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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the tool is safe. The description adds that it 'looks up pricing and calculates estimated monthly cost', which is consistent. It does not discuss accuracy, caching, or data freshness, but overall transparency is good.

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

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

The description is well-structured with examples and a parameter list, but it redundantly repeats schema descriptions. The examples are helpful, and the front-loading is effective. Some pruning could improve 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?

Given no output schema, the 'Returns' line provides minimal description of return type. The tool has 8 parameters with one required, and the description covers use cases adequately. It could mention that cost components are returned, but it's sufficient for selection and 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 coverage is 100%, and the description adds value by providing examples that clarify parameter usage (e.g., hours_per_month=1 for storage, defaults like 730 hours). The examples demonstrate how parameters interact, going beyond mere 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 clearly states 'Calculate monthly cost for an Azure resource' and provides examples that differentiate it from siblings like azure_fetch_prices and azure_query_prices, which focus on raw price lookups. The verb 'calculate' and the resource 'Azure resource' are specific.

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?

Examples illustrate typical usage (e.g., VM cost, storage cost) but do not explicitly state when not to use it or mention alternative tools like azure_query_prices for raw price retrieval. The guidance is clear but lacks 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?

Annotations already indicate destructiveHint: true. The description adds that it returns a dictionary with cleared cache information but does not elaborate on side effects or required permissions. This is adequate given the annotations, but lacks extra context.

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 short and front-loaded with the main purpose, followed by a clear parameter list. No extraneous information. Efficient.

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 cache-clearing tool with no required parameters and no output schema, the description covers the functionality and parameter effects sufficiently. It does not discuss use cases or potential impacts, but for this tool it is complete enough.

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 100% coverage, providing descriptions for all four parameters. The description essentially replicates these parameter descriptions, adding no new meaning beyond defaults. Thus, it meets the baseline of 3.

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 directly states 'Clear Azure pricing cache', which is a specific verb-resource pairing. It clearly distinguishes from sibling tools like azure_fetch_prices or azure_calculate_cost, which are for data retrieval/computation.

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 lists parameters but does not indicate scenarios such as clearing cache to force updated pricing or avoiding unnecessary cache clearing.

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?

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds details about local caching for 24 hours, force_refresh behavior, and default fallback for services/regions, which are useful beyond annotations.

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

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

Well-structured with example and sections, but slightly verbose. The core purpose is clear in the first sentence, and the example is helpful.

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 4 parameters and no output schema, the description covers caching, return type (dictionary with status and summary), and examples. Lacks details on specific return keys and error handling, but overall sufficient.

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 repeats parameter descriptions already in the schema but adds no additional meaning beyond what is already provided.

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 'Fetch and cache Azure retail prices' and mentions the API and caching. It is specific about what it does but does not explicitly distinguish from sibling tools like azure_query_prices.

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 like azure_query_prices or when to use force_refresh. Examples show usage but lack conditions 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?

Annotations already declare readOnlyHint=true, and the description adds context (in memory and on disk, returns statistics) without contradicting annotations.

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 extremely concise with no wasted words, front-loading the action and including return type.

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 zero-parameter tool with annotations, the description covers the return type and scope, providing complete context.

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?

No parameters exist, so baseline is 4; description does not need to add parameter info.

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 specifies a clear action ('List') and resource ('cached services'), distinguishing it from siblings like 'azure_list_services' which list all services.

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 cached services but does not explicitly state when to use this tool over alternatives or provide 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?

Annotations indicate read-only, non-destructive behavior; the description adds details on optional service filtering, caching, pagination, and limits, providing useful behavioral context.

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

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

Concise, well-structured docstring with Args and Returns sections, no waste, front-loaded with purpose.

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 read-only list tool, the description sufficiently explains parameters and return format; no output schema but return description is adequate.

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

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

Schema coverage is 100% with defaults already documented; description repeats parameter info and adds return format, offering marginal value over 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 lists available ARM regions for a service or cached data, distinguishing it from sibling tools like azure_list_services.

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 through parameters but lacks when-not or alternative tool mentions.

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?

Annotations already indicate read-only and non-destructive behavior. The description adds important context: caching strategy (from_cache_only), pagination (max_pages), and limits (max_services). This goes beyond annotations.

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

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

The description is extremely concise with a clear purpose sentence, args list, and returns note. No unnecessary words.

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

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

For a list tool with no output schema, the description covers return type, caching, pagination, and limits. It is sufficiently complete given the parameter richness.

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 parameters are fully documented. The description does not add new parameter-level meaning beyond summarizing defaults and the return type.

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 (list) and what is returned (Azure service names for a region). It is specific but does not explicitly distinguish from sibling tools like azure_list_cached_services.

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 includes parameter defaults and a caching option, implying when to use cached data, but no explicit guidance on when to prefer this tool over alternatives like azure_list_cached_services.

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?

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds valuable context beyond annotations: it explains the caching behavior ('If data is not cached, it will be fetched automatically') and the return format (dictionary with matching items and summary). No contradictions.

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

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

The description is well-structured: a concise one-line purpose, then brief caching behavior, followed by clear examples, and a bulleted args list. Every sentence adds value, no fluff, and 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?

Given 8 parameters, no output schema, and openWorldHint=true, the description adequately covers caching behavior, examples, return type, and parameter usage. It lacks explanation of the 'page' parameter and pagination, but overall it is sufficient for an agent to use the tool effectively.

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 88% (7 of 8 parameters have descriptions). The description repeats parameter details but adds examples that show usage patterns for service, sku_contains, and price_type. However, the 'page' parameter is not documented in the schema or description, so the description does not fully compensate for that gap.

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 'Query cached Azure pricing data with flexible filters', specifying the verb 'query', the resource 'cached Azure pricing data', and the capability 'flexible filters'. It distinguishes itself from siblings like azure_fetch_prices and azure_calculate_cost by focusing on querying a cache.

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 on when to use the tool: for querying cached Azure pricing data with automatic fetching if not cached. Examples demonstrate various use cases (VM pricing, Databricks, reserved instances). However, it does not explicitly state when NOT to use it or name alternative tools, though the cache vs. fetch distinction is implied.

