ThinkNEO Control Plane

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

Annotations already indicate read-only and idempotent. Description adds key behavioral context: immutable trail, hash verification, cryptographic chaining for tamper detection, which goes beyond annotations.

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

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

Two sentences, front-loaded with purpose, no wasted words. Every sentence adds essential 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?

Simple tool with 2 optional params, output schema present, annotations cover safety. Description lacks mention of return format or pagination, but overall adequate for its 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%, and description does not add extra meaning beyond the schema's parameter descriptions. No additional format or usage details provided.

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

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

Clearly states the tool retrieves an immutable audit trail for A2A interactions with hash verification and cryptographic chaining, distinguishing it from siblings like thinkneo_a2a_log (logging) and thinkneo_audit_export (exporting).

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., thinkneo_a2a_log, thinkneo_audit_export). Does not mention prerequisites, when-not-to-use, 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 destructiveHint=false. The description adds context that data comes from the 'live gateway', implying real-time visibility, and clarifies output contents. This goes beyond the structured 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?

Two sentences, both front-loaded. No redundant or irrelevant 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 an output schema present, the description doesn't need to detail return values. It covers the tool's purpose, inputs implied via schema, and output nature. No obvious gaps.

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

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

Schema coverage is 100% and the description does not mention the workspace parameter or add any semantics beyond the schema's description. Baseline 3 applies.

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

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

The description clearly states 'Visualize agent-to-agent communication flow' and specifies what is shown: registered agents, approval status, and interaction patterns. This distinguishes it from sibling tools like thinkneo_a2a_audit or thinkneo_a2a_log.

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 when-to-use guidance or comparison with alternatives is provided. The description only states what the tool does, leaving the agent to infer when to use it versus other a2a 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds behavioral context by specifying what data is returned (agents, actions, costs, outcomes) and that it comes from the live gateway, which implies near real-time data. 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?

Two sentences with no wasted words. The first sentence states the core purpose, and the second adds key details. Very concise 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?

Given the simplicity of the tool (2 optional parameters, output schema exists), the description covers the essential information: what logs are retrieved and what data is shown. No further context is needed for a read-only log retrieval tool with rich annotations and schema.

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

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

Schema coverage is 100%, so the input schema already documents both parameters (limit and workspace) with descriptions. The description does not add additional meaning beyond what the schema provides, 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 it retrieves A2A interaction logs and specifies the fields shown (agents, actions, costs, outcomes). The verb 'Retrieve' and resource are specific, but it does not explicitly differentiate from sibling tools like thinkneo_a2a_audit or thinkneo_get_trace, though the focus on logs is implied.

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., thinkneo_a2a_audit for auditing or thinkneo_get_trace for specific traces). It only implies usage for retrieving logs, but does not mention 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?

Annotations already indicate read-only and non-destructive behavior. The description adds that the tool retrieves from the 'live gateway', which implies real-time data. However, it does not disclose additional traits like pagination, performance, or data freshness. With annotations present, the description contributes moderate 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 two concise sentences. The first states the primary action, and the second lists the contents. No unnecessary words or redundancy. 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?

Given the existence of an output schema and comprehensive annotations, the description adequately covers the tool's purpose and behavior. It is sufficient for an agent to understand when to use it. A minor improvement could mention any access prerequisites, but overall it is 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?

The input schema has 100% description coverage for its single parameter ('workspace'). The tool description does not add any meaning beyond what the schema already provides, so it meets the baseline without further enhancement.

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

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

The description clearly states the action ('retrieve') and resource ('A2A interaction policies from the live gateway'). It also lists specific data elements (allowed actions, rate limits, cost caps, approval requirements), which distinguishes it from sibling policies-focused tools like thinkneo_check_policy or thinkneo_policy_list.

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 reading policies from the live gateway, but it does not explicitly state when to use this tool versus alternatives (e.g., thinkneo_policy_list, thinkneo_policy_evaluate) or mention any exclusions. The guidance is indirect.

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, destructiveHint. Description adds context on output details (daily trend, success rate, baseline comparison) beyond annotations, aiding agent understanding of what computations occur.

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 efficient sentences front-loading purpose, with no wasted words. Clear and direct.

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 full schema coverage, rich annotations, and output schema, description sufficiently covers core ROI calculation. Could mention need for historical data but not essential.

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

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

Schema coverage is 100% with clear parameter descriptions. The overall description adds no additional parameter details beyond schema, meeting baseline expectation but not exceeding.

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

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

Description clearly states 'Calculate ROI per AI agent' and specifies outputs: value vs cost, daily trend, success rate, pre-AI baseline. Answers explicit questions, distinguishing it from sibling tools like thinkneo_business_impact.

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

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

Description implies usage for agent ROI analysis but lacks explicit when-to-use vs alternatives or when-not-to-use. No comparison to siblings like thinkneo_get_savings_report or thinkneo_benchmark_compare.

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

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

Annotations indicate non-read-only, non-destructive, non-idempotent. The description adds the authentication requirement and example constraints (e.g., budget_usd required for certain metrics), but does not fully disclose side effects or error behavior. It covers basic behavioral traits but not comprehensively.

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: purpose, example, requirement. Every sentence provides value without redundancy or wasted words.

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

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

Given 10 parameters and an output schema (exists but not shown), the description is fairly complete with a comprehensive example. It could mention return values or error cases, but the schema compensates. Leave some room for improvement.

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 good parameter descriptions. The description's example demonstrates parameter relationships (e.g., metric=key_spend_pct_of_budget needs budget_usd and scope_value) but does not add extensive new meaning beyond the schema.

