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

Annotations indicate read-only and idempotent behavior. The description adds detail on what is shown (API key or browser login) and that instructions are provided if not authenticated, enhancing transparency without contradicting annotations.

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

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

Three short sentences, each with purpose. Very concise and front-loaded with the primary action.

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

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

For a simple auth check with no output schema, the description fully explains what it returns and under what conditions, leaving no ambiguity.

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

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

No parameters exist, so schema coverage is 100%. The description notes 'No arguments required,' which is sufficient.

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 ('Check') and resource ('authentication status'), clearly distinguishing it from sibling 'influq_login' for logging in.

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 states it shows current status and provides instructions if not authenticated, implying usage for status checking. However, it does not explicitly state when not to use or mention alternatives like influiq_login.

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

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, openWorldHint. The description adds valuable behavioral context: 'Free plans see up to 3 results; paid plans get full access.' This plan limitation is not in structured fields and helps the agent understand constraints.

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

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

The description is concise and well-structured: a clear purpose sentence, a plan limitation note, then a bulleted list of parameters. Every sentence adds value, and the most important information (search + filters) is front-loaded.

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

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

Given 15 parameters with full schema coverage and no output schema, the description explains all parameters and adds plan context. However, the return value ('List of influencer profiles with metrics') is vague; more detail on output fields would improve completeness. Still, it is sufficient for most use cases.

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

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

Schema coverage is 100%, but the description adds meaning beyond the schema by providing examples (e.g., categories: ['tech', 'gaming']), explicit thresholds for engagement_tier (e.g., 'high' >5%), and clarification of sort_by options. This helps the agent select appropriate 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 explicitly states the tool searches the InfluIQ discovery database for influencers matching criteria, with specific verb 'search' and resource 'influencers'. It lists many filters, distinguishing it from sibling tools like get_discovery_profile (single profile) or get_discovery_filters (available filters).

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 exclusions or suggest when not to use it. For example, it does not direct users to get_discovery_profile for a specific influencer.

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

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

Beyond the annotations (which indicate it is not read-only, destructive, or idempotent), the description adds that it consumes credits and outlines the return structure. This provides useful behavioral context that annotations alone do not. No contradictions detected.

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

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

The description is concise and well-structured, with the core purpose stated first, followed by a bulleted list of arguments and return type. Every sentence serves a purpose without redundancy.

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

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

For a simple tool with two parameters and no output schema, the description covers the essential purpose, inputs, output format, and credit consumption. However, it does not specify whether generation is synchronous or if it returns immediately with a report ID for later retrieval via 'influq_get_reputation_report'. This gap slightly reduces 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 already covers both parameters with descriptions. The description repeats the parameter names and types without adding significant new meaning (e.g., accepted URL formats, platform enumeration). With 100% schema coverage, the description does not need to compensate heavily, but it adds minimal extra value.

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

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

The description clearly states the tool generates a reputation report for an influencer, specifying the required input parameters and output format. It distinguishes itself from sibling tools like 'influq_get_reputation_report' by implying this creates a new report, while that retrieves an existing one.

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

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

The description notes that the tool consumes credits, which is a valuable usage consideration. While it doesn't explicitly list when not to use it or contrast with alternatives, the context of sibling names suggests this is for generating new reports. A clearer exclusion (e.g., use 'influq_get_reputation_report' if report already exists) would elevate it to 5.

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

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

Annotations (readOnlyHint=true, idempotentHint=true) align with 'Retrieve'. Description discloses return contents (engagement metrics, audience demographics, etc.) beyond annotations. Lacks mention of error handling for invalid IDs but overall sufficient.

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

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

Description is efficiently structured with clear sections, but could be slightly more concise. Front-loaded with primary purpose.

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

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

Given one parameter, no output schema, and comprehensive annotations, the description fully covers usage: return contents, alternative tool, and parameter source.

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?

Only one parameter 'analysis_id' with 100% schema coverage. Description adds value by stating 'The UUID of the analysis (from influiq_start_analysis)', clarifying its origin beyond schema's 'Analysis UUID'.

