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

No annotations provided, and description does not disclose essential behavioral traits like idempotency, error handling, or authentication requirements for a mutation tool.

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

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

Three concise sentences front-loaded with the core purpose, no fluff.

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 output schema existence, description covers high-level purpose and supported servers, but lacks details on conflict resolution, token usage, or return value semantics.

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 0%, and the description adds no parameter explanations or constraints, failing to compensate for the missing 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 the tool registers a git repository as a config source, distinguishes it from siblings like fetch_config and remove_config_source, and specifies supported git servers.

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?

Advises use to set up sources for fetch_config, providing context for when to use, but lacks explicit when-not-to-use or alternative tool guidance.

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

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

With no annotations, the description carries the transparency burden. It mentions per-repo authentication and supported platforms, but does not disclose side effects, idempotency, or what happens if a repo already exists. This is adequate but not thorough.

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

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

Two concise sentences with no filler. The first sentence states the purpose, the second adds supported platforms and authentication. Front-loaded and 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?

Given 7 parameters and no schema descriptions, the description is incomplete. It covers the core action and platform support but omits parameter roles, error states, and authentication details. Output schema existence doesn't fully compensate.

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 0%, so the description must explain parameters. It only alludes to authentication (token_env) and does not detail other fields like branch, author_name, author_email, or enabled. The agent must rely on parameter names 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 action: 'Register a plugin marketplace repository.' It specifies the purpose for publishing skills and lists supported platforms, which distinguishes it from related tools like remove_marketplace or list_marketplaces.

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 indicates use for adding a repository to publish skills, but it does not explicitly contrast with siblings or provide conditions for when not to use it. The context is clear but lacks exclusions.

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

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

With no annotations, the description carries full burden. It reveals that the tool transforms workflow examples into guides with specific components, but lacks details on side effects, dependencies, or required input format.

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?

Single sentence, front-loaded with key action. No wasted words, but could benefit from slight expansion to cover usage hints.

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, 0% schema coverage, and no annotations, the description is insufficient. It does not explain output schema, parameter roles, or error conditions.

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 0%, yet the description adds no meaning to the 5 parameters. It mentions 'workflow test examples' but does not clarify input, output, group_by, no_ai, or json_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 verb (Build) and resource (how-to guides from workflow test examples). It differentiates from sibling tools like extract_test_examples and create_workflow by specifying the transformation into educational guides.

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

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

No guidance on when to use this tool vs alternatives. No mention of prerequisites, exclusions, or context for when this tool is appropriate.

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

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

With no annotations, the description carries full behavioral transparency burden. It mentions file save location but omits critical details such as overwrite behavior, permissions, validation, error handling, or output description (despite output schema existing). Minimal disclosure.

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, no wasted words. Front-loaded with verb and resource, location provided. Efficient and well-structured.

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

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

Despite a simple tool with output schema, the description lacks essential context: success behavior, response structure, validation, error cases, and overwrite policy. Incomplete for a creation action.

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 0%, so description must compensate. It implies 'content' is YAML and hints at destination, but does not explain the 'name' parameter role, constraints, or formats. Insufficient enrichment 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 action (create), resource (user workflow), input format (YAML content), and output location (~/.config/...). It effectively distinguishes from sibling tools like delete_workflow, get_workflow, and update_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?

No explicit guidance on when to use this tool vs. alternatives (e.g., update_workflow). The context is clear but lacks explicit when-to-use or when-not-to-use statements, which is adequate but not proactive.

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

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

No annotations are provided, so the description must carry the full burden. It discloses that bundled workflows cannot be deleted, which is useful, but lacks details on irreversibility, permissions, 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 two concise sentences with no redundant information. Every part adds value: the action, the resource, and the constraint on bundled workflows.

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 delete operation with one parameter and an output schema, the description covers the key constraint (bundled workflows). It doesn't address error cases or return value, but the output schema likely fills that gap.

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

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

Schema coverage is 0%, so the description should compensate. It mentions 'by name' but does not clarify naming conventions, case sensitivity, or format. The single parameter lacks meaningful semantic detail beyond the schema.

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

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

The description clearly states the verb 'Delete' and the resource 'user workflow by name', and includes a constraint about bundled workflows, distinguishing it from siblings like create_workflow or get_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?

The description implies use for deleting user workflows but does not explicitly state when not to use it or provide alternatives. It warns about bundled workflows but lacks guidance on prerequisites or context-specific 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?

No annotations provided, so description should disclose behavior. It does not mention whether the tool is read-only, performance implications, or required permissions. For a detection tool, this is a notable gap.

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 one sentence long, listing patterns and languages. It is concise but lacks structure; parameter details could be included in bullet points or separate sentences.

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 5 parameters and no param descriptions, the description is incomplete. Output schema exists but is not referenced. The agent lacks critical information 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 coverage is 0% and description fails to explain any of the 5 parameters (file, directory, output, depth, json). The agent cannot infer how to use these parameters from the current 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 the tool detects design patterns in source code, lists specific patterns (Singleton, Factory, etc.) and supported languages (Python, JavaScript, etc.). This distinguishes it from all sibling tools, which cover config, workflow, scraping, 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?

No explicit guidance on when to use this tool vs alternatives. However, since sibling tools are unrelated, confusion is minimal. Missing prerequisites or typical use cases (e.g., 'use on codebases to identify architectural patterns').