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

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

The description explicitly states 'Create a Monitor Agent alert rule,' which is a specific verb and resource. It distinguishes itself from sibling tools like thinkneo_alert_rule_delete and thinkneo_alert_rule_list through the action and example.

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

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

The description provides a concrete example and mentions the requirement for an admin API key, giving clear context. However, it does not explicitly state when not to use this tool versus alternatives, though sibling names imply creation vs. deletion or 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?

Annotations already provide destructiveHint=true and readOnlyHint=false. The description adds the behavioral trait that an admin API key is required, which is not captured by annotations. There is no contradiction with annotations.

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

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

The description is a single, well-structured sentence that front-loads the action and resource, with no unnecessary words. Every part is informative.

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 complete input schema descriptions, the description provides sufficient context for a delete operation. It could mention permanence or idempotency, but the annotations already cover these aspects.

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

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

The input schema has 100% description coverage, so the baseline is 3. The description adds no new parameter semantics beyond what is already in the schema; it merely restates 'rule_id' without additional detail.

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

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

The description clearly states the action ('Delete') and the resource ('a Monitor Agent alert rule'), and specifies the identifying mechanism ('by its rule_id'). This uniquely distinguishes it from sibling tools like thinkneo_alert_rule_create and thinkneo_alert_rule_list.

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 notes a key prerequisite: 'Requires an admin API key.' While it does not explicitly state when not to use the tool or mention alternatives, the sibling tools are distinct enough that the purpose alone implies when to use this tool over others.

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 readOnly, idempotent, non-destructive. Description adds admin API key requirement, which is useful. No contradiction.

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

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

Two sentences, efficient. First sentence states purpose, second provides examples and auth requirement. No unnecessary words.

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

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

Covers purpose, examples, auth. Has output schema so return details omitted. Could mention pagination or sorting, but not essential.

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

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

Schema covers 100% of parameter description. Description does not add additional meaning beyond the schema's explanation of optional workspace defaulting.

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 states 'List your configurable Monitor Agent alert rules' with specific verb and object, and explains what the rules watch and notify. Clearly distinguishes from sibling tools like create, delete, test.

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?

Explains when to use (to view rules) and prerequisite (admin API key). Lacks explicit when-not-to-use but context is clear from siblings.

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

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

Annotations already indicate non-readonly and non-destructive behavior. The description clarifies that the tool sends a test notification, but does not elaborate on potential side effects (e.g., actual delivery, rate limits, or cost implications). Given no contradiction with annotations, the description adds limited transparency beyond the structured fields.

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, clear sentence followed by a necessary prerequisite note. No redundant or unnecessary words; every part serves a purpose. Ideal conciseness.

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

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

Given the tool's action (sending a test notification) and the presence of an output schema (not shown but flagged), the description covers the main purpose and a key requirement. It does not discuss error conditions, asynchronous behavior, or what the response entails, but the output schema likely fills that gap. Nearly complete for a straightforward test tool.

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

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

Schema coverage is 100%, providing descriptions for both parameters. The description adds value by cross-referencing 'from thinkneo_alert_rule_list' for rule_id and noting the admin API key requirement, which is not a parameter but relevant context. This goes beyond baseline 3.

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

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

The description clearly states the action 'Send a test notification' with the specific resource 'a rule's configured channels' and lists supported channels (email/discord/whatsapp). It effectively distinguishes this test tool from sibling tools like thinkneo_alert_rule_create, thinkneo_alert_rule_delete, and thinkneo_alert_rule_list.

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 mentions 'Requires an admin API key', providing a critical prerequisite. While it implies usage after rule creation (to confirm delivery), it does not explicitly state when to use this tool versus alternatives or mention that the rule must exist and have configured channels. Still, the context of 'test notification' gives reasonable 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds context about exporting from the 'live gateway' and the purpose for SIEM integration, which is useful. 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?

Two concise sentences front-load the core purpose and key features (formats, date filtering, SIEM). 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 existence of an output schema, the description does not need to explain return values. It covers the export nature, formats, filtering, and a use case. However, it lacks mention of default behavior or potential size/limits, which would add slight improvement.

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 parameters. The description adds that formats are JSON/CSV (schema says ndjson and csv) and mentions date range filtering, but does not provide new details beyond the schema. Baseline 3 is appropriate.

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

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

The description clearly states the tool exports audit events from the live gateway, mentions support for JSON and CSV formats with date range filtering, and indicates SIEM integration as a use case. This specific verb+resource description distinguishes it from siblings like thinkneo_a2a_audit and thinkneo_list_alerts.

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 exporting audit events for SIEM integration but does not explicitly state when to use this tool versus alternatives like thinkneo_a2a_audit or thinkneo_list_alerts. No exclusion criteria or prerequisites 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 declare readOnlyHint=true, destructiveHint=false, indicating a safe read operation. The description adds context about required authentication and mentions the output (quality scores, verification rates, rankings), which helps the agent understand the tool's behavior 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—two sentences with no wasted words. The key information is front-loaded, starting 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?

Given the complexity of a comparison tool, the description covers purpose, parameters, and general output. The presence of an output schema likely provides formal structure for return values, so the description is sufficient.

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

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

Schema coverage is 100%, so the schema already documents both parameters. The description restates the parameter types and provides an example for providers, but does not add significant new 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's function: 'Compare providers side-by-side for a specific task type.' It lists specific outputs (quality scores, verification rates, rankings) and distinguishes itself from siblings like thinkneo_compare_models (which compares models) and thinkneo_benchmark_report (which likely provides a broader 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 'Requires authentication' as a prerequisite but does not provide explicit guidance on when to use this tool versus alternatives. It implies use for comparing providers for a specific task, but no when-not-to or alternative tool references.