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 'Retrieve the full results of a completed influencer analysis' with a specific verb and resource. It distinguishes from sibling tool 'influiget_analysis_progress' by noting that for progress, use that tool.

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

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

Provides explicit alternative: 'If the analysis is still processing, check status with influiq_get_analysis_progress.' Also prerequires analysis_id from 'influiget_start_analysis', clarifying the source of the parameter.

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

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

Annotations provide readOnly, idempotent, non-destructive hints. Description adds context: lightweight endpoint and return shape (status, progress 0-100, currentStep). No contradictions.

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

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

Extremely concise: two sentences plus an Args/Returns block. Purpose is front-loaded. Every part adds value.

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

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

Given single parameter and rich annotations, the description fully explains return shape, making it complete for its use case.

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

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

Only one parameter (analysis_id). Schema coverage is 100% with description 'Analysis UUID'. Description states 'The UUID of the analysis', adding slight clarification. 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?

Clearly states it polls progress of a running analysis. Distinguishes from sibling tools like list_analyses and start_analysis.

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 checking progress via 'Poll the progress of a running analysis' and 'Lightweight endpoint', but does not explicitly state when not to use or suggest alternatives.

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

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

Annotations already provide safety and idempotency hints. Description adds the return format '{ credits: number }', going beyond annotations. No contradictions.

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

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

Three concise sentences with no filler. Purpose is front-loaded. Every sentence adds value.

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

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

Given zero parameters and no output schema needed, description fully covers purpose, usage, and return type. No gaps.

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

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

No parameters exist, and schema coverage is 100%. Description explicitly confirms 'No arguments required', adding clarity beyond the empty schema.

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

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

Clearly states the verb 'check' and resource 'current analysis credit balance'. Distinguishes from sibling tools which involve analyses, reports, 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?

Explicitly states 'No arguments required', indicating simple invocation. While no alternatives or exclusions are mentioned, the context is clear for a balance-check tool.

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

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

Annotations already provide full readOnlyHint and idempotentHint. Description adds return field names but no further behavioral disclosure beyond what annotations cover.

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 brief, front-loaded with the core purpose, and lists return fields efficiently. 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 parameterless, read-only tool with comprehensive annotations, the description fully covers the return data and usage model.

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

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

No parameters exist, and description confirms 'No arguments required.' Schema coverage is 100%, so no additional semantic explanation 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?

Title and description explicitly state 'Get Dashboard Statistics' and list specific aggregated metrics, distinguishing it from sibling tools that focus on individual analyses or credit balance.

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?

Clearly states 'No arguments required,' implying simple invocation. Lacks explicit when-to-use guidance versus siblings, but context suggests it is for high-level overview.

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, so the safety profile is clear. The description adds value by specifying the exact return shape (categories as objects with slug/name, languages and countries as string arrays). This provides behavioral detail beyond the annotations.

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

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

The description is extremely concise: two sentences plus a brief return type specification. Every part adds value—purpose, argument requirement, and output structure. No filler or 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 that there is no output schema, the description provides a complete picture: purpose, argument requirement, and return format. It covers all necessary aspects for an agent to understand and use this tool without additional context.

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

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

The input schema has zero parameters, and the description states 'No arguments required,' which is helpful. With 100% schema coverage (no params to cover) and zero parameters, the baseline is 4, and the description meets that threshold.

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

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

The description clearly states 'Get available filter options for discovery' and specifies the three types (categories, languages, countries). This verb+resource structure is specific and distinguishes it from sibling tools (e.g., influiq_discover_influencers, influiq_get_analysis).

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 'No arguments required,' giving clear usage guidance. While it does not mention when not to use or compare directly with siblings, the context makes it obvious that this is a standalone getter for filter options. A 5 would require explicit alternatives or exclusions.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description's mention of return fields (metrics, categories, demographics, sponsorship data) adds valuable behavioral context beyond annotations. It does not contradict annotations.

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

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

Extremely concise: two sentences and a structured parameter/return list. No wasted words, front-loaded with purpose.

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

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

For a simple single-parameter lookup tool with comprehensive annotations, the description adequately covers what the tool does and returns. No output schema exists, but the return fields are listed, providing sufficient context for agent decision-making.