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

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

With no annotations provided, the description carries full burden. It reveals modes and output length (500+ lines) but lacks critical behavioral details: whether the tool modifies the file in place, what happens if skill_dir doesn't exist or lacks a SKILL.md, or if the operation is destructive. This is insufficient for safe usage.

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

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

Two sentences with no superfluous info. The first sentence states the core purpose, and the second clarifies modes and output. Information is front-loaded and each word earns its place.

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

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

Given no annotations and 4 parameters, the description covers purpose and modes but omits prerequisites (e.g., skill_dir must exist, SKILL.md must be present), error scenarios, and side effects. An output schema exists but its content is unknown; description doesn't mention it. The description is adequate for a simple tool but leaves gaps for robust usage.

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

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

Schema description coverage is 0%, so the description must compensate. It provides context for three parameters: target (platform's model), mode (local vs API), and api_key (required in API mode). However, it fails to explain what 'target' values are acceptable or detail the mode options beyond 'local' and 'api'. Skill_dir is implied but not explicitly tied to the file.

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 'enhance', the resource 'SKILL.md', and the method 'using AI with target platform's model'. It distinguishes between local and API modes, and specifies the outcome: transforming basic templates into comprehensive 500+ line guides with examples. This sets it apart from sibling tools like install_skill or build_how_to_guides.

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 local vs API mode based on API key availability. However, it does not provide guidance on when to use this tool over alternatives like build_how_to_guides, nor does it specify prerequisites or when not to use it. The guidance is limited to mode selection.

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?

Discloses it's a non-downloading, fast preview, which suggests read-only behavior. However, lacks explicit statements about side effects, permissions, or output format beyond what the output schema might convey.

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, 12 words, no fluff. Concise but could add a brief parameter explanation without losing brevity.

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

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

With no annotations and 0% parameter coverage, the description is too sparse. Does not mention the output type or behavior of optional parameters, leaving gaps for safe usage.

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

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

Schema description coverage is 0%, yet the description only implicitly references config_path. Does not explain max_discovery or unlimited, leaving the agent without guidance on their 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 the tool estimates page count from a config, and explicitly notes it's a fast preview without downloading content, distinguishing it from scraping siblings.

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

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

Implies usage for quick previews, but does not explicitly state when to use vs. alternatives like scrape_* tools, nor provide when-not-to-use conditions.

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

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

No annotations are provided, so description must disclose behavioral traits. It only explains what Chroma is, not how the export behaves (e.g., overwrite behavior, required permissions, side effects).

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

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

The description is concise with two sentences and no fluff. The extra context about Chroma is useful.

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 2 parameters and an output schema, the description is incomplete. It lacks parameter explanations, output description, and any usage context. The presence of output schema is not leveraged.

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 0%, yet the description does not explain the parameters (skill_dir, output_dir). It adds no 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?

Clearly states 'Export skill to Chroma vector database format' with a specific verb and resource. However, it does not differentiate from sibling export tools (faiss, qdrant, weaviate) which share the same pattern.

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 usage context provided. Does not mention when to use this over other export tools, nor any prerequisites or conditions.

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

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

No annotations exist, so the description must fully disclose behavioral traits. It fails to mention whether the tool overwrites existing files, requires specific permissions, or has any destructive potential. The description only states the action without 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?

The description is brief (two sentences) and front-loaded with the core purpose. The second sentence provides background on FAISS which, while informative, is not directly actionable for tool invocation. Overall, it is concise but could omit the FAISS background without loss.

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 presence of an output schema (context confirms), the description does not explain the return format. With two parameters undocumented in text and no usage guidance relative to siblings, the description is incomplete for an agent to correctly select and invoke the 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 description coverage is 0%, requiring the description to explain parameters. The description does not mention 'skill_dir' or 'output_dir' at all, adding no meaning beyond the schema. This is a serious 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 exports a skill to FAISS format, but does not differentiate from sibling export tools like export_to_chroma, export_to_qdrant, etc. The verb 'export' and resource 'skill' are specific, but lack sibling distinction.

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 like export_to_chroma or export_to_weaviate. The description does not mention context, prerequisites, 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?

With no annotations, the description must disclose behavioral traits, but it only describes Qdrant's general features (filtering, performance) without specifying any tool behavior such as idempotency, overwrite policy, authorization needs, or side effects.

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

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

The description is concise with two sentences. The first sentence captures the purpose directly. The second sentence provides background about Qdrant but is not strictly necessary for tool invocation, making it slightly wasteful.

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 two parameters, no annotations, and an output schema available, the description should clarify input expectations and behavior. It fails to address prerequisites, return format, or edge cases, leaving significant gaps for an agent.

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 0% and the description does not explain what 'skill_dir' or 'output_dir' represent. The agent is given no semantic context beyond the parameter names and types, which is insufficient for correct usage.

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 ('Export skill to Qdrant vector database format') and the target resource. However, it does not differentiate from sibling export tools (e.g., export_to_chroma, export_to_faiss) which could confuse an agent selecting among 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?

No guidance is provided on when to use this tool versus its alternatives. There is no mention of prerequisites, contexts, or exclusions, leaving the agent to rely solely on the name for selection.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It fails to mention side effects like file overwriting, required permissions, or scope changes, leaving critical behavioral traits undocumented.