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?

Annotations indicate non-read-only and non-destructive behavior. The description explicitly states that output_path defaults to overwriting the input file, disclosing a key behavioral trait. However, it does not cover authorization requirements 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?

The description is well-structured with a clear purpose sentence, an illustrative example, and a bulleted Arg list. While not extremely concise, it efficiently uses space without redundancy.

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

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

Given the tool has 9 parameters with 2 required and no output schema, the description covers all essential aspects: inputs, defaults, and return value (status dictionary). It lacks only fine-grained details like error conditions or exact return format.

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?

With 100% schema coverage, baseline is 3. The description adds value by providing an example and an Args block that explains each parameter in context (e.g., 'Optional sheet name (overrides sheet in data_range)') and indicates defaults, going beyond the schema alone.

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 ('Add a chart to an Excel worksheet') with a specific verb and resource. Among siblings, it is distinct from other Excel tools like excel_add_sheet, making its purpose 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 provides an example but no explicit guidance on when to use this tool versus alternatives or when not to use it. Usage is implied (when a chart is needed), but no exclusions or contextual advice 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?

The description adds behavioral details beyond annotations: creation of an empty sheet, insertion position options, and overwrite behavior via output_path. However, it does not disclose behavior when the sheet name already exists or error handling.

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 concise and well-structured: a one-line summary, brief explanation, three clear examples, parameter list, and return note. Every sentence adds value without redundancy.

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

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

Given the tool's simplicity and lack of output schema, the description covers the core functionality, parameter behavior, and return value. It is complete for an agent to invoke correctly.

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

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 includes an Args section that reiterates schema descriptions but adds value through examples showing parameter combinations and usage patterns.

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 starts with 'Add a new sheet to an Excel workbook', which is a specific verb and resource. It clearly distinguishes from siblings like excel_add_chart or excel_list_sheets, as no other sibling adds a sheet.

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 examples and parameter details, making the usage context clear. However, it does not explicitly state when not to use this tool or mention alternatives for related operations (e.g., if sheet exists).

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?

Annotations already provide destructiveHint=true. The description adds that it returns a status dictionary with deletion details, but does not disclose error handling behavior (e.g., if comment is missing). With annotations covering the core behavioral trait, the description provides some additional but incomplete context.

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 very concise with a clear purpose stated first. The Args and Returns sections are structured and add value without unnecessary verbosity.

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

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

Given the tool's complexity (delete operation, 4 params, no output schema), the description covers the basic operation but lacks completeness on edge cases, default behavior for output_path, and potential errors. It is adequate but not thorough.

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 schema already documents all parameters. The description repeats parameter information without adding new semantics or usage constraints beyond what is in 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 action ('Delete a comment') and the target ('from a specific cell'), implying an Excel file context. With sibling tools like pptx_delete_comment and word_delete_comment, the tool is well-distinguished as the Excel-specific deletion 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?

No guidance on when to use this tool versus alternatives. No prerequisites mentioned (e.g., file must exist, comment must be present). No mention of when not to use it or what to do if the comment doesn't exist.

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?

Annotations indicate non-readonly and non-destructive. The description adds extensive detail: GFM parsing, auto-detection, formatting, numeric coercion, formulas, sheet naming from headings, and argument-size limits for markdown_file.

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

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

The description is well-structured with bullet points and a comprehensive example. It is appropriately detailed for a complex tool, though slightly lengthy; 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 complexity, the description covers all behavioral aspects, constraints (sheet name length, input size limits), and return value. It includes a rich example and does not rely on an output 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% and already explains each parameter clearly. The description adds an example and clarifies markdown_file usage for large inputs, but does not introduce new semantic meaning 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 tool converts Markdown tables to an Excel workbook, specifying the verb and resource. It distinguishes from sibling tools like excel_add_sheet and word_from_markdown by focusing on creation from markdown content.

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 calls it 'the primary tool for creating Excel workbooks from text content' and explains inline vs file input, offering clear usage context. However, it does not explicitly exclude other tools like excel_add_sheet for non-table content.

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?

Annotations already indicate read-only behavior, and the description adds context by detailing the output (visibility, dimensions, tables, data validations). It provides an example and parameter details, enhancing transparency beyond the annotations.

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

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

The description is well-structured with a clear purpose, example, and parameter breakdown. It is slightly verbose with a 'Returns' section that duplicates schema info, but overall it is efficient and 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 the tool's simplicity, the description covers the essential aspects: what it does, how to use it, and what it returns. It lacks an explicit output schema but adequately describes the return value. Annotations cover safety, so no 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%, and the description's parameter descriptions largely repeat the schema. The example usage provides minimal additional context for parameter semantics, but does not significantly enrich meaning 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 tool lists all sheets in an Excel workbook with properties. It uses a specific verb-resource pair ('list sheets') and distinguishes itself from sibling Excel tools that perform different actions (e.g., adding or modifying sheets).

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 by stating the tool's purpose but provides no explicit guidance on when to use it versus alternatives. It does not mention when not to use it or suggest other tools for related tasks.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds that it returns a dictionary, which is basic. No additional behavioral traits (e.g., about caching, dynamic nature) are disclosed.

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

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

The description is very concise with two short sentences. However, there is slight redundancy: 'List supported document formats and their availability' implies a mapping, and the 'Returns' line restates this. It is still efficient but could be merged.

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 no parameters and no output schema, the description is vague about which document formats are supported (e.g., Word, Excel, PowerPoint) and whether the list is static or dynamic. More context is needed for a complete understanding.

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 tool has zero parameters, and the schema description coverage is 100%. The description does not need to add parameter semantics; the baseline for zero params is 4.

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 lists supported document formats and their availability. The verb 'list' and resource 'supported formats' are specific, and it distinguishes from sibling tools that deal with services, prices, or document manipulation.

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 on when to use this tool versus alternatives or when not to use it. The description only states the function, leaving the agent to infer context from the name.

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?

Annotations already provide readOnlyHint=true and destructiveHint=false, so the agent knows it's a safe read operation. The description adds the list of checks and configuration details but does not expand on behavioral traits beyond what annotations imply. With annotations present, the description adds some context but is not essential.

