicitly state safety, the behavior is clear enough.

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 with no wasted words. It front-loades the purpose and immediately specifies the return values. Every part contributes meaning.

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

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

Given the tool's simplicity (no parameters, no output schema, straightforward purpose), the description provides all necessary context to understand and use the tool correctly. It covers what it does and what it returns.

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?

There are zero parameters, so the description adds no extra meaning beyond the schema, which is already complete. The baseline for zero parameters is 4, but the description perfectly handles this case.

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

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

The description uses a specific verb ('Test') and resource ('MS SQL connection to the IntelliMatch database'), and clearly states the output (server version and database name). This distinguishes it from sibling tools, which are all about data operations or reporting.

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 the tool is for verifying connectivity, but does not explicitly state when to use it vs. alternatives, nor does it mention when not to use it. However, since no other sibling tool provides this function, the guidance is sufficient.

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