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 the search mechanism, output type (grounded answer plus citations), independence from other tools, and API key requirement. However, it lacks details on rate limits, error handling, or what happens if the API key is invalid.

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, each serving a distinct purpose: function, differentiation/use case, and setup requirement. No fluff, front-loaded with the core 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?

Despite missing output schema details, the description covers purpose, usage context, and authentication. The tool is simple with one parameter, and the description provides enough for an agent to decide when and how to use it. Output schema exists, so return values need not be described.

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

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

Schema coverage is 100% and the description adds no parameter-specific information beyond what the schema already provides. The baseline of 3 is appropriate since the schema fully documents the single 'query' 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 'Performs a web search via Gemini + Google Search grounding', identifying the specific verb, resource, and mechanism. It also distinguishes itself from siblings by noting 'Independent of Tavily/Firecrawl', making its purpose unambiguous.

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

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

The description explicitly says 'use as a second search path for cross-validation', providing a clear when-to-use context. It also names the alternatives (Tavily/Firecrawl) and mentions the prerequisite GEMINI_API_KEY, giving explicit 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It discloses that API keys are automatically masked, connection test has a 10-second timeout, and it sends a request to the /models endpoint. These are valuable behavioral traits beyond the mere statement of function, making the tool's operation predictable and safe.

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

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

The description is well-structured with clear sections for Key Features and Edge Cases/Best Practices. Every sentence provides useful information, and the bullet points make it scannable. It is appropriately sized, not overly verbose, and front-loaded with the core 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?

The tool has no output schema, so the description should explain return values. It mentions returning configuration, listing models, and testing connectivity, but does not specify the exact structure of the response. Given the simplicity of the tool and the richness of behavioral details provided, this is quite complete, though a brief mention of the response format would make it fully comprehensive.

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

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

The tool has zero parameters, so the input schema provides complete coverage. The description adds no parameter-specific information, but with no parameters, there is nothing to explain. The baseline for zero parameters is 4, which is appropriate here.

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

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

The description clearly states the tool's function: 'Returns current multsearch MCP server configuration and tests API connectivity.' The verb 'returns' and 'tests' are specific, and the resource is well-defined. It also lists key features (configuration check, connection test, model discovery) which further clarifies the scope and distinguishes it from sibling tools like web_search or get_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 provides explicit usage guidance: 'Use this tool first when debugging connection or configuration issues.' This gives a clear context for when to employ the tool, though it does not explicitly mention alternatives or exclusions. This is a clear context with no exclusions, qualifying for a 4.

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 conveys this is a read-only retrieval of cached sources, which is inherently safe, and hints that data persists ('cached'). It does not mention what happens for invalid/expired session_ids, auth requirements, or pagination, but for a simple retrieval tool the basic safety profile is adequately conveyed.

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

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

The description is highly repetitive — three sentences effectively say the same thing: use the web_search session_id to get the source list. It also contains a typo ('invoke the this tool'). A single crisp sentence ('Retrieve all cached sources for a prior web_search call using its session_id.') would carry the full meaning. The redundant first sentence should be cut.

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?

An output schema exists, so the return format is covered externally. For a low-complexity tool with a single required parameter, the description adequately covers when to use it (after web_search) and what it returns (the full source list). The main gaps — error behavior for invalid sessions and any filtering/ordering — are minor given the tool's simplicity.

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

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

Schema coverage is 100% — the schema already documents session_id as 'Session ID from previous web_search call.' The description reinforces that the ID must come from web_search, adding marginal provenance context, but it does not add meaningful syntax or format details beyond what the schema provides. Baseline 3 is appropriate.

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

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

The core purpose is clear: 'Retrieve all cached sources for a previous web_search call' states a specific verb and resource, and ties the tool to the web_search sibling via session_id. However, the opening sentence uses odd emotional framing ('When you feel confused or curious...') which muddies the definition rather than clarifying it. The purpose is distinguishable from siblings like web_fetch and web_map because it targets cached search 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 gives useful context: the tool is invoked with a session_id returned by a prior web_search call, so it is clearly a follow-up to web_search. However, it never states when NOT to use it or names alternatives (e.g., web_fetch for fetching actual page content). The 'confused or curious' trigger is too vague to be actionable 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 provided, the description carries full responsibility for behavioral disclosure. It transparently reveals persistence to ~/.config/multsearch/config.json, immediate effect, and the risk of invalid model IDs causing API errors. It also notes that changes persist across sessions until explicitly changed, providing a complete behavioral picture.

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

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

The description is well-structured with clear sections for key features and edge cases. Every section provides meaningful information without fluff. The length is appropriate for the tool's complexity and the rich context it provides.

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 parameter, no output schema, no annotations), the description fully covers purpose, usage, persistence, immediate effect, and edge cases. It equips the agent with all necessary context to select and invoke the tool correctly.

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

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

The schema already covers 100% of the parameter semantics with a clear description and example. The tool description adds value by warning about invalid model IDs and suggesting verification via get_config_info, which enriches the parameter's context 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 action: 'Switches the default LLM model used for search and fetch operations, persisting the setting.' This specific verb+resource combination distinguishes it from sibling tools like web_search and get_config_info, which serve different functions.