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

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

The description is well-structured with sections for purpose, replacements, examples, args, and returns. It is somewhat lengthy but front-loaded with the main purpose. Every section adds value, and the examples are helpful.

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

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

Given the tool's complexity (3 parameters, nested object, no output schema), the description is thorough: it explains all checks, the audit_config structure, and return format. The 'Replaces' line and examples provide sufficient context for an agent to use the tool correctly.

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

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

The description provides an 'Args' section that explains each parameter, including the enum values for 'checks' and the subfields of 'audit_config', which go beyond the schema's descriptions. Schema coverage is 67%, and the description compensates by detailing optional configuration.

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 starts with a clear verb+resource: 'Audit documents for completeness, placeholders, and issues.' It also lists the tools it replaces, distinguishing it from siblings like excel_audit_placeholders and word_audit_completion.

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 explicitly states 'Replaces: excel_audit_placeholders, word_audit_completion, word_audit_sow, pptx_audit_placeholders,' which tells when to use this tool. Examples further clarify usage scenarios. It does not explicitly say when not to use, but the replacement guidance is strong.

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?

Annotations provide readOnlyHint=false and destructiveHint=false; the description adds behavioral context such as operation-specific behavior per app (e.g., resolve/reopen for Word only), target variations, and default output overwrite. No contradictions.

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

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

The description is lengthy but well-structured with examples and separate sections for Args and Returns. The main purpose is front-loaded. Could be slightly more concise, but clarity benefits from examples.

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?

All 8 parameters are described with usage details. Despite no output schema, the description states return type ('dictionary'). Covers all operations and supported apps comprehensively.

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. The description adds meaning beyond schema by detailing target usage per operation/app and providing concrete examples (e.g., 'target' for Excel add is a cell reference, for Word add is a text span).

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 'Manage comments in Word, Excel, or PowerPoint documents.' It lists specific operations and replaces several sibling tools (e.g., excel_add_comment, word_get_comments), clearly distinguishing its unified functionality.

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 detailed examples for each operation and app, explaining how target varies. It mentions replaced tools but does not explicitly state when to avoid this tool in favor of others for non-comment tasks (e.g., reading content via office_read).

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?

Annotations show readOnlyHint=false and destructiveHint=false. The description implies a read operation ('get help'), but does not clarify mutation potential. No contradiction, but the description could better explain side effects or state changes.

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 4 sentences, front-loaded with purpose, then usage guidance. No redundant information; every sentence 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 no output schema, 5 parameters, and numerous sibling tools, the description provides adequate context for a discovery tool but lacks details on return format and specific parameter behavior, making it partially 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?

With 0% schema description coverage, the description adds value by explaining the relationship between 'goal', 'task', and optional parameters. However, it omits explanation for 'format' and 'constraints' details, leaving gaps.

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 'Get structured workflow help and recommendations for office document work,' using a specific verb and resource. It distinguishes itself from sibling tools by positioning as a discovery entry point for systems architecture and consulting workflows, not a direct action 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 explicitly says 'Use this as the preferred discovery entry point...' and provides guidance on preferring 'goal' plus optional parameters over 'task'. It lacks explicit when-not-to-use or alternatives, but the context is clear.

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?

Annotations indicate readOnlyHint=false and destructiveHint=false. The description adds valuable behavioral details: auto-detects document format, defaults to overwriting input unless output_path specified, and explains target parameter behavior per app. No contradiction with annotations.

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

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

Well-structured: one-line summary, followed by auto-detection note, then comprehensive examples, and finally Args. Information is front-loaded. Every sentence is necessary given the multi-application 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?

Given 6 parameters, multiple document types, and no output schema, the description covers all essential aspects: supported formats, target syntax, default behavior, and return value. It is complete enough for an agent to invoke the tool correctly.

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

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

Schema coverage is 100%, so parameters are already documented. The description enhances understanding by providing detailed explanations and examples for the 'target' parameter across different document types, which is not fully captured in the 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?

Description clearly states 'Insert an image into a Word, Excel, or PowerPoint document.' It specifies supported formats (PNG, JPG/JPEG, GIF) and auto-detection. This distinguishes it from sibling tools like excel_add_chart and office_patch, which serve different 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?

Provides clear context for use via examples for each application type (Word, Excel, PowerPoint). Although no explicit 'when not to use' is given, the examples effectively guide the agent on target syntax and parameter usage. Alternatives among siblings are not mentioned, but the tool's unique function is apparent.

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?

Annotations declare readOnlyHint: true and destructiveHint: false, and the description consistently describes an inspection (read-only) operation. The description further adds behavioral context such as auto-detection of format and unified replacement of many tools, fully aligning with annotations.

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

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

The description is well-structured: a concise first-line summary, a note on auto-detection, a replacement list, a comprehensive examples section, and an Args section. All sentences add value, no redundancy.

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

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

Given the tool's complexity (3 parameters, read-only, no output schema), the description fully covers necessary context. It explains how to use the tool with different document types, lists all inspection options, and provides clear examples. The return type is mentioned as a dictionary.

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%, but the description provides extensive additional meaning: it explains each allowed 'what' value with context, describes the 'target' parameter's usage for different document types, and includes examples. This goes beyond the schema's minimal parameter 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 states the tool inspects document structure and metadata, auto-detects format, and lists many specific inspection types. It clearly differentiates from sibling tools like office_read, office_patch, and the replaced tools such as excel_list_sheets by stating it replaces them.

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 explicitly lists which tools this tool replaces, providing clear guidance on when to use it instead of alternatives. It also explains auto-detection of document format and includes examples covering common use cases.

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?

Annotations indicate mutation (readOnlyHint=false, destructiveHint=false). Description adds context: track_changes default, overwrite behavior, and critical note about PPTX bullets. No contradiction with annotations.

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

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

Well-structured with examples and bolded important note. Slightly lengthy but each section adds value; front-loaded with the core 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, but description explains return format. Covers all necessary aspects: file path, changes formatting, track_changes, output_path, and PPTX specific behavior. Complete for a multi-document patching 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 has 80% description coverage. Description adds meaning by explaining target formats across document types (cell refs, placeholders) and the bullet constraint for PPTX. The 'mode' parameter is not mentioned in description, but the overall guidance is valuable.