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 consists of two sentences, with the first clearly stating the action. The second adds some context (hybrid search, users) but is not strictly necessary. Overall, it is efficient though slightly promotional.

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 having an output schema, the description lacks details on parameter semantics and behavioral implications. For a tool that writes to a database, additional context on data handling or error conditions would be expected.

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

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

The schema has 0% description coverage for parameters (skill_dir, output_dir), and the description does not explain their meaning or usage. This leaves agents without guidance on what values to provide, making the tool hard to invoke correctly.

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 'Export skill to Weaviate vector database format,' providing a clear verb-resource pairing. It distinguishes from sibling exporters (e.g., export_to_chroma, export_to_faiss) by naming Weaviate specifically.

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

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

The description gives context on when to use this tool—'Ideal for production RAG applications' and 'Weaviate supports hybrid search'—helping agents choose among vector DB exporters. It does not explicitly state when not to use or mention alternatives, but the differentiation 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the core actions—analyzing, detecting patterns, generating documentation, and AI enhancement—which gives a baseline understanding. However, it fails to state potential side effects, such as whether the AI mode calls external APIs or if the tool modifies source files, leaving important gaps.

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

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

The description is concise at three sentences, front-loading the primary purpose. It efficiently conveys the core functionality and optional enhancement. However, the phrase 'Supports 9 formats' is vague and could be more specific, and the 'C3.4' reference is unclear.

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 8 parameters, no schema description coverage, and an output schema that is not detailed in the description, the text is insufficient for complete understanding. It does not explain parameters, return values, or usage scenarios. The agent is left guessing about input requirements and output structure.

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

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

Schema description coverage is 0%, and the description adds no information about any of the 8 parameters. It does not explain the directory requirement, the output path default, the ai_mode options, or the boolean flags. The agent must rely solely on the schema, which lacks descriptions and enums.

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 extracts configuration patterns from config files, detects specific pattern types (database, API, logging), generates documentation, and offers optional AI enhancement. The verb 'extract' and resource 'config patterns' are specific, and the listing of pattern types and formats provides clarity. It distinguishes from siblings like 'detect_patterns' by focusing on config files.

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 lacks guidance on when to use this tool versus alternatives like 'detect_patterns' or 'extract_test_examples'. It mentions optional AI enhancement but does not specify when to enable it. No context on whether it's a read-only operation or if it modifies the codebase, and no prerequisites are noted.

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

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

The description discloses that Python uses AST-based parsing while other languages use regex-based, which is a useful behavioral trait. However, it does not mention any side effects, performance implications, or limitations (e.g., accuracy differences, resource usage). Without annotations, more detail would be beneficial.

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: two sentences that front-load the main action and then expand on supported languages. No wasted words. The structure is 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?

Given the high number of parameters (7) and zero schema descriptions, the description fails to provide sufficient context for correct invocation. While the purpose is clear, the agent lacks details on how to set parameters, which are optional/required, and what the expected output covers (though output schema exists).

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 0%, yet the tool description provides no explanations for the 7 parameters. The agent must infer meaning from names like 'file', 'directory', 'language', etc., without hints about usage, defaults, or constraints. The description adds no value beyond the schema.

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

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

The description clearly states the tool's purpose: 'Extract usage examples from test files.' It elaborates on what is extracted (instantiation, method calls, etc.) and distinguishes from siblings by specifying it targets test files and supports 9 languages. This is specific and unambiguous.

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

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

The description does not provide guidance on when to use this tool instead of alternatives like 'extract_config_patterns' or scraping tools. No hints about prerequisites, exclusions, or preferred contexts. The agent is left to infer from the purpose alone.

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

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

No annotations are provided, so the description must fully disclose behavior. It mentions fetching and listing but does not clarify side effects (e.g., file overwrites, authentication requirements, error handling). The token parameter hints at auth, but description omits this.

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

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

The description is two sentences, front-loaded with the core purpose and modes. No redundant information, 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?

With 9 parameters, no schema descriptions, and no annotations, the description is insufficient. It lacks parameter guidance and behavioral details, though output schema exists. The tool's complexity demands more comprehensive documentation.

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 0%, so the description must compensate. It mentions config_name, git_url, source, and list_available implicitly, but does not explain destination, category, branch, token, or refresh. High-level modes are described but parameter mapping is incomplete.

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 fetches configs from API, git URL, or registered source, and supports three modes. It distinguishes from sibling tools like list_configs and validate_config by specifying the action of fetching or downloading.

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 outlines three modes and when each might be used (named source, git URL, API). However, it does not explicitly state when not to use this tool or mention alternative sibling tools like list_configs for merely listing.

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 mentions 'interactively creates' but does not explain what that means in a tool context. There is no information on side effects (e.g., whether the config is saved locally, stored in a database, or just returned). With no annotations, the description fails to disclose critical behavioral traits like idempotency or data persistence.

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 only one sentence, which is concise but at the expense of clarity. It does not earn its place by providing necessary details; instead it leaves out critical information, making it under-specified rather than efficiently concise.

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 7 parameters, no schema descriptions, no annotations, and many sibling tools, the description is severely incomplete. It fails to explain the output (though an output schema exists), the effect of the tool, or how parameters control behavior. Almost no context is provided.