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

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

Annotations already declare readOnlyHint and idempotentHint, so the description needn't repeat those. It adds authentication requirement and describes output contents, providing moderate added value.

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-loaded with the core purpose, and every sentence adds value without redundancy.

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

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

Given an optional parameter and output schema (context indicates present), the description adequately explains what the tool shows and how to filter, making it complete for selection and invocation.

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

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

Schema description coverage is 100% with explicit details about the task_type parameter. Description does not add meaning beyond the schema, so baseline 3 applies.

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

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

Description clearly states the tool 'View the outcome benchmark matrix' with specific details about real quality scores per provider/model/task_type, distinguishing it from siblings like thinkneo_benchmark_compare.

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

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

Description provides context for viewing benchmark data but does not explicitly tell when to use this tool vs alternatives like thinkneo_benchmark_compare or thinkneo_compare_models.

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, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds no behavioral context beyond the name, such as how agent_name is used or what happens when it's empty. With annotations carrying most of the burden, the description adds minimal value.

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 directly states the tool's purpose without any extraneous information. It is efficiently front-loaded and every word 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?

Given the tool's simplicity (one optional parameter, output schema present), the description provides the core purpose. However, it lacks context about the bridging mechanism (e.g., it might clarify that it wraps an A2A agent as an MCP tool for agent-isolated usage). This is adequate but not fully complete for an agent to understand implications.

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% as the single parameter 'agent_name' has a description in the schema. The tool description does not add any additional meaning or context for the parameter, so it meets the baseline for a fully covered 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 'Bridge A2A agents to MCP tool format' uses a specific verb (bridge) and resource (A2A agents to MCP tool format), clearly distinguishing it from the sibling tool 'thinkneo_bridge_mcp_to_a2a' which performs the inverse operation.

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 its alternatives. There is no mention of when bridging is appropriate, prerequisites, or exclusions, leaving the agent to infer usage from the name 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds the context that it generates a card from registry data, which is consistent but adds little 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 a single concise sentence, but it is overly brief and lacks structure. It is adequate but could benefit from more detail without being verbose.

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

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

Given the tool has one parameter, no nested objects, and an output schema exists, the minimal description is acceptable but does not explain what the card contains or any prerequisites, leaving some context 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 100% (agent_id). The description does not add any additional meaning or usage details beyond what the schema provides, so baseline score 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 verb 'Generate', the resource 'A2A Agent Card', and the source 'from registry data'. It is specific and distinguishes the tool from siblings like registry_get or registry_search.

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

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

No explicit guidance on when to use this tool versus alternatives. The description does not provide any 'when', 'when not', or mention of sibling tools for context.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds no behavioral context beyond 'list all...', such as pagination, ordering, or impact. It does not contradict annotations but adds minimal value.

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 with no fluff. Front-loaded with the verb and clear object. Highly concise 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?

Given no parameters and the presence of an output schema, the description is complete enough for a list operation. It defines the scope (tenant) and resource. Slightly unclear about what a 'bridge mapping' comprises, but sibling names provide context.

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

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

No parameters exist in the schema, so baseline is 4. There is nothing to document, and the description does not need to add parameter 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 states specifically 'List all MCP <-> A2A bridge mappings for a tenant,' clearly defining the action (List), the resource (MCP<->A2A bridge mappings), and scope (all, per tenant). This distinguishes it from siblings like thinkneo_bridge_a2a_to_mcp which likely create or manage individual mappings.

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 over alternatives. The description does not mention prerequisites, context, or contrasts with other list or bridge tools. For a simple list tool, it's usable but lacks explicit usage direction.

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, idempotentHint=true, and destructiveHint=false, so the description carries a lighter transparency burden. The description adds that it shows tool-to-skill mappings, which is consistent. No additional behavioral details are disclosed beyond what annotations provide.

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 short sentences that clearly convey the tool's function. It is front-loaded with the core action ('Bridge MCP tool registry to A2A format') and no superfluous text.

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

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

Given the tool's simplicity (one optional parameter, output schema present), the description adequately covers its purpose. It could mention what a 'tool-to-skill mapping' entails, but the output schema likely fills that gap. Overall complete for the tool's scope.

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 the parameter 'tool_name' described as 'MCP tool name to bridge'. The description adds no extra meaning beyond this. Baseline 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 uses specific verbs 'bridge' and 'shows' to indicate the tool converts MCP tool registry to A2A format and displays mappings. It distinguishes from sibling 'thinkneo_bridge_a2a_to_mcp' which likely does the reverse. However, it could be more explicit about taking a tool name as input and returning its A2A mapping.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'thinkneo_bridge_list_mappings' or 'thinkneo_bridge_a2a_to_mcp'. It does not mention prerequisites, context, 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 indicate readOnlyHint=true and idempotentHint=true, and the description adds no contradictory information. The description provides additional context by listing the specific metrics returned, which helps the agent understand the scope of data beyond just '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 extremely concise at just two sentences. It front-loads the purpose and immediately explains the value proposition, with no wasted words.

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

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

Given the complexity of the tool (aggregating multiple business metrics), the description adequately covers what is returned. An output schema exists to define return values, so the description does not need to detail them. It is complete enough for an agent to understand the tool's purpose.

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

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

The input schema has 100% coverage with descriptions for both parameters (period and workspace). The description does not add extra meaning beyond the schema, so it meets the baseline of 3.

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

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

The description clearly states it is an executive business impact dashboard that returns a single view of specific metrics like total value, cost, ROI, etc. It distinguishes itself from sibling tools like thinkneo_agent_roi (agent-specific ROI) and thinkneo_decision_cost (cost per decision) by aggregating multiple metrics into one executive 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 implies usage for CxO-level justification of AI investment, providing clear context. However, it does not explicitly state when not to use this tool or suggest alternatives for more granular metrics.