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% (profile_id described with UUID). The description restates the parameter without adding new meaning, so baseline 3 is appropriate.

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

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

The description clearly states the action 'Get detailed profile' of a specific resource 'discovered influencer by ID'. It distinguishes from siblings like 'discover_influencers' (discovery) and 'get_analysis' (analysis), making the tool's unique role obvious.

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 a profile_id is available, but it does not explicitly guide when to choose this tool over alternatives like 'influIQ_get_discovery_filters' or 'influIQ_get_analysis'. No when-not-to-use or alternative recommendations.

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

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

Annotations already declare readOnlyHint, idempotentHint, etc. The description adds return content details (scores, trust signals, risk factors) which enriches behavioral context without contradicting annotations.

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

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

The description is extremely concise (3 lines) with clear Args and Returns sections. Every sentence adds value, 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?

For a simple retrieval tool with one parameter and read-only annotations, the description covers purpose, parameter, and return content. It could mention that the report must exist, but overall sufficient.

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

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

The input schema already describes 'report_id' as 'Reputation report UUID'. The description repeats this with 'Report UUID', adding no new semantic value beyond the schema.

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

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

The description uses specific verb 'Retrieve' and resource 'reputation report' with clear identification by ID. It distinguishes from siblings like 'influq_list_reputation_reports' and 'influq_generate_reputation_report'.

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 'previously generated' implying the report must exist. It provides clear context for retrieval but does not explicitly state when to use versus listing or generating reports.

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true, so the safety profile is clear. The description adds a detailed return structure, including fields like subscription status and plan details, which provides useful behavioral context beyond annotations.

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

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

The description is concise: two sentences. The first states the purpose, and the second specifies no arguments and shows the return shape. Every sentence contributes value without waste.

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 no parameters and rich annotations, the description is fairly complete. It provides the return structure (missing an output schema). However, it does not differentiate usage from sibling tools like 'influIQ_list_plans' or 'influIQ_get_credits_balance', which slightly reduces 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?

There are zero parameters, and the input schema is empty with 100% coverage. The description correctly notes 'No arguments required.' According to the guidelines, 0 parameters gives a baseline of 4, and no additional parameter semantics are 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 explicitly states 'Get your current subscription plan, status, usage, and billing period.' It uses a specific verb and resource, and clearly distinguishes from sibling tools like 'influIQ_list_plans' which lists available plans, and 'influIQ_auth_status' which checks authentication.

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 any guidance on when to use this tool versus alternatives. It states 'No arguments required' but does not provide context on when not to use it or mention specific use cases. No exclusions or alternatives are discussed.

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

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

Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true. The description adds value by stating the return format (paginated list with id, platform, username, status, date) and pagination behavior, which goes beyond the annotations.

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

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

The description is concise (three sentences plus args list) and well-structured with bullet points. Every sentence adds value without unnecessary 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 output schema, the description explains return fields adequately. However, it misses pagination metadata (e.g., total count) and omits 'pending' in status list. Overall sufficient for a list tool with good annotations.

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 of parameters is 100%, so baseline is 3. The description repeats defaults and enum values already in the schema, but provides no new semantic insight. It also omits 'pending' from the status enum (schema includes it), a minor inaccuracy.

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 'past influencer analyses', with pagination. It distinguishes this tool from siblings like influiq_get_analysis (single analysis) and influiq_start_analysis (start new analysis) by focusing on history listing.

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 past analyses with filters, but does not explicitly state when to use this tool versus alternatives (e.g., use get_analysis for a single analysis). No when-not or exclusion criteria are provided.

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

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

Annotations already provide readOnlyHint, destructiveHint, idempotentHint, openWorldHint. The description adds return shape information but does not contradict annotations. Adds modest behavioral context beyond annotations.

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

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

Three concise sentences with no superfluous information. The key points are front-loaded, making it easy to parse quickly.

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 zero parameters, rich annotations, and the description outlines the return structure, it is fully complete for agent invocation. No gaps remain.

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

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

No parameters expected, and schema coverage is 100%. Description clarifies 'No arguments required,' which adds confirmation. Baseline for zero params is 4.