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 0%, so the description must compensate. However, it only mentions generating a config without explaining any of the 7 parameters (name, url, description, force, max_pages, unlimited, rate_limit). The tool says 'interactively' but the parameters are purely declarative.

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

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

The description clearly states the tool generates a config file for documentation scraping and creates a JSON config for any documentation website. It distinguishes itself from siblings like fetch_config (retrieves existing) and validate_config (validates). However, the word 'interactively' may be misleading given the tool takes parameters directly.

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 like fetch_config or validate_config. The description does not mention prerequisites, limitations, or scenarios where this tool is appropriate.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states it generates/creates a router but does not specify side effects, permissions needed, rate limits, or whether it writes to a store. This is insufficient for safe invocation.

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

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

The description is two sentences, front-loaded with the main action, and contains no redundant information. It is appropriately concise, though the brevity sacrifices parameter and context 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?

The tool has an output schema (not shown) and two parameters. The description partly explains the high-level purpose but omits details on output format, prerequisites, and relationship to sibling tools. It is minimally adequate for an agent familiar with the domain but incomplete for new users.

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 0% and the description does not explain the parameters 'config_pattern' and 'router_name'. Their purpose, format, or allowed values are completely absent, forcing the agent to guess or infer incorrectly.

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

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

The description clearly states the tool generates a router/hub skill for split documentation and creates intelligent routing to sub-skills. This distinguishes it from sibling tools like split_config or extract_config_patterns. However, the term 'intelligent routing' could be more explicit about the mechanism.

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. It does not mention prerequisites, scenarios, or when not to use it. Sibling tools like build_how_to_guides or detect_patterns relate to documentation but no comparative context is given.

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

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

With no annotations provided, the description carries the full burden. It discloses that the tool retrieves YAML content and searches two locations in order, but does not cover error handling (e.g., workflow not found), permissions, or side effects. Behavior is adequately described for a read operation.

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

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

The description is two sentences, directly front-loading the purpose then adding search behavior detail. Every word is useful, 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 has one parameter, an output schema (reducing the need to describe return values), and low complexity, the description covers key aspects: what it returns and where it searches. It lacks error handling info, but overall is mostly complete.

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

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

Schema description coverage is 0%, so the description must compensate. It only labels the parameter as a 'named' workflow, without specifying format, constraints, or examples. This adds minimal meaning beyond the schema's property name.

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 retrieves the full YAML content of a workflow, with a specific verb 'get' and resource 'workflow'. It distinguishes from siblings like 'list_workflows' and 'create_workflow' by specifying the action and output format.

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 mentions a search order (user dir then defaults), which provides context on where the tool looks. However, it does not explicitly state when to use this tool over alternatives, such as 'list_workflows' for listing all workflows or 'update_workflow' 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?

With no annotations provided, the description carries the full burden. It discloses that the tool performs multiple steps (fetch, scrape, enhance, package, upload), enhancement is mandatory and improves quality from 3/10 to 9/10, the process takes 20-45 minutes, and it supports various LLM platforms with auto-upload detection. However, it does not detail side effects like file creation or overwriting, permissions needed, or error scenarios.

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 four sentences, front-loading the workflow and key facts. Every sentence adds value: workflow steps, mandatory enhancement, time estimate, platform support, auto-upload condition. It could be more structured (e.g., bullet points), but it is appropriately sized and avoids fluff.

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

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

Given no annotations, 0% schema coverage, and 7 unrequired parameters, the description is insufficient. It explains the workflow and some behavioral aspects but fails to document what each parameter controls, return values (though an output schema exists), prerequisites, or error handling. The agent would struggle to invoke this tool correctly without additional knowledge.

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

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

Schema coverage is 0%, so the description must explain parameters. It only explains the 'target' parameter (auto, claude, gemini, openai, markdown) and mentions config generally. The other parameters (config_path, destination, auto_upload, unlimited, dry_run) are not described at all. This leaves significant gaps for the agent to understand how to use the tool correctly.

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 is a complete one-command workflow: fetch config → scrape docs → AI enhance → package → upload. It uses specific verbs and resources, and differentiates from sibling tools like enhance_skill, package_skill, upload_skill by presenting itself as a composite of those steps.

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: it is a full installation workflow, enhancement is mandatory, it takes 20-45 minutes, supports multiple LLM platforms, and auto-uploads if an API key is set. While it implies when to use this tool versus its siblings (e.g., for a complete install rather than just enhance or upload), it does not explicitly state when not to use it or mention alternatives.

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

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

No annotations exist, so the description must carry the burden. It only states listing configs, with no mention of side effects, permissions, or whether the list is read-only. Lacks additional 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?

The description is a single concise sentence, front-loading the action. However, it could be slightly more structured or informative without losing 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 zero parameters and an output schema, the description is minimal but adequate. It does not specify scope (e.g., global vs user-specific) or how the list is ordered, which might be helpful for complex scenarios.

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 baseline is 4. The description does not need to add parameter meaning, and the existence of an output schema reduces the burden. No extra info is needed.

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 'List' and the resource 'all available preset configurations,' which distinguishes it from sibling tools like 'fetch_config' (which fetches a single config) and 'list_config_sources' (which lists sources).

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 vs alternatives, such as 'fetch_config' or 'list_config_sources'. The description implies listing all configs but does not exclude specific scenarios.