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, idempotentHint=true, destructiveHint=false, fully covering safety. The description adds context about the source ('live gateway runtime metrics') but no further behavioral traits. Acceptable given rich 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?

Single sentence of 9 words, front-loaded with the action and resource. No redundancy or unnecessary 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 low complexity (0 params, safe annotations, output schema exists), the description fully covers what the tool does and the data source. No missing critical information.

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

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

There are no parameters, and the baseline score for 0 parameters is 4. The description adds no param details, which is fine since none exist and schema coverage is 100%.

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 'Get' and specifies the exact resource 'semantic cache stats' and source 'live gateway runtime metrics'. It distinguishes from siblings like thinkneo_billing_status or thinkneo_provider_status which target different resources.

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 cache stats are needed but provides no explicit when-to-use or when-not-to-use guidance, nor mentions alternatives. Given the tool's simplicity, this is adequate but not explicit.

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds context that no authentication is required and that it returns a safety assessment with specific warnings, which are not provided by annotations alone. No contradiction.

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

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

The description is three sentences, each serving a distinct purpose: introducing the tool, detailing its capabilities, and clarifying access requirements. No wasted words 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 the tool has one parameter fully described in schema, annotations covering safety, and an output schema, the description provides clear purpose, input scope, output summary, and access requirements. It is sufficiently complete 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?

The schema already provides a full description for the single 'text' parameter, including the max 50,000 character limit. The tool description does not add any additional meaning beyond what the schema offers, so baseline 3 is appropriate.

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

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

The description clearly states the tool performs a prompt safety check, analyzing for injection patterns and specific PII types. It distinguishes itself as a free-tier option covering both categories, but does not explicitly contrast with sibling tools like thinkneo_detect_injection or thinkneo_detect_pii_intl.

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 via 'Free-tier' but provides no explicit guidance on when to use this tool versus alternatives like thinkneo_detect_injection or thinkneo_detect_pii_intl. There are no when-not 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 indicate read-only, idempotent, non-destructive behavior. The description adds useful context (no auth required, compliance purpose) but does not elaborate on side effects or rate limits beyond what annotations provide.

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, comprehensive sentence that front-loads the main action. It is concise yet informative, though could be better organized (e.g., bullet points) for 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, the description sufficiently covers the tool's functionality and scope. It mentions compliance requirements and supported regions, making it complete 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% with clear descriptions for both parameters. The description adds significant value by listing all supported country codes and document types, including Luhn validation for credit cards, providing 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 purpose: detect international PII across 30+ document types from 15+ countries, with specific examples. It differentiates from siblings like thinkneo_check and thinkneo_check_policy by focusing on international coverage and compliance requirements.

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 compliance checking (LGPD/GDPR/HIPAA) and mentions no authentication required, but does not explicitly state when to use versus alternatives or provide exclusions.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, providing safety guarantees. The description adds context by listing the types of policies checked (e.g., model access, budget limits), which goes beyond the annotations. No contradictions found.

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, clear sentence that efficiently communicates the tool's purpose and scope. It is front-loaded with the verb and resource, and every word contributes value without redundancy.

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

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

Given the low complexity (one optional parameter, high schema coverage, annotations present, and an output schema exists), the description adequately covers the tool's behavior. The presence of an output schema means 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?

The only parameter 'workspace' is well-described in the input schema (100% coverage). The tool description does not add any new meaning beyond what the schema provides, so the baseline score of 3 is appropriate.

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

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

The description clearly states the verb 'Check' and the resource 'AI governance policies', specifying the areas covered (model access, budget limits, data controls, agent governance). This distinguishes it from siblings like thinkneo_policy_create or thinkneo_policy_list, which have different 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?

The description implies usage for checking policies but does not provide explicit guidance on when to use this tool versus alternatives like thinkneo_policy_list or thinkneo_policy_evaluate. No when-not-to-use or context exclusions are 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?

Annotations indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which already convey that the tool is safe and idempotent. The description adds that it returns a 'real cost breakdown', but does not address additional behavioral traits such as caching, rate limits, or authentication requirements. Since annotations already cover safety, the description provides marginal extra transparency.

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

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

The description is a single sentence that succinctly states the purpose and return value. It is front-loaded and avoids unnecessary words. However, it could be slightly more structured (e.g., listing the breakdown dimensions explicitly) to improve scannability.

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 an output schema exists (providing return value details) and the input schema is fully described, the description sufficiently covers the tool's purpose and parameters. It explains what the returned breakdown includes (provider, model, time period), making it complete for a simple read query tool.

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

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

The input schema provides full coverage (100%) with descriptions for all three parameters: period, group_by, and workspace. The description does not add new semantic meaning beyond what the schema already offers; it merely summarizes the output. 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 verb 'check', the resource 'AI spend summary', and the scope 'workspace, team, or project'. It specifies the return value as a 'real cost breakdown by provider, model, and time period'. This distinguishes it from sibling tools like thinkneo_billing_status or thinkneo_get_budget_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 implies usage for checking spend but does not provide explicit guidelines on when to use this tool versus alternatives (e.g., thinkneo_get_savings_report, thinkneo_simulate_savings). There are no exclusions or context about prerequisites or complementary 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the tool's safety profile is known. The description adds the context that it accesses the 'live gateway catalog', but does not disclose specific behavioral traits like rate limits, error responses, or result details beyond the scope.

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 extraneous words. Every word earns its place.