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

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

The description explicitly advises using get_config_info to verify available models before switching, directly addressing when to use this tool versus an alternative. The 'Edge Cases & Best Practices' section further clarifies usage context and potential pitfalls.

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

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

With no annotations, the description carries the full burden. It discloses key behaviors: full content extraction, markdown conversion, 100% content fidelity without summarization, and limitations (dynamic content, large page timeouts). This is useful transparency for a fetch tool, though it does not explicitly state read-only nature or error handling on invalid URLs.

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

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

The description is well-organized with headers and bullet points, front-loading the main purpose. It is concise, though there is minor redundancy between 'Full Content Extraction' and 'Content Fidelity' (both imply completeness). Overall, it is compact and scannable.

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

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

Given no output schema and no annotations, the description explains the return type (structured Markdown) and mentions edge cases (dynamic content, timeouts). However, it lacks explicit differentiation from sibling tools and does not address error handling (e.g., invalid URLs) or whether any side effects occur. It is adequate but not exhaustive.

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

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

The schema already provides a complete description of the 'url' parameter (valid HTTP/HTTPS web address, must be complete and accessible) with 100% coverage. The tool description repeats this accessibility guidance but adds no new parameter semantics, so the baseline of 3 applies.

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

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

The description clearly states the action ('Fetches and extracts complete content from a URL') and the output (structured Markdown). It is distinct from web_search (which searches) and web_map (which likely maps links) by focusing on a single URL. The purpose is unambiguous and immediately understandable.

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 its use (when you have a specific URL and want its content) but does not explicitly state when to use this tool over alternatives like web_search. It provides edge cases (accessibility, dynamic content) but no exclusions or routing to siblings, leaving the choice largely to inference.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the graph traversal approach, depth/breadth controls, instruction filtering, and edge cases like timeout limits ('Large sites may hit timeout limits; adjust timeout and limit parameters accordingly'). This reveals non-destructive behavior implicitly (mapping a site does not modify it) and provides practical limits. It could be more explicit about being read-only, but the overall behavior is transparent enough.

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

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

The description is well-structured with clear headings ('Key Features', 'Edge Cases & Best Practices') and bullet points. It is front-loaded with the primary purpose, followed by relevant details. Every sentence contributes to understanding the tool or its usage, with no filler. It is appropriately sized for a tool with 6 parameters and multiple controls.

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 parameters including traversal controls) and the presence of an output schema, the description covers the necessary ground: how it works (graph traversal), how to control it (depth/breadth/limit/timeout), and how to handle edge cases (timeouts, instructions for filtering). It doesn't explicitly mention prerequisites like authentication or public accessibility, but these are not critical for a mapping tool. The output schema covers return values, so that gap is acceptable.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds value beyond the schema by explaining the purpose of parameters in context (e.g., depth and breadth control under 'Depth & Breadth Control', instructions under 'Instruction Filtering') and giving concrete usage advice like 'Start with low max_depth (1-2) for initial exploration'. This goes beyond the schema's bare descriptions and provides actionable parameter 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 states a clear verb and resource: 'Maps a website's structure by traversing it like a graph, discovering URLs and generating a comprehensive site map.' This is specific and distinguishes it from siblings like web_search (searching) and web_fetch (fetching a single page). The mention of 'site map' and graph traversal makes the tool's role unambiguous.

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

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

The description provides best practices for using the tool (e.g., 'Start with low max_depth (1-2) for initial exploration', 'Use instructions to filter for specific content'), which gives practical usage context. However, it does not explicitly state when to use this tool versus alternatives or mention exclusions. There is no reference to sibling tools, so an agent must infer when web_map is appropriate. This is clear context but lacks explicit routing.

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 and it delivers meaningful context: it discloses the underlying services (Tavily, Firecrawl), the default model (GLM-5.2 via Ark), and even the caching behavior via the 'cached' flag. This goes beyond a simple 'search tool' and gives the agent insight into how results are generated and possibly stale.

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

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

The description is well-structured: a purpose sentence followed by a bulleted return list. The return list is necessary because no output schema exists, and each bullet earns its place. It is slightly more verbose than necessary but remains focused and front-loaded with the main function.

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

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

The description covers the search pipeline, default model, return values, and caching, and it links to a sibling tool (get_sources) via session_id. With no output schema, this is essential. It does not provide explicit alternatives for search-related choices (gemini_search), but that gap is primarily for usage guidelines. Overall, the description is reasonably complete for a read-only search tool with a rich schema.

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

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

Schema description coverage is 100%, so the schema already explains all three parameters clearly. The description adds little to parameter understanding, though it does connect the returned session_id to get_sources, which is output-related. Baseline 3 applies per the rubric.

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 'performs a deep web search' using Tavily + Firecrawl and synthesizes a cited answer with an LLM. This specific pipeline (multi-source + synthesis) distinguishes it from siblings like gemini_search, which likely uses a different search 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 phrase 'deep web search' implies when to use it, and the return field 'pass to get_sources' suggests a workflow. However, it does not explicitly state when to use this tool versus alternatives like gemini_search, web_fetch, or web_map, nor does it mention any exclusions.

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