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

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

No annotations are provided, so the description carries full burden. It indicates a read-only listing operation but does not disclose any potential side effects, permissions, limits, or pagination. Adequate but lacks depth.

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

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

Two sentences with no unnecessary words. The main purpose is front-loaded, and every sentence adds value.

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

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

For a simple list tool with one parameter and an output schema, the description covers the primary use case. However, it lacks explanation of the parameter and does not describe the return format, though output schema exists.

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 0% for the only parameter 'enabled_only,' and the description does not explain its meaning or effect. The agent must guess what 'enabled' or 'disabled' sources entail.

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

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

The description clearly states it lists all registered config sources, specifies they are git repositories registered via add_config_source, and mentions usage for fetch_config. It distinguishes from sibling tools like add_config_source, remove_config_source, and fetch_config.

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 to see available sources for fetch_config,' providing clear context. However, it does not mention when not to use it or contrast with other similar listing tools like list_configs.

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

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

No annotations are provided, so the description must fully disclose behavior. It only states the basic action without mentioning read-only nature, pagination, rate limits, or authentication 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, efficient sentence. However, it is so brief that it sacrifices necessary detail.

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 (one optional parameter, output schema exists), the description is minimally adequate but lacks context such as what constitutes a 'registered' marketplace or the format of the return data.

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

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

The schema description coverage is 0% for the single parameter 'enabled_only'. The description adds no extra meaning or context beyond what the schema provides (title and default).

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

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

The description uses a specific verb ('List') and resource ('registered plugin marketplace repositories'), clearly distinguishing it from sibling tools like add_marketplace and remove_marketplace.

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 listing marketplaces but provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites.

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

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

No annotations are provided, so the description carries the burden. It adequately describes the return values but does not disclose safety traits (e.g., read-only nature) or any limitations. Since it's a list operation, the behavior is straightforward, but more transparency 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?

Two sentences, front-loaded with the action, and no wasted words. Efficient and to the point.

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 zero parameters, no annotations, and an existing output schema, the description fully covers the tool's purpose and return structure. It provides enough context for an agent to use it correctly.

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

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

No parameters in the schema, so the description is not required to add param info. However, it adds value by describing the output format (name, description, source). Baseline for 0 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?

Description clearly states the tool lists all available enhancement workflows and specifies the return fields (name, description, source). It distinguishes between bundled and user-created workflows, and differentiates from siblings like create_workflow, get_workflow, 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 implies usage when one needs to see all workflows, which is clear. However, it does not explicitly state when not to use it or mention alternatives among siblings, which is not critical given the zero parameters and simple action.

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

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

With no annotations, the description bears full burden for behavioral traits. It discloses auto-upload behavior based on API key presence and format differences by platform, but omits important details like side effects (overwrite, error handling, directory structure 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?

Three sentences, each essential. First states the primary action and formats, second lists platforms, third mentions auto-upload. No redundant information; highly 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?

Despite having an output schema, the description lacks explanation of prerequisites (e.g., skill directory structure), error conditions, or output details. With 0% schema coverage and complex behavior (packaging + upload), more contextual information 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?

Schema description coverage is 0%, so the description compensates partially. It explains 'target' via platform list and 'auto_upload' via auto-upload behavior, but 'skill_dir' receives no elaboration. The meaning is conveyed but not fully mapped to each parameter.

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 packages a skill directory into platform-specific formats (ZIP for most, tar.gz for Gemini) and lists supported platforms. It distinguishes from siblings like 'upload_skill' by combining packaging with optional auto-upload, making 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?

No explicit guidance on when to use this tool vs. alternatives like 'upload_skill'. The description implies usage for packaging with optional upload, but does not state when not to use it or provide context for choosing among the 39 sibling tools.

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

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

With no annotations provided, the description must bear the full burden of behavioral disclosure. It indicates the tool creates a plugin, implying a write/mutation operation, but does not disclose potential side effects (e.g., overwriting existing entries), authentication requirements, or impact on the marketplace repository.

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 at two sentences with no unnecessary words. It front-loads the core action. However, it could be slightly more structured to highlight key constraints or parameters.

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

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

Given the tool has 7 parameters, no parameter descriptions, and no annotations, the description is incomplete. It does not explain prerequisites (e.g., a packaged skill from 'package_skill'), the nature of marketplace repositories, or expected return values (though output schema exists separately).

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 zero information about any of the 7 parameters (e.g., skill_dir, marketplace, category). With 0% schema description coverage, the agent has no guidance on parameter meaning, allowed values, or relationships, making effective invocation difficult.

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 'publish a packaged skill to a plugin marketplace repository' and specifies the result 'Creates a Claude Code plugin'. This provides a clear verb+resource combination. However, it does not explicitly distinguish this from sibling tools like 'package_skill' or 'upload_skill', which could be confused without additional context.

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 offers no guidance on when to use this tool versus alternatives, nor does it mention prerequisites or when not to use it. It simply states the basic action without contextual usage instructions.

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

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

With no annotations, the description must fully disclose behavior. It outlines the steps (validate, place in category directory, commit, push) but does not mention side effects like branch creation, overwriting, required permissions, or failure modes. Adequate but not comprehensive.

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

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

The description is a single, direct sentence that front-loads the primary action. It is very concise, though it could benefit from slight elaboration on parameters without losing efficiency.