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

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

For a simple tool with one parameter, an output schema, and clear annotations, the description is mostly complete. It could mention what the comparison result looks like (e.g., side-by-side view), but the output schema may cover that. Still, a minor gap 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 coverage is 100% with the 'models' parameter already well-described. The description does not add any additional meaning beyond the schema, so baseline score 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 verb 'compare' and the resource 'available AI models from the live gateway catalog'. It distinguishes itself from sibling tools like thinkneo_benchmark_compare by specifying the source (live gateway catalog vs. benchmarking results).

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 explicit guidance on when to use this tool versus alternatives (e.g., thinkneo_benchmark_compare). The context is clear but no when-not or alternative tooling advice 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?

Annotations indicate readOnlyHint=false and destructiveHint=false, but the description adds key behavior: requests are policy-checked before reaching the model, and blocked prompts never arrive. This goes beyond annotations by explaining the governance flow.

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

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

Two concise sentences front-load the main action and key behavioral trait. Every sentence adds value with no redundancy.

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

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

Given the output schema exists (not shown), the description covers governance, authorization, and tenant/workspace derivation. It lacks details on streaming or async behavior, but openWorldHint suggests general applicability, making it sufficiently 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 coverage is 100% with all parameters documented. The description adds no extra semantics beyond what the schema already provides, achieving the baseline for high-coverage schemas.

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 governed LLM completion through a gateway, with specific verbs 'Run' and 'governed'. It distinguishes from siblings like thinkneo_count_tokens or thinkneo_route_model by focusing on completion with policy enforcement.

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 governance is needed (authorization, classification, policy-checking) and states workspace derivation from API key. While it doesn't explicitly exclude alternatives, the context is clear for an AI agent to decide when to use this completion 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 indicate read-only and idempotent behavior; the description adds that data comes from live audit data, which is valuable context beyond the 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?

A single concise sentence that front-loads the core purpose and includes key details (frameworks, data source). No wasted words.

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

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

With an output schema present, the description adequately covers purpose and data source. Could mention that it generates report in the specified format, but that is implied. Sufficient for a simple generation tool.

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

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

Schema coverage is 100% with descriptions for all parameters. The description lists frameworks inline, but that adds no new information beyond what is in the schema's framework parameter 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?

The description clearly states the tool generates a compliance report for specific regulatory frameworks (EU AI Act, ISO 42001, SOC2, NIST), distinguishing it from related tools like thinkneo_get_compliance_status which likely retrieves status rather than generating a 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 provides the context of exporting from live audit data, but does not explicitly specify when to use this tool versus alternatives such as thinkneo_get_compliance_status or thinkneo_audit_export.

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. Description adds the specific approximation method 'chars/4', which is a useful behavioral trait 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?

Single sentence, front-loaded with the core purpose, no unnecessary words. 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?

For a simple one-parameter tool with an output schema and clear annotations, the description provides all necessary context: what it does and the approximation formula.

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

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

Schema description coverage is 100%, so baseline is 3. Description does not add any additional meaning beyond what the schema provides for the 'text' 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?

Clearly states the tool estimates token count for text using a chars/4 approximation. Distinct from siblings which focus on auditing, compliance, and other tasks.

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

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

No explicit guidance on when to use this tool versus alternatives or when not to use it. The description implies usage for token counting but lacks context on 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, idempotentHint=true, destructiveHint=false. The description adds behavioral context (shows costs, comparisons) but does not contradict annotations. It does not cover auth or rate limits, but with strong annotations, this is acceptable.

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 plus two embedded questions, no wasted words. Front-loaded purpose, very 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 the tool has 4 parameters and an output schema, the description sufficiently explains the tool's purpose and what it returns. The output schema handles detailed structure, so the description is 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 coverage is 100%, so the schema already documents all four parameters (period, workspace, agent_name, process_name). The description does not add further meaning beyond what the parameter descriptions provide. Baseline 3 is appropriate.

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

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

The description clearly states the tool analyzes cost-per-decision for AI agents and compares to pre-AI baseline. It answers specific questions, distinguishing it from sibling tools like thinkneo_agent_roi or thinkneo_get_savings_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 implicitly guides usage by stating what questions it answers ('How much does each AI decision cost?' and comparison). However, it does not explicitly exclude scenarios or compare to alternatives, which would be helpful given many siblings.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, establishing a safe, non-destructive profile. The description adds that the tool retrieves live stats beyond detection, which is useful context. However, it does not disclose limitations, edge cases, or how the stats are returned, so some behavioral details remain unaddressed.

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-loading the primary purpose and adding a secondary feature concisely. Every sentence is necessary, with no redundancy or wasted words.

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

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

Given the low complexity (one parameter, clear schema, output schema exists), the description is largely sufficient. It covers the core detection purpose and an additional stat retrieval. However, it is slightly ambiguous whether stats are returned alongside results or separately, and it does not reference the output schema, but that is not required.

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

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

The schema covers 100% of parameter descriptions, so the baseline is 3. The description does not add any extra meaning about the 'text' parameter beyond what the schema says (e.g., no format or length constraints).

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 detects prompt injection attempts in text using guardrail patterns, and also retrieves live guardrails_blocked stats. The verb 'detect' and resource 'text' are specific, but it does not differentiate from sibling tools like thinkneo_evaluate_guardrail or thinkneo_check_policy, which may have overlapping functionality.

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

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

The description provides no guidance on when to use this tool versus alternatives, nor does it mention when not to use it. It only states what it does, leaving the agent to infer usage context without 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?

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, which the description aligns with. The description adds that it returns specific actionable findings, but does not disclose additional behavioral traits beyond what annotations provide.

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 an example, efficiently conveying purpose and expected output. The example adds value but could be slightly more concise without losing clarity.

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

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

Given the simple parameters, full schema coverage, and presence of an output schema, the description adequately covers the tool's behavior. It explains what kind of findings to expect, though it does not mention prerequisites or setup requirements (likely unnecessary for a read-only tool).