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 'Apply edits to Word, Excel, or PowerPoint documents.' and lists the tools it replaces (e.g., excel_patch_cell, word_patch_section), making the purpose unambiguous and distinct from sibling tools.

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

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

Provides detailed examples for each document type and important notes for PowerPoint. Lacks explicit when-not-to-use or alternative suggestions, but the coverage of use cases is thorough.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false. Description adds auto-detection behavior, parameter details (e.g., scope specifics per document type), return type info, and notes on unimplemented features, providing useful context beyond annotations.

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

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

Well-structured intro, replacements list, examples, and parameter docs. Each section serves a purpose. Slightly verbose due to examples, but they enhance clarity. Good front-loading of key info.

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?

Covers all parameters, return types, supported document types, and includes examples. Notes limitations (scope not implemented for Word/PPT). With no output schema, description adequately explains what to expect. Complete for a read-only 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?

Input schema has 100% description coverage, but description's Args section adds deeper detail for each parameter (e.g., valid file extensions, scope format for Excel/Word/PPT, explanation of include_formulas). Significantly enriches meaning 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?

The description clearly states it reads content from Word, Excel, or PowerPoint documents, auto-detects format, and extracts in requested output format. It lists replacements (word_extract, etc.) distinguishing from sibling tools.

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?

Description explicitly names alternative tools that this replaces, guiding when to use this. Examples illustrate usage. However, no explicit when-not-to-use or exclusion criteria beyond replacements.

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?

Annotations indicate readOnlyHint=false and destructiveHint=false. The description adds value by explaining that the tool updates 'in-memory defaults', is non-destructive, and only affects subsequent operations. No contradiction with annotations.

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

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

The description is concise (3 sentences plus structured Args/Returns), front-loaded with the purpose, and every sentence adds value. No redundancy.

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

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

Given 3 parameters (1 required), no output schema, and annotations already covering mutation behavior, the description fully explains the tool's purpose, parameters, and effect. Return value is described as 'Updated identity configuration', which is sufficient.

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. The description adds context beyond field names: examples like 'Jane Doe' for name, and clarity that identity is email or alias, initials are optional overrides. This provides practical guidance.

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

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

The description clearly identifies the tool's action ('set default commenter identity') and its resource ('for subsequent comment operations'). It distinguishes from sibling tools like office_comment by explaining that this tool configures defaults used by add-comment tools when the author argument is omitted.

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 specifies when to use: before comment operations to set author defaults. It explains that the identity is used by office_comment and format-specific add-comment tools when author is omitted. While it doesn't explicitly list when not to use, the context is clear enough for an AI agent.

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?

Annotations already indicate readOnlyHint=false and destructiveHint=false. The description adds value by detailing per-operation behavior (e.g., create requires specific data structure, update_row uses row_index). It does not contradict annotations. However, it does not mention side effects like overwriting or undo, but given the annotation coverage, this is sufficient.

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

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

The description is well-structured with intro, replaced tools list, examples, and args section. It is somewhat long but justified by the tool's complexity (multiple apps and operations). Front-loads the core purpose and examples. Could be slightly more concise, but the format aids 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?

Given the tool's complexity (7 parameters, multiple app-specific behaviors, no output schema), the description covers inputs and return value adequately. It lacks error handling or permission notes, but sibling tools and annotations fill some gaps. The replaced tools list provides context for migration. Overall, a solid description.

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 71%, and the description explains parameters with context beyond the schema, especially table_id (per-app details) and data (nested structure for create). However, output_path and mode are present in schema but not described in the description. Examples help clarify usage, so overall good but not complete.

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 tables in Word, Excel, or PowerPoint documents. It lists replaced tools (e.g., excel_get_table, word_get_table), which distinguishes it from siblings. The verb 'manage' along with examples for get, add_row, update_row, create operations makes the purpose specific and actionable.

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 extensive examples for each operation and app, showing exactly how to use the tool. It lists replaced tools, implying when to use this instead. However, it does not explicitly contrast with siblings like office_read or office_patch, nor does it state when not to use this tool. The guidance is clear but could be more direct about 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?

Annotations indicate readOnlyHint=false and destructiveHint=false, which align with description. The description adds behavioral context about the two operations (copy and analyze) and notes that destination_path is ignored for analyze. No contradictions, but more detail on side effects (e.g., file creation) could be added.

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

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

The description is well-structured with a short summary, replaced tools list, examples, args, and returns. It is informative but slightly lengthy; could be trimmed slightly without losing clarity.

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 three parameters and lack of output schema, the description adequately covers usage, operations, and return style. It does not specify the exact return dictionary structure, but for a tool of this complexity, it is sufficient.

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 description enriches parameters with examples and operational context. It clarifies the operation enum usage and explains that destination_path is ignored for analyze, adding value 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?

The description clearly states the tool copies templates or analyzes template structure, providing specific examples for Excel, Word, and PowerPoint. It explicitly replaces multiple previous tools (excel_copy_template, word_copy_template, etc.), making its purpose distinct from sibling tools.

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 explains when to use the tool (for template operations) and lists replaced tools, giving context. However, it does not explicitly state when not to use it or suggest alternatives for non-template file operations.

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

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

Annotations indicate readOnlyHint=false and destructiveHint=false, but description adds value by disclosing that output_path defaults to overwriting input, which is a key behavioral detail. It does not mention other side effects like file locking or error conditions, but covers the main mutation 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 well-structured with sections and bullet points for layout values. However, the layout list is somewhat lengthy; could be more concise while retaining clarity. Still front-loaded with the primary purpose.

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 5 parameters (1 required), no output schema, and sibling tools, the description covers all parameters with defaults and examples. It also mentions using pptx_list_masters for more layouts. The return value 'Status with new slide_number' is sufficient for context.

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?