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 5 parameters, 0% schema coverage, no annotations, and a presumably important output schema, the description is too brief. It lacks return value information, error conditions, and details about the process, leaving the agent with significant unknowns.

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 0%, so the description must compensate. It hints at 'category directory' aligning with the category parameter and 'commits' implying branch usage, but it fails to explicitly describe any of the five parameters (config_path, source_name, category, create_branch, force) or their semantics.

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 ('Push a config'), target ('registered config source repository'), and steps ('Validates, places in category directory, commits, and pushes'). It distinguishes from sibling tools like 'validate_config' and 'sync_config' by including the commit and push 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?

No guidance is provided on when to use this tool versus alternatives such as fetch_config, validate_config, or sync_config. It lacks any conditional or exclusionary context to help an agent decide between 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?

With no annotations provided, the description carries the full burden. It discloses that cached git repository data is not deleted, which is helpful. However, it does not mention if the operation is reversible, requires specific permissions, or what happens if the source does not 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?

Two sentences, front-loaded with the key action, and no wasted words. Every sentence serves a 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 simple tool with one parameter, the description covers the core action and an important exception. The presence of an output schema reduces the need to describe return values. Minor gaps remain (e.g., side effects, error states) but overall 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 description coverage is 0%, so the description should compensate. However, it does not describe the 'name' parameter beyond what is obvious from the tool name and schema. The meaning is inferred but not explicitly added.

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 (remove/delete) and the resource (config source), distinguishing it from tools like add_config_source or list_config_sources. However, it does not explicitly differentiate from other removal tools like remove_marketplace, but the naming and context are sufficient.

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, when not to use it, or any prerequisites. It simply states what it does, leaving the agent to infer appropriate 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?

With no annotations provided, the description adds useful behavioral context: it only deletes from registry, not cached data. This informs the agent of the tool's scope and side effects.

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

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

The description is a single sentence with no wasted words. It effectively communicates the tool's purpose and a key behavioral note.

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 is adequate for a simple tool with an output schema, but it lacks parameter detail. Given the low schema coverage, more context about the 'name' parameter would improve completeness.

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

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

The input schema has 0% description coverage for the parameter 'name', and the description does not clarify its meaning beyond the schema. Since coverage is low, the description should compensate but fails to do so.

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 ('Remove') and resource ('registered plugin marketplace'), distinguishing it from sibling tools like add_marketplace and list_marketplaces.

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 or not use this tool. The context is implied from the tool's name, but alternatives or prerequisites are not mentioned.

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

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

With no annotations, the description carries the full behavioral disclosure burden. It reveals that the tool walks directories and extracts signatures/docstrings, and optionally generates API docs and dependency graphs. However, it does not disclose potential side effects (e.g., writing files to the output directory), permissions needed, or whether the operation is read-only.

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

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

The description is two sentences and efficiently states the purpose and key behaviors. There is no fluff, but it could be more structured (e.g., listing parameters). Still, it earns a high score for 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 7 parameters with zero schema descriptions and no annotations, the description is incomplete. It omits explanations for four parameters and does not cover return values (though an output schema exists but is not shown). For a complex tool that walks directories and generates outputs, the description provides insufficient detail for full 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?

Schema description coverage is 0%, so the description must compensate. It only explains 'directory' and the two boolean options (build_api_reference, build_dependency_graph). The other parameters (output, depth, languages, file_patterns) are not described, leaving the agent to guess their meaning beyond name/type/default.

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: analyzing a local codebase and extracting code knowledge. It enumerates specific actions (walks directory, analyzes files, extracts signatures/docstrings) and optional outputs (API reference, dependency graphs), distinguishing it from sibling tools like scrape_docs or scrape_github which target external sources.

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

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

The description implies the tool is for local codebase analysis, but does not explicitly state when to use it versus alternatives, nor does it provide when-not-to-use guidance. Sibling tool names (e.g., scrape_github, scrape_docs) hint at context, but no direct comparison is offered.

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

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

With no annotations provided, the description must disclose behavioral traits. It mentions creating files and fallback behavior, but does not state if it overwrites files, requires network access, or handles errors. This leaves uncertainty about side effects and preconditions.

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 three sentences, front-loading the primary action. It avoids redundancy and is well-paced, though a slightly more structured breakdown of parameters would improve clarity without increasing length significantly.

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, 0% schema description, and no annotations, the description is incomplete. It does not cover parameter semantics or crucial behavioral details needed for correct invocation. The tool has high complexity that is not matched by the 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 description coverage is 0%, so the description must explain parameters. It only implicitly mentions config_path through the config context, but fails to explain unlimited, enhance_local, skip_scrape, dry_run, and merge_mode. This is insufficient for an AI agent to use the tool correctly.

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 scrapes documentation to build an LLM skill, specifying output files (SKILL.md and reference files). It distinguishes from siblings by mentioning single-source and multi-source configs, which is not typical of other scrape tools like scrape_codebase or scrape_pdf.

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 mentions automatic detection of llms.txt for faster processing and fallback to HTML scraping, giving some context on when the tool performs best. However, it lacks explicit guidance on when to use this tool versus alternatives like scrape_generic or scrape_codebase.

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

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

No annotations are provided, so the description carries full burden but only mentions delegation without detailing side effects, authentication needs, or limitations. Very little behavioral insight.