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

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

Schema description coverage is 100% for both parameters (days and workspace). The description does not add new information about parameter meaning or usage beyond the schema, so it meets the baseline but does not exceed it.

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

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

The description clearly identifies the tool as detecting waste and inefficiency in AI operations, listing specific analyses (agent performance, A2A communication, error costs, unused capacity, cost outliers) and giving concrete examples of findings. This distinguishes it from siblings like thinkneo_a2a_audit and thinkneo_agent_roi.

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 as an initial diagnostic tool ('creates the buying trigger'), providing context for when to use it. However, it lacks explicit comparisons with alternatives or exclusions for ongoing monitoring, so it's clear but not fully prescriptive.

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 key behavioral traits beyond the annotations: it is a mutating operation (ending a trace), triggers a side effect (anomaly detection), and requires authentication. The annotations set readOnlyHint=false, destructiveHint=false, so the description adds necessary context about mutation and side effects. No contradiction exists.

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: stating the action and output, listing return values, and noting side effects and authentication. It is concise, front-loaded with the core purpose, and contains no unnecessary verbiage.

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 (2 parameters, output schema exists), the description covers all necessary aspects: what it does, what it returns, side effects (anomaly detection), and prerequisites (authentication). The presence of an output schema means return values are well-defined, and the description summarizes them adequately.

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

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

The input schema has 100% coverage, with both parameters (session_id and status) already described. The description does not add any additional meaning or constraints beyond what the schema provides. Baseline 3 is appropriate since the schema already handles parameter documentation.

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 ('End an active agent trace') and the primary output ('get the session summary'). It lists the specific metrics returned: total cost, duration, tool/model call counts, and event count. This distinguishes it from related siblings like thinkneo_start_trace (which starts traces) and thinkneo_get_trace (which retrieves trace info without ending).

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 context by stating 'End an active agent trace' and mentions a side effect ('Triggers post-session anomaly detection'). It does not explicitly state when not to use it or compare with alternatives like thinkneo_get_trace or thinkneo_start_trace, but the context is clear. The mention of authentication also provides a prerequisite.

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

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

Annotations already indicate read-only and non-destructive behavior. Description adds that it requires authentication and returns risk assessment, violations, and recommendations, which extends beyond annotations without contradiction.

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

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

Two efficient sentences: first states core purpose, second covers return type and authentication. No redundant information.

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

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

With output schema present, description need not detail returns. It covers purpose, usage timing, and authentication. Minor omission: no mention that tool does not execute the prompt.

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% (all three parameters documented). Description adds no additional meaning beyond schema, baseline score 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?

Description clearly states the verb 'evaluate', the resource 'prompt or text against ThinkNEO guardrail policies', and the context 'before sending it to an AI provider'. It distinguishes from siblings like thinkneo_policy_evaluate and thinkneo_detect_injection by focusing on guardrail policies.

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 'before sending it to an AI provider' provides clear usage context. However, no explicit guidance on when not to use or mention of alternatives among siblings, which are numerous.

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 reveals important behaviors: score validity of 30 days, generation of a public badge URL, and requiring authentication. Annotations are minimal (no readOnly, no destructive hints), so the description provides meaningful disclosure beyond structured fields.

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, uses clear language, and front-loads the core purpose. Every sentence adds value without redundancy.

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

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

For a tool evaluating a trust score, the description covers input (org_name), output components (score, breakdown, badge, recommendations), temporal constraint (30-day validity), and extra output (badge URL). Given the presence of an output schema for return details, the description is complete.

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

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

With only one parameter (org_name) and 100% schema description coverage, the description correctly adds no additional parameter-level insight. Baseline 3 applies as the schema already documents the parameter completely.

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

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

The description clearly identifies the tool's purpose: evaluating an organization's AI Trust Score across 10 named dimensions. The verb 'evaluate' and resource 'trust score' are specific and distinct from sibling tools, which cover auditing, compliance, costing, 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 outlines what the tool does and what it returns (score, breakdown, badge, recommendations), but does not explicitly state when to use it instead of alternatives or what prerequisites are needed beyond authentication. The context is clear for an agent to infer appropriate 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?

Annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false) already clearly indicate this is a safe, read-only operation. The description adds the context of 'from the ThinkNEO gateway' but no additional behavioral traits beyond what annotations provide, so a 3 is appropriate.

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 with the core purpose ('Check AI budget status'). It contains no redundant words and all information is relevant.

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 low complexity (one optional parameter, output schema present), the description is sufficiently complete. It mentions three key data elements (spend vs limit, forecast, chargeback). The absence of authentication context is acceptable given readOnlyHint 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?

The input schema has one parameter with a description (100% coverage), so the baseline is 3. The tool description does not add any meaning beyond the schema for this parameter, and no new parameter details are provided.

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

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

The description clearly states the action ('Check') and the resource ('AI budget status') with specifics like spend vs limit, forecast, and chargeback. It differentiates from siblings like thinkneo_billing_status and thinkneo_check_spend by including forecast and chargeback, but does not explicitly name alternatives.

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 explicit guidance on when to use this tool versus alternatives such as thinkneo_billing_status or thinkneo_check_spend. The context of 'budget status' implies a specific use case, but no when-not-to-use or alternative recommendations are given.

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

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

Annotations (readOnlyHint, idempotentHint, destructiveHint) already indicate safe read operation. Description adds value by detailing what is retrieved (framework coverage, governance assessments) without contradicting annotations. No additional behavioral traits need 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?

Single sentence of 15 words efficiently conveys all necessary information. No redundant or extraneous content. Front-loaded with the core action 'Get compliance status'.