With 100% schema coverage, baseline is 3. The description adds meaning beyond schema: for layout_index it lists common values (0,1,5,6) with descriptions, for position it gives examples, and for output_path it states the default overwrite behavior. This enhances 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 clearly states 'Add a new slide to an existing presentation,' specifying the action and resource. It distinguishes from siblings like pptx_duplicate_slide or pptx_delete_slide by focusing on slide addition.

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 common layout_index values and position options, aiding selection, but lacks explicit guidance on when to use this tool versus alternatives like pptx_duplicate_slide or pptx_import_slide. No 'when to use' or 'when not to use' statements.

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

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

Annotations indicate non-read-only and non-destructive behavior, which description does not contradict. The description adds that header rows are bold and provides default dimensions, but lacks details on error handling, file modification behavior, or what the 'Status' return implies.

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 concise, consisting of a brief two-sentence overview followed by a structured parameter list. Every sentence is informative and necessary.

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 9 parameters (3 required) and no output schema, the description adequately explains purpose, parameters, and return value. However, it could be more complete by specifying behavior on missing files or slide numbers, and by clarifying the return type.

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 beyond the input schema by providing examples (e.g., ['Phase', 'Duration', 'Deliverables']) and explaining default values (left=1.0", top=2.0"). However, the schema already covers 44% of parameters with descriptions, so the description is supplementary.

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 'Add a data table to a slide' and elaborates on creating tables with column headers and optional data rows, specifying that the header row is bold. It is distinct from sibling tools which focus on other operations (e.g., excel_add_chart, pptx_add_slide).

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 explains the tool's functionality but does not provide guidance on when to use this tool versus alternatives like office_table or excel_add_chart. No explicit exclusions or context for selection 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?

Annotations already indicate destructiveHint=true; the description adds that deletion can target one or all comments, and that output_path defaults to overwriting the input. It mentions the return value is 'Status with deletion details', providing sufficient behavioral context beyond annotations.

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

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

The description is concise and well-structured, with a clear purpose statement followed by Args and Returns sections. Every sentence adds necessary information without redundancy.

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

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

Given the absence of an output schema, the description specifies the return type as 'Status with deletion details', which is adequate. It covers the core behavior but does not address error scenarios or edge cases; however, for a delete tool, this level of detail is reasonable.

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?

Input schema has 100% coverage with descriptions, but the description adds critical context: comment_index is optional and omitting it deletes all comments. This behavior is not fully captured in the schema, adding value.

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 deletes comments from a slide, specifying two modes: deleting a single comment by index or all comments when index is omitted. This distinguishes it from sibling tools like pptx_delete_slide, excel_delete_comment, etc.

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 explains the two usage modes (one comment vs all) and indicates required parameters (file_path, slide_number). However, it lacks explicit guidance on when not to use it or comparisons with alternatives, though the sibling context makes it clear it's for pptx comments.

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?

Annotations show destructiveHint=true. Description adds that output defaults to overwriting input and returns status with remaining count, providing useful behavioral context beyond annotations.

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

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

Description is well-structured with a front-loaded purpose sentence and a clear Args section. Appropriate length for the tool's simplicity.

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?

Covers main behaviors: deletion, default overwrite, return value. No output schema, but return described. Adequate for a simple deletion 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 description doesn't need to add much. It repeats parameter descriptions from schema and adds default for output_path, but adds minimal new meaning.

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?

Description clearly states 'Remove a slide from the presentation.' with a specific verb and resource. Siblings like pptx_add_slide and pptx_duplicate_slide indicate distinct actions.

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 says 'USE THIS to remove template slides you don't need or to clean up unwanted content.' Provides context for when to use, though no explicit when-not or comparison to siblings.

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?

Annotations already indicate mutation (readOnlyHint=false, destructiveHint=false). The description adds that it performs a 'full XML deep copy,' which is useful but doesn't disclose potential performance implications or other behavioral traits.

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

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

The description includes a summary, usage hint, and parameter list. However, the parameter section is redundant with the schema. It could be more concise by omitting the Args/Returns block.

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 includes 'Returns: Status with new slide number.' It explains the deep copy behavior. While it doesn't cover error cases, it is sufficiently complete for a duplicate tool with good annotations and 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 coverage is 100%, so the schema already documents all parameters. The description repeats the same information (e.g., 'Optional output path (defaults to overwriting input)'), adding no new semantic value beyond what the schema 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 'Copy a slide including all shapes, tables, and formatting,' which is a specific verb and resource. It distinguishes from sibling tools like pptx_add_slide or pptx_import_slide by focusing on duplication.

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 explicitly says 'USE THIS when you need multiple slides based on a template slide,' providing clear usage context. It does not mention when not to use or alternatives, but the guidance is sufficient and not misleading.

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 thoroughly details behavioral traits such as layout selection, theme fonts, internal unit usage, and font inheritance. It also includes a comprehensive slide mapping section. Annotations are non-contradictory (readOnlyHint=false, destructiveHint=false), and the description adds significant value beyond them.

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

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

The description is well-organized with clear sections (Features, Slide Mapping, Example) and front-loads the core purpose. The extensive example and feature list are justified by the tool's complexity, though minor condensation could improve 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?

Given the tool's complexity (5 params, detailed slide mapping), the description provides comprehensive guidance covering input methods, behavior, slide rules, and return value. The absence of an output schema is compensated by clear description of the return structure ('Status dictionary with file path and slide count').

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 all 5 parameters. The description adds context beyond the schema by explaining the purpose of markdown_file for large inputs and listing default font values. The detailed slide mapping rules further enrich 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 explicitly states 'Convert Markdown content to a PowerPoint presentation' and identifies it as 'the primary tool for creating PowerPoint decks.' It contrasts with sibling tools like pptx_add_slide by focusing on full deck creation from text.

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 presents this as the go-to tool for creating decks from markdown. It also provides guidance on using markdown_file for large inputs to avoid size limits. While it does not explicitly list when not to use it among siblings, the context implies its primary role.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds value by explaining that omitting slide_number returns notes from all slides, which is behavioral context beyond annotations.

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

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

The description is concise, front-loaded with the main action, and every sentence serves a purpose. No fluff or repetition.