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 are concise and front-loaded with the purpose, but the second sentence only adds minimal 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?

With zero schema coverage, no annotations, and an output schema present but unmentioned, the description fails to provide sufficient context for proper usage.

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

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

Schema description coverage is 0%, and the description does not explain the parameters (source_type, name, path, url) beyond listing them. No added 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?

The description clearly states it scrapes from specific source types (jupyter, html, etc.) and distinguishes itself as a generic entry point from siblings like scrape_codebase or scrape_docs.

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 implies usage for new source types not covered by specific scrapers via 'delegates to appropriate CLI scraper module', but lacks explicit when-to-use or when-not-to-use guidance.

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

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

With no annotations, the description must disclose behavioral traits. It mentions extraction and skill building, implying read and write operations, but fails to clarify side effects, authorization needs, rate limits, or what happens to existing skills. The 'token' and 'scrape_only' parameters are not explained, creating significant gaps.

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

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

The description is concise at two sentences with no redundancy. However, the information could be better structured (e.g., bullet points) to improve scanability, and the phrase 'build Claude skill' is somewhat vague.

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 10 parameters, no schema descriptions, and no annotations, yet the description is minimal. It omits output details (though an output schema exists), parameter explanations, and scenario-specific guidance. Given the complexity and many siblings, the description is incomplete.

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

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

Schema description coverage is 0%, so the description must compensate. It lists extracted content but provides no explanation for the 10 parameters (e.g., repo, config_path, no_issues). The agent cannot determine parameter purpose from the description 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 action 'Scrape GitHub repository' and the outcome 'build Claude skill', listing specific extracted content (README, Issues, Changelog, Releases, code structure). This distinguishes it from siblings like scrape_docs or scrape_video, providing a specific verb and resource.

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 (e.g., scrape_codebase, scrape_generic). No prerequisites, exclusions, or context for selection are given, leaving the agent to infer usage from the tool name and description alone.

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

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

With no annotations, the description partially discloses behavior (extracts text, code, images) and mentions building a Claude skill, but does not explain side effects, permission needs, or return format. It provides some transparency but is insufficient.

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 (two sentences) and front-loaded with the core action. No unnecessary words or repetition. Highly 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?

Given the tool has 5 parameters, no annotations, and an output schema, the description is incomplete. It fails to explain how to use parameters, what the output contains, or how the skill-building process works. Much context is missing.

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?

All 5 parameters are optional and only defined by type (string/null). The description provides no explanation of config_path, pdf_path, name, description, or from_json. With 0% schema coverage, the description fails to add 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?

The description clearly states the tool scrapes PDF documentation and builds a Claude skill, specifying extraction of text, code, and images. It uses specific verb+resource and distinguishes from sibling scraping tools by focusing on PDFs.

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

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

No guidance on when to use this tool versus alternatives like scrape_docs, scrape_generic, or scrape_video. The description lacks context on prerequisites, limitations, or 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?

No annotations provided, so description must disclose behavioral traits. It only states what it does (extract, build skill) without mentioning side effects, auth requirements, rate limits, or parameter interaction. For a 16-parameter tool with no schema descriptions, this is insufficient.

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?

Single sentence that front-loads the core action. Lacks bullet points or structured sections, but avoids verbosity. Could better organize the 'build Claude skill' addition.

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 16 parameters, 0 required, 0% schema descriptions, and no annotations, the description is critically incomplete. It does not cover return values (output schema exists but not referenced), parameter combinations, or tool behavior beyond basic extraction.

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 0%, and description adds minimal meaning beyond parameter names. It mentions video sources (YouTube, Vimeo, local files) which maps to url/video_file, but does not explain other 14 parameters (e.g., visual, languages, whisper_model).

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 specifies verb 'Extract' and resource 'transcripts and metadata from videos' with concrete sources (YouTube, Vimeo, local files). It uniquely adds 'build Claude skill', differentiating it from sibling scrape tools that target other sources.

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

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

No guidance on when to use this tool vs alternatives like scrape_docs or scrape_generic. No prerequisites or exclusions mentioned, despite many sibling tools.

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

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

With no annotations, the description must disclose behavioral traits. It mentions auto-detection of config type and recommendation of best strategy, but does not explain side effects like whether the original config is modified or destroyed, authorization needs, or the nature of the splitting operation (e.g., whether it creates new skills or modifies the config).

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

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

The description is three sentences, totaling about 30 words, with no wasted words. It front-loads the main action, then adds supporting details (supported use cases, auto-detection) in a logical order.

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

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

The tool has 4 parameters, no annotations, and 0% per-parameter description, so more context is needed. The description omits behavior details, parameter choices, and what the output schema contains, leaving gaps for an agent to operate 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 0%, so the description must compensate for parameter meanings. It only implicitly references config_path, but does not describe strategy options, target_pages semantics, or dry_run behavior. The phrase 'recommends best strategy' hints at strategy but lacks detail on possible values.

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 primary action: 'Split large configs into multiple focused skills.' It specifies the resource (large configs) and the outcome (focused skills), and distinguishes from sibling tools like fetch_config or validate_config by focusing on splitting.

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 large configs needing splitting, and that auto-detection recommends strategy. However, it does not explicitly state when not to use this tool (e.g., if config is small) or mention alternative tools like extract_config_patterns or enhance_skill for similar 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?