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 2 optional parameters, output schema exists, and the tool is a simple status retrieval, the description is sufficient. It covers what the tool returns (framework coverage and governance assessments), though could mention that output schema details the 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 covers 100% of parameters with descriptions and defaults. Description does not add meaning beyond schema; it mentions frameworks but not workspace or default behavior. Baseline score of 3 is appropriate given high schema coverage.

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 retrieves compliance status, listing specific frameworks (EU AI Act, ISO 42001, NIST AI RMF, SOC 2) and governance assessments. It uses a specific verb (Get) and resource (compliance status), distinguishing it from siblings like thinkneo_compliance_generate which creates reports.

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. Siblings like thinkneo_compliance_generate, thinkneo_check_policy, and thinkneo_evaluate_guardrail exist, but description doesn't specify use cases, prerequisites, or when not to use this 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 declare readOnlyHint=true and idempotentHint=true, so the safety profile is clear. The description adds the Datadog analogy and authentication requirement, but does not disclose any side effects, limitations, or additional behavioral traits beyond what annotations provide. It neither contradicts nor significantly enhances transparency.

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

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

The description is three sentences, front-loaded with the purpose, followed by a list of included metrics and a helpful analogy. Every sentence earns its place without redundancy or 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 tool has one optional parameter, read-only annotations, and an output schema (exists but not shown), the description provides a comprehensive overview of what the dashboard includes. It could mention the output format, but the output schema fills that gap. Slightly incomplete regarding the structure of the dashboard, but sufficient.

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

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

Schema description coverage is 100% with a clear description of the 'period' parameter ('1h', '24h', '7d', '30d'). The tool description adds no additional parameter information, so the baseline of 3 is appropriate because the schema already does the heavy lifting.

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 an agent observability dashboard with aggregated metrics, using the verb 'Get' and specific resource. It lists the included metrics (sessions, cost, etc.) which helps distinguish it from sibling dashboard tools like thinkneo_sla_dashboard or thinkneo_verification_dashboard, though it doesn't explicitly differentiate them.

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

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

The description does not provide guidance on when to use this tool versus alternatives. It only states what it does, without mentioning when not to use it or suggesting other tools for specific needs (e.g., detailed traces). There is no explicit context 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?

Adds context beyond annotations: describes immutable nature, SHA-256 hash for tamper detection, authentication requirement. Annotations already indicate read-only/idempotent, so description enriches but doesn't contradict.

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, front-loaded with purpose, second sentence details contents, third a tagline. Efficient but tagline could be trimmed.

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?

Output schema exists so return not needed. Lacks mention of error conditions or that claim must exist and be verified. Adequate but not 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?

Parameter description matches schema (UUID of claim). Schema coverage 100% so baseline 3; description adds no new semantics 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?

Describes retrieving an immutable proof record for a verified claim, listing included components (original claim, evidence, verifier identity, proof hash). Clearly distinguishes from siblings like register_claim or verify_claim.

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 verified claims and requires authentication, but no explicit when-to-use or when-not-to-use guidance compared to 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description need not restate safety. It adds 'requires authentication,' which is useful but does not disclose other traits like data freshness, caching, or response size.

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 filler. First sentence states the core function, second enumerates the report contents. Efficient and front-loaded.

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

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

For a simple read-only report tool with an output schema, the description covers the main purpose, what data it shows, and the only prerequisite (authentication). No missing pieces.

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

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

With 100% schema coverage, the single parameter 'period' is already well-documented in the schema. The description adds no extra meaning beyond what's in the schema, so baseline score is appropriate.

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

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

The description clearly states the tool retrieves an AI cost savings report and lists specific metrics it shows (requests, costs, savings, breakdowns), distinguishing it from related sibling tools like thinkneo_usage or thinkneo_billing_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?

Only basic requirement (authentication) is mentioned. No guidance on when to use this tool over alternatives, such as thinkneo_usage or thinkneo_get_budget_status, or what context warrants a savings report.

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, idempotentHint=true, destructiveHint=false. Description adds authentication requirement and details on output components, which is useful context beyond annotations.

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

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

Two concise sentences: first states the core action, second enumerates return data. No unnecessary words, well-structured for scanning.

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

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

Given low complexity (1 param, no enums, output schema exists), description covers purpose, return components, and authentication. Could mention typical use cases but 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?

Only one parameter with 100% schema description coverage; tool description adds no additional meaning or examples 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?

Description clearly states 'Retrieve the full trace for an agent session' and lists specific return components (timeline, metadata, cost, duration, alerts), distinguishing it from sibling tools like thinkneo_start_trace and thinkneo_end_trace.

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 avoid this tool versus alternatives. Implicit context from sibling names, but description lacks exclusions or usage 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds 'No authentication required,' which is beyond annotations. It does not cover error conditions or idempotency details, but the added disclosure is valuable.

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: purpose/returns, embed usage, and auth. No wasted words, front-loaded with the core action.

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

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

For a simple read-only tool with one parameter and an output schema, the description covers purpose, return values, result usage, and authentication. No obvious gaps.

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

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

Schema coverage is 100% for the single parameter report_token. The description repeats 'by report token' but does not add meaning beyond the schema's description. Baseline 3 is appropriate.

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

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

The description clearly states the tool retrieves a public AI Trust Score badge using a report token, listing returned fields (organization name, score, badge level, validity period) and usage (embed URL). This distinguishes it from siblings like evaluate_trust_score by emphasizing 'public' and 'no 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 implies use after a trust score evaluation (requires report_token) but does not explicitly state when to use this vs alternatives like evaluate_trust_score or verify_claim. No exclusion criteria or alternative recommendations 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 indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which cover the safety profile. The description adds that it lists 'active alerts' but does not disclose additional behavioral traits such as pagination, rate limits, or response format. With annotations present, the bar is lower, but no extra context is provided.