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

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

For a simple read tool with no output schema, the description fully covers purpose, usage, parameter behavior, and return values. No 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% with descriptions for both parameters. The description adds meaning by clarifying the effect of omitting slide_number, which goes beyond the schema's 'Specific slide (omit for all slides)'.

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 'Read speaker notes from slides' which is a specific verb+resource. It is distinct from sibling tools like pptx_set_notes and pptx_delete_comment.

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 advises 'USE THIS to see existing notes before updating them', providing context for when to use. It also explains behavior without slide_number, but does not explicitly mention when not to use.

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 fully discloses behavior: hidden slides are skipped but editable, output_path defaults to overwriting input, and returns a status with visibility state. This adds context beyond annotations (readOnlyHint=false, destructiveHint=false) without contradiction.

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 structured with purpose first, then behavioral details, then a parameter list. It is fairly concise but includes an explanatory sentence about hidden slides that adds value. Minor inefficiency: the Args section largely mirrors the schema.

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 adequately describes return value. It covers all parameters, explains behavior and use cases, and provides enough context for an agent to use the tool correctly alongside 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 coverage is 100%, so baseline is 3. The description repeats parameter descriptions but adds minimal extra meaning beyond what's in the schema. However, it mentions the return value (status with visibility state), which is absent from the input 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 'Hide or unhide a slide' with a specific verb and resource. It explains the behavior of hidden slides (skipped but editable) and their use cases (backup or speaker-only material), distinguishing it from slide deletion or addition.

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 when to use (for backup/ speaker-only material) but does not explicitly exclude alternatives like deletion. Among siblings, this is the only hide/unhide tool, so usage is clear, but no explicit when-not-to-use 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?

Annotations declare readOnlyHint=false and destructiveHint=false. The description adds significant behavioral details: it validates layout/master chain, reuses existing layout if identical, imports only necessary layouts/masters, and copies notes optionally. This provides valuable context beyond annotations.

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

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

The description is well-structured: a one-line purpose, usage guideline, behavioral details, and then parameter list. It is concise at around 150 words with no fluff. The parameter list is slightly redundant given the schema, but it aids quick scanning.

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 7 parameters, no output schema, and returns a status dictionary as mentioned. The description covers the core behavior, layout/master handling, and return value. It does not discuss error conditions or permissions, but for a copy operation these are secondary. Adequate for the 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?

The input schema covers all 7 parameters with descriptions. The description lists the same parameters with similar context (e.g., 'Required when position=after'). It does not add new semantic meaning beyond the schema, so baseline 3 applies.

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 'Copy one slide from a source presentation into a target presentation.' This provides a specific verb and resource, and distinguishes itself from siblings like pptx_add_slide (which creates a new slide) and pptx_duplicate_slide (which duplicates within same deck).

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?

It explicitly says 'USE THIS when you need to lift a fully-designed slide across from one deck to another...' and explains the layout/master chain handling. While it doesn't list alternative tools, it implies this is for preserving complex assets, which guides usage well.

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?

Annotations already indicate readOnlyHint=true and destructiveHint=false. Description adds value by listing exact return fields (number, title, layout_name, etc.), providing behavioral context beyond what annotations offer.

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?

Well-structured with bullet points listing return fields, no fluff. Every sentence is informative and 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?

Simple overview tool with detailed description of return values. No output schema, but description fully compensates by listing each field and its meaning. Complete for its purpose.

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?

Single parameter 'file_path' with 100% schema coverage. Description repeats the schema description exactly. No additional semantic value added, but baseline 3 applies.

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?

Description clearly states 'Get an overview of all slides in a PowerPoint file' with specific verb and resource. It differentiates from sibling tools that modify slides by being a read-only overview.

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 advises 'USE THIS FIRST when working with an existing presentation to understand its structure before making changes,' providing clear context for when to use and implying alternatives for modifications.

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?

Annotations indicate non-read-only and non-destructive. Description reveals it appends to notes (a write operation) and that output_path defaults to overwriting input, which is important behavioral info. No contradiction.

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

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

Description is front-loaded with purpose and usage, then provides structured argument list. While slightly verbose with the Args section, it is clear and efficient overall.

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?

All necessary information is present: purpose, parameters with descriptions, default behavior for output_path, and what is returned. No output schema needed; return value is described.

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?

Input schema has 100% coverage, so baseline is 3. Description repeats parameter descriptions but adds clarifying context for the 'changes' object structure, providing marginal additional value.

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 verb 'append', resource 'first slide's notes', and purpose 'audit trail since PowerPoint doesn't have track changes'. Distinguishes from all sibling tools, as no other tool logs changes to notes.

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 says 'Use for audit trail since PowerPoint doesn't have track changes', providing clear context. Does not mention when not to use or contrast with alternatives like pptx_set_notes, but the use case is well defined.

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 annotations already declare readOnlyHint=true and destructiveHint=false, indicating a safe read-only operation. The description adds value by detailing the content types and return behavior (recommended layout_index and alternatives), which goes beyond the annotations. No contradictions exist.

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 concise and well-structured. It front-loads the purpose in the first sentence, then provides a bulleted list of content types. Every sentence contributes to understanding, 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?

For a simple tool with two parameters and no output schema, the description adequately covers purpose, parameter semantics, and return value. It mentions that the tool returns a recommended layout_index and alternatives, which is sufficient for an agent to understand what to expect. Minor gap: the exact format of the return is not specified, but it's acceptable given the tool's simplicity.

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 already describes both parameters with 100% coverage. The description enriches this by explicitly enumerating valid content_type values and their semantic meanings (e.g., 'title' for section title slides). This adds significant meaning beyond the schema's generic descriptions.

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

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

The description clearly states the tool's purpose: 'Get the best layout for a specific content type.' It uses a specific verb ('Get') and resource ('layout'), and the list of content types further clarifies its scope. This distinguishes it from sibling tools like pptx_add_slide, which likely creates slides with a given layout.

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 when to use the tool (when determining layout for content) but provides no explicit guidance on when not to use it or alternatives. There is no mention of conflicts with pptx_add_slide or other tools, leaving the agent without clear decision 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?

The description adds context that output_path defaults to overwriting the input file, which is a behavioral trait beyond annotations. However, it lacks details on error handling (e.g., invalid slide numbers) or side effects. Annotations (readOnlyHint=false, destructiveHint=false) are not contradicted.