With no annotations, the description must disclose behavioral traits. It mentions validation and GitHub issue creation, but omits critical details: the need for a github_token (evident from schema but not stressed), that the action creates a public issue, whether the config is stored locally, or error handling. The mutation nature is clear but insufficient context for safe usage.

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

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

The description is a single sentence with no waste, conveying the core action and two steps (validate, create issue). It is appropriately concise for a simple tool, though additional information could be accommodated without 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 4 optional parameters with no schema descriptions, no annotations, and a non-trivial action (creating a GitHub issue), the description is insufficient. It does not explain config formats, parameter selection, or the review process. The existence of an output schema is not leveraged to describe return values.

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 0%, meaning no descriptions in the schema. The description fails to explain any of the 4 parameters (config_path, config_json, testing_notes, github_token), their purposes, formats, or when to use one over the other. This is a significant gap for a tool with multiple optional parameters.

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

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

The description clearly states the tool submits a config file and validates it, creating a GitHub issue. The verb 'submit' and resource 'custom config file' are specific. However, it does not differentiate from siblings like push_config or validate_config, missing an opportunity to clarify its unique role.

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 sharing configs with the community and mentions validation and review. But it provides no explicit guidance on when to use this tool versus alternatives (e.g., push_config, fetch_config, validate_config), nor does it state exclusions or prerequisites like requiring a GitHub token.

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

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

No annotations provided, so description carries full burden. 'Sync' is ambiguous (read-only diff or actual update?). The 'apply' parameter hints at a dry-run vs. write mode, but this is not explained.

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

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

The description is a single sentence, which is too concise for a tool with 6 parameters and no parameter descriptions. It omits critical 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 tool's complexity (6 params, no annotations) and the presence of an output schema, the description fails to explain return values, default behaviors, or the effect of parameters like 'apply'.

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 0% description coverage and the description does not explain any of the 6 parameters (config_path, apply, depth, max_pages, rate_limit, source_index). The description only mentions 'start_urls', which is not a parameter.

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 ('sync'), the resource ('config's start_urls'), and the comparison target ('what's live on the docs site'). This distinguishes it from sibling tools like scrape_docs or fetch_config.

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 (e.g., push_config, fetch_config). No mention of prerequisites or exclusions.

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

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

No annotations are provided, so the description carries the full burden. It discloses that the update is an overwrite and that bundled workflows are excluded, but does not mention any side effects, required permissions, or what happens if the workflow doesn't 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 extremely concise at two sentences, with no wasted words, and places the key action and constraint upfront.

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 role in updating workflows and the presence of an output schema, the description covers the basic constraint but lacks parameter explanations and usage context, making it incomplete for an agent to fully understand how to invoke it correctly.

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

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

The schema has 2 parameters with 0% description coverage, and the description provides no information about what 'name' or 'content' represent, leaving the agent to infer meaning from the tool name 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 action (update/overwrite) and resource (existing user workflow), and explicitly excludes bundled workflows, distinguishing it from siblings like create_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?

The description provides one exclusion (cannot update bundled workflows), but does not offer guidance on when to use this tool versus alternatives like create_workflow or delete_workflow.

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

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

No annotations are provided, so the description carries full burden. It discloses API key requirement and non-support for markdown, but lacks details on success response, error conditions, idempotency, or rate limits. For a mutation tool, this is insufficient.

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 three sentences, front-loading the main action and then adding details. It is concise with no redundant information, though slightly more structure could improve 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 presence of an output schema and simple parameters, the description covers essential aspects like required API key and supported platforms. It could mention output expectations or constraints like size limits, but is mostly 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 description coverage is 0%, so description must compensate. It partially explains parameters: skill_zip as the package, api_key as required, target as one of the supported platforms. However, it does not explain default values or format, leaving ambiguity.

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 'upload' and resource 'skill package', and specifies supported platforms (claude, gemini, openai), differentiating it from sibling tools like 'install_skill' or 'package_skill'.

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 mentions requirement for platform-specific API key and lists supported platforms, implying when to use, but does not explicitly state when not to use or provide alternatives like 'install_skill' or 'package_skill'.

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

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

No annotations are provided, so the description must carry the full burden. It does not disclose what happens during validation (e.g., what constitutes an error, whether the tool modifies anything, what the return value contains). For a validation tool, the lack of behavioral detail is a significant gap.

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

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

The description is a single sentence that is front-loaded and contains no wasted words. However, it could be slightly more informative without sacrificing 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 has an output schema (not shown), the description need not explain return values, but it still lacks context about what 'validate' entails. With 37 sibling tools in config-related domains, the description does not provide enough to distinguish or guide correct usage.

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

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

With 0% schema description coverage, the description should add meaning to the only parameter, 'config_path'. It does not explain the expected format (file path, URL, etc.), restrictions, or any validation context. The parameter name alone is insufficient.

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 'validate' and the resource 'config file for errors,' making the purpose clear. However, it does not differentiate from sibling tools that also deal with config files, such as 'validate_config' might be similar to 'fetch_config' or 'generate_config' but the description is specific enough to imply validation vs. generation.

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?

There is no guidance on when to use this tool versus alternatives like 'fetch_config' or 'split_config'. No mention of prerequisites, exclusions, or typical use cases. The description is purely declarative.

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