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

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

The description uses a clear verb 'List' and specific resource 'all available InfluIQ subscription plans' with details on pricing and features. It distinguishes from sibling tools like 'influq_get_subscription' which likely retrieves a single plan.

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

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

It explicitly states 'No arguments required,' guiding the agent on invocation. However, it doesn't explicitly contrast with siblings like 'influq_get_subscription' for retrieving current user's plan, but the sibling names imply different use cases.

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

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, and openWorldHint. The description adds only that the tool returns a paginated list, which is expected. It fails to disclose any additional behavioral traits such as result ordering, scope of 'your' (e.g., user or workspace), or handling of empty results.

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

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

The description is extremely concise: a single sentence overview followed by a clear list of parameters with defaults. Every sentence is necessary and efficiently structured, with no extraneous information.

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

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

Given the absence of an output schema, the description provides minimal return information ('Paginated list of reputation reports'), omitting details like pagination metadata, report fields, or error handling. However, considering the tool's simplicity and rich annotations, the description is adequate but not comprehensive.

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

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

Schema coverage is 100%, with both parameters (page and limit) fully described in the schema. The description simply restates their defaults, adding no new semantic meaning beyond what the schema already provides.

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

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

The description clearly states the tool lists 'your reputation reports with pagination,' specifying the verb 'list' and the resource 'reputation reports.' However, it does not explicitly distinguish from sibling tools like influiq_get_reputation_report or influiq_list_analyses, which could cause confusion.

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. For example, it does not explain when to list reports versus retrieving a single report, nor does it mention any prerequisites or context for pagination 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?

The description fully explains the tool's behavior: opening a browser, secure credential entry, automatic session linking without token copying. It also states no arguments are required. This goes beyond the annotations, which only indicate idempotence. No contradictions with annotations.

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

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

The description is well-structured with a clear main sentence followed by logical subsections about the login process and API key alternative. It is front-loaded with the core purpose. Every sentence contributes meaningfully without redundancy.

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

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

Given the tool's simplicity (no parameters, straightforward login action), the description covers all necessary aspects: what it does, how it works, and an alternative method. There is no output schema, but the description implicitly covers expected outcomes. It is fully adequate for the tool's complexity.

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

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

There are no parameters, and the description explicitly states 'No arguments required.' According to the baseline for zero parameters, a score of 4 is appropriate as the description adds value by confirming the absence of inputs.

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: signing in to InfluIQ by opening a login page in the browser. It distinguishes itself from API key authentication by providing alternative instructions. The verb 'Sign in' and the resource 'InfluIQ' are specific, and the purpose is distinct from sibling tools like influiq_auth_status.

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

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

The description provides clear when-to-use guidance: 'alternative to API key authentication' and gives detailed steps for API key setup. However, it does not explicitly compare to the sibling tool influiq_auth_status for checking login state, which would be a helpful exclusion criterion.

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

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

Beyond annotations (readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true), the description adds that it consumes 1 analysis credit, supports only YouTube/Instagram, and returns an analysisId for polling. No contradictions.

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

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

The description is well-structured: a concise introductory paragraph followed by a brief args list. Every sentence adds value, and the key information (purpose, credit cost, platforms, return value) is front-loaded.

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

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

Despite no output schema, the description explicitly states the return structure (analysisId, status, platform, creditsRemaining). It covers all parameters, explains the workflow, and provides enough detail for an agent to use the tool correctly.

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

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

Schema coverage is 100%, so the schema documents all parameters. The description adds value with examples (e.g., 'https://youtube.com/@MrBeast'), clarifies that username can include '@', and explains brand_profile_id is for brand-fit scoring. This supplements the schema.

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

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

The description clearly states it starts a new influencer analysis, specifies supported platforms (YouTube, Instagram), and explains how to provide input (URL or platform+username). It also distinguishes from siblings by mentioning the returned analysisId for polling with influiq_get_analysis.

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 clear context on when to use: to start an analysis, consuming 1 credit, and that it returns an analysisId for polling. It does not explicitly state when not to use or direct to alternatives, but the context is sufficient for most agents.

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