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 concise: a one-sentence purpose, an illustrative example, and structured Args/Returns. Every sentence adds value with no redundancy.

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

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

For a simple reorder tool, the description covers the parameters and return value. Missing details on what the return 'Status' includes (e.g., success message or error object) and edge cases (e.g., duplicate slide numbers). Given the low complexity, the gaps are minor.

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 meaning beyond the input schema by specifying that new_order must be a complete list (1-based) and gives an example. Since schema description coverage is 100%, the baseline is 3; the additional guidance justifies a 4.

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 verb and resource: 'Change the order of slides in a presentation.' It distinguishes from sibling tools like pptx_delete_slide or pptx_duplicate_slide by focusing specifically on reordering, and provides a concrete example.

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 does not explicitly state when to use this tool versus alternatives like pptx_add_slide or pptx_delete_slide. It implies usage through the example but lacks 'when not to use' or alternative tool references.

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?

Annotations indicate readOnlyHint=false, consistent with 'Set' implying mutation. The description adds behavior details like the append parameter (add vs replace) and default output path behavior, providing useful context beyond annotations.

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

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

The description is concise with a clear structure: purpose, explanation, Args list, Returns. The Args list repeats schema info but is justified for readability; it is not verbose.

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 5 parameters and no output schema, the description covers purpose, parameter details, and return value preview. It lacks prerequisites but is adequate for a medium-complexity 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%, but the description adds extra context such as 'supports newlines' for notes_text and 'defaults to overwriting input' for output_path, enhancing understanding beyond the schema's field descriptions.

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

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

The description explicitly states 'Set speaker notes for a slide', which is a specific verb and resource. It distinguishes from siblings like pptx_get_notes.

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?

It says 'Use for talking points and context' but does not explicitly say when to use this tool versus alternatives (e.g., pptx_get_notes) or 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?

Beyond the annotations (destructiveHint: true), the description adds valuable behavioral details: the server will exit and VS Code will automatically restart it. This provides clear expectations for the agent.

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 concise, with a front-loaded purpose sentence. It includes clear usage context, an example, and return information without extraneous text.

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), the description thoroughly covers all aspects: purpose, usage scenario, behavior, example, and return value. No gaps remain.

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?

With zero parameters, the input schema is fully covered. The description includes an example call with no arguments, which is sufficient and aligns with the baseline for parameterless tools.

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 'restart' and resource 'MCP server', with the specific purpose of reloading code changes. It uniquely distinguishes itself from sibling tools which cover Azure, Office, web, etc.

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 explicitly states when to use this tool: after modifying tool modules in .github/mcp/tools/. It provides an example and explains the automatic restart behavior. Although alternatives are not explicitly excluded, no other tool performs this function.

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?

Annotations already indicate read-only and non-destructive behavior, but the description adds valuable detail: it performs a HEAD request with GET fallback, and returns fields like status_code, final_url, and content_type. This enriches the agent's understanding beyond annotations.

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

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

The description is concise and well-structured: a brief summary, followed by an explanation, examples, and a clear args/returns section. Every sentence is purposeful, and the key 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?

Given the tool's simplicity and the richness of the description, it covers all necessary behavioral aspects and return values. The description compensates for the lack of an output schema by listing the dictionary fields. Sibling tools are diverse, but the description uniquely identifies this tool's role.

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?

Input schema has 100% coverage with descriptions for all three parameters. The description reinforces these with an example showing default values and usage patterns (e.g., timeout=5, follow_redirects=True). While no new information is added beyond the schema, the examples provide practical context.

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

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

The description clearly states the tool's function: checking if a URL exists and is accessible. It specifies the HTTP method (HEAD/GET) and its utility for validating links. Among sibling tools like web_fetch or web_search, this tool has a distinct purpose, making differentiation easy.

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 explicitly recommends using this tool for validating links before including them in documents. While it does not list when not to use it or directly mention alternatives, the context is sufficiently clear about its primary 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?

Annotations already indicate readOnlyHint=true and destructiveHint=false, and the description adds behavioral details like fetching the page, extracting links, and optional filtering. No contradictions, and the description enhances understanding beyond annotations.

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

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

The description is well-structured with a clear purpose statement, example usage, and parameter list. It is concise but could be slightly tighter by not repeating schema details.

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 absence of an output schema, the description adequately explains the return type as a dictionary with links and text. It covers the core functionality and parameters, though it could mention potential error handling or size limitations.

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 parameters. The description repeats this information and adds an example, but does not significantly enhance meaning beyond what the schema 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 explicitly states 'Extract all links from a web page' with a specific verb and resource, and differentiates from sibling tools like web_extract_tables and web_fetch by focusing solely on hyperlink extraction.

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 by stating the tool is 'useful for discovering related pages or building navigation maps,' but lacks explicit guidance on when not to use it or alternatives for different tasks.

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?

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds behavioral context: it fetches the page, extracts HTML tables, and converts to structured format with headers and rows. This goes beyond annotations, though it omits details like rate limits or error handling.

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 concise, front-loading the purpose, then explaining the process, followed by examples and args. Every sentence is informative, 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 lacks an output schema, and its return note is minimal: 'Dictionary with extracted tables'. It does not specify the dictionary structure, behavior when no tables found, or error handling. For a tool with 3 parameters and no output schema, this is adequate but not comprehensive.

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 has 100% parameter description coverage. The description adds value by providing usage examples and stating the default timeout (30 seconds). This clarifies param semantics beyond the schema definitions.

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 extracts tables from a web page as structured data, with a specific verb and resource. It is distinct from siblings like web_fetch (fetches raw page) and web_extract_links (extracts links).

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 examples but does not explicitly state when to use this tool versus alternatives like web_fetch or web_extract_links. It implies usage when needing structured table data, but lacks exclusions or comparative 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?

Adds substantial detail beyond annotations: uses readability to remove clutter, converts to Markdown, and explains parameter defaults. No contradiction with annotations.

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

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

Well-structured: brief introduction, two examples, and organized Args/Returns sections. Every sentence provides useful 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 no output schema, description fully explains return values (title, content, url, metadata). Covers all necessary details for agent use.

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. However, description provides additional context for each parameter in the Args block and examples, adding value.

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 it fetches a web page and extracts main content as Markdown using readability. Distinguishes from siblings like web_search, web_extract_links, web_extract_tables.

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

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

Provides clear context via examples and description of content extraction. Does not explicitly say when not to use, but sibling tools cover 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?

Annotations indicate readOnlyHint=true and destructiveHint=false, and the description confirms it's a read-only search that returns snippets. It adds behavioral context by stating it does not fetch full page content, which aligns with annotations.

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

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

The description is concise with a brief overview, an example, and a structured args list. No unnecessary words; front-loaded with purpose.

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 explains return format (dictionary with title, url, snippet). All parameters are documented with defaults. Behavioral constraints are clear. Complete for a search tool.

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

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

Schema coverage is 100% with descriptions for each parameter. The tool description adds value by providing an example and clarifying the default for max_results and region. While not significantly beyond schema, the examples enhance usability.

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 searches the web using DuckDuckGo, distinguishes from sibling web_fetch by noting it does not fetch full page content, and provides a concrete example.

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 explicitly says when to use (web search) and when not (use web_fetch for full content). It also explains region parameter. However, it does not mention other sibling tools like web_check_url as alternatives for checking URLs.

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?

Annotations indicate not readOnly and not destructive. The description adds value by specifying that deletion markup is removed and insertion markup is converted, giving more detail than the name alone. However, it does not mention reversibility or error handling.

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, concise and to the point. No fluff or redundant 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?

The description covers the main action but lacks parameter details and usage guidance. For a tool with 2 parameters and no output schema, more context about expected input and output format would be beneficial.

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?

With 0% schema description coverage, the description should explain the parameters file_path and output_path. It does not, leaving the agent to guess that file_path is input and output_path is optional output.

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 accepts all tracked changes (insertions/deletions) in a Word document, explaining it removes deletion markup and converts insertion markup to normal content. It is specific and distinct from siblings like word_enable_track_changes or word_patch_with_track_changes.

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 on when to use this tool versus alternatives like word_patch_with_track_changes or word_cleanup_sow. It does not mention prerequisites (e.g., document must have tracked changes) 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?

Annotations already mark this as destructive (destructiveHint: true), and the description reinforces that by detailing irreversible removals. It adds beyond annotations by listing specific content types removed and stating 'All removals are tracked for auditability,' which is valuable behavioral context for an agent.

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

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

The description is well-structured: a one-sentence summary, a bullet list of removals, a usage context sentence, and a Python-like example with Args and Returns. It is concise yet comprehensive, 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?

Given the tool's moderate complexity and the absence of an output schema, the description covers inputs, behavior, and return value (cleanup statistics). It could be slightly more specific about what 'cleanup statistics' includes, but overall it provides sufficient context 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?

The input schema already provides clear descriptions for all three parameters (file_path, output_path, author), covering 100% of the schema. The description adds extra value by noting the default behavior for output_path ('defaults to overwriting input') and the author default, plus an example call with real paths.

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 starts with a specific verb ('Clean') and resource ('SOW document'), clearly distinguishing it from sibling tools like word_generate_sow or word_parse_sow_template. It lists exactly what is removed (e.g., highlighted text, bracket placeholders), making the tool's purpose unmistakable.

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

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

Explicitly states 'This is the final step after generate_sow to ensure the document is presentation-ready with no visible template artifacts.' This tells the agent exactly when to use it and implies not to use it before generation. The example with file paths further clarifies typical usage.

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?

Annotations indicate it is not read-only or destructive. Description adds value by detailing the workflow (parse, load template, fill, save) and the use of generate_sow internally, which provides behavioral context beyond the annotation hints.

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 well-structured with front-loaded purpose, then important note, workflow, example, and args. It is slightly verbose but every sentence adds value; 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?

Covers purpose, workflow, parameter distinctions, and return value. However, it omits explanation of the mode parameter (best_effort, safe, strict, dry_run), which is a gap for a tool with no output schema and medium 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 covers 4 out of 5 parameters with descriptions, so baseline is 3. Description adds context for markdown vs markdown_file (large inputs) but does not explain the mode parameter, which has enum but no description in 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?

Description clearly states verb (Create), resource (SOW document), and method (from markdown, filling template). It distinguishes from sibling tools like word_from_markdown and word_generate_sow by specifying the requirement for a template and the internal workflow.

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?

Description explains the workflow and requirement for a template, and gives an example. It does not explicitly state when not to use this tool or name alternatives, but the context implies it is for SOW creation with templates, which is distinct from siblings.

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 reinforces the destructiveHint annotation by explaining it removes a comment and strips markers. It also adds that the file is overwritten by default unless output_path is provided, providing full behavioral transparency without contradicting annotations.

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

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

The description is extremely concise: a single-line summary followed by a clear list of args and returns. Every sentence is necessary and well-structured, front-loading the key 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?

Given the tool's simplicity, rich annotations, and complete schema, the description provides all necessary context. It mentions the return value ('Status dictionary') and covers edge cases (default overwrite), making it fully complete.

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

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

With 100% schema coverage, the baseline is 3. The description adds value by specifying that comment_id comes from word_get_comments and clarifying output_path's default behavior, improving 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 clearly states the tool's purpose: 'Delete a comment from a Word document by comment ID.' It also explains internal operations (removes from comments.xml, strips markers), distinguishing it from sibling tools like word_get_comments or word_reply_comment.

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?

It specifies that the comment_id comes from word_get_comments output, giving context for when to use it. However, it does not explicitly state when not to use it or mention alternatives, but the sibling list helps agents differentiate.

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?

Annotations are neutral (readOnlyHint false, destructiveHint false), but the description only says 'Return' without confirming read-only behavior or disclosing any side effects, performance impacts, or auth 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?

The description is a single, well-structured sentence with no unnecessary 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?

Despite the tool's simplicity, the description lacks completeness by not explaining what the 'structured document map' contains or how it can be used, necessitating additional context for effective invocation.

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