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

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

The description is a single sentence of 14 words, front-loaded with the key action and resource. It is concise and contains no unnecessary information.

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

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

Given the tool's simplicity (list with two optional parameters and an output schema), the description is sufficiently complete. However, it could mention default behavior when no filters are applied, but the schema defaults cover that implicitly. The output schema is present, so return values are documented.

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% (both severity and workspace have descriptions). The tool description does not add any meaning beyond what the schema already provides. Baseline score 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 verb 'List' and the resource 'active alerts' for specific categories (budget, policy, SLA, security) from the ThinkNEO gateway. It effectively distinguishes from sibling tools that target specific alert types or statuses.

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. For example, it could mention that detailed budget or SLA status might be obtained via sibling tools like thinkneo_get_budget_status or thinkneo_sla_status.

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 (all false), description discloses auto-calculation of value from baseline cost and ROI tracking. However, does not specify whether logging is append-only or overwrites, and no mention of 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?

Three sentences plus example, front-loaded with purpose. Efficient, no redundant information.

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

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

Given output schema exists and parameters are documented, description adequately covers the tool's purpose and key behavior. Minor gap: does not clarify if logging is idempotent or if previous entries are overwritten.

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

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

Schema covers 100% of parameters with descriptions. Description adds an illustrative example but does not provide new parameter-level details 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?

Description states tool logs business decisions with cost/value tracking, and provides a concrete example (support-bot). Clearly distinguishes from siblings like thinkneo_log_event (generic logging) and thinkneo_decision_cost (cost 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 use when recording a decision with cost/value, but does not explicitly state when to use vs alternatives or when not to use. Lacks guidance on exclusion criteria or alternative tools.

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

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

The description adds that authentication is required and discloses return values (event_id, running session cost). Annotations already indicate non-destructive and non-idempotent behavior, so the description complements them well.

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 action, and contains no redundant information. Every part 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?

The description covers return values and authentication. Given that an output schema exists and schema documentation is complete, it is mostly adequate. Could mention the relationship to thinkneo_start_trace and thinkneo_end_trace for fuller 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?

Schema documentation covers all parameters at 100%, so the description adds minimal value. It lists event types for the event_type parameter, but does not elaborate on other 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 it logs events within an active agent trace, lists supported event types, and mentions return values. However, it does not differentiate from sibling tools like thinkneo_log_decision, 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?

The description notes authentication is required but does not specify when to use this tool versus alternatives, nor does it mention 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?

Annotations show readOnlyHint=false and destructiveHint=false, indicating a non-destructive write. The description adds that if estimated_impact_usd is omitted, a default is calculated from severity—a useful behavioral detail. However, it doesn't discuss idempotency or persistence, which would improve transparency further.

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 core purpose and then adding quantification, examples, and a default behavior note. Every sentence adds value, and there is no unnecessary repetition or 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?

The description covers when and why to use the tool, key parameters, and an important behavioral detail (default impact calculation). Since an output schema exists, not describing the return value is acceptable. However, it could mention whether log entries are immutable or if duplicate events are allowed, but this is sufficient for a logging tool.

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

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

Schema coverage is 100%, so parameters are individually documented. The description enhances this by explaining the overall purpose (logging avoided risks) and the automatic impact calculation, which clarifies the role of estimated_impact_usd and severity. The examples in the description also help understand the risk_type 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 logs avoided risk events, quantifies dollar impact, and gives specific examples (PII leak, injection, policy violation). It distinguishes from other logging tools like thinkneo_log_decision or thinkneo_log_event by focusing on governance-layer risk avoidance.

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 to use this tool when a risk event is blocked or avoided by the governance layer. It doesn't mention when not to use or contrast with alternatives, but the context is clear enough for an agent to select it over other logging 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?

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds no behavioral details beyond confirming a read-only check, so it provides minimal additional transparency.

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

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

The description is a single, well-structured sentence with no unnecessary words. It is appropriately concise for such a simple tool.

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, and the presence of an output schema and clear annotations, the description fully covers what the tool does without requiring additional detail.

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, so the description cannot add meaning beyond the input schema. Per guidelines, a baseline of 4 is appropriate for zero-parameter tools.

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

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

The description uses a specific verb ('Check') and identifies the resource ('connector grants and secrets status'). It clearly distinguishes from sibling tools like thinkneo_rotate_key, which performs a different action.

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 what the tool does but provides no guidance on when to use it versus alternatives. With many siblings, explicit context would be helpful, but the purpose is self-explanatory.

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, and destructiveHint. The description adds 'with live metrics context' but does not elaborate on behavior beyond confirming it is non-destructive and idempotent.

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 8 words, capturing the essential function. Every word adds value, and it 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?

For a simple one-parameter tool with an output schema (not shown here), the description is complete enough. It could mention that optimizations are suggested, not applied, but the annotations imply read-only.

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 schema description for 'prompt' is clear. The description adds no new parameter meaning beyond noting live metrics context.

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

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

The description clearly states the tool's function: analyze a prompt and suggest optimizations. The verb 'analyze' and resource 'prompt' are specific. No sibling tool performs prompt optimization, making it distinct.

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 optimizing prompts, and the tool name reinforces this. However, it does not explicitly state when to use or avoid this tool compared to siblings.

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

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds value by specifying real-time nature and the specific metrics (latency, error rates, availability). It also notes no authentication required, which is useful behavioral context.

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

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

The description is concise: two sentences conveying the essential information. No fluff, and the most important details (real-time status, no auth) are front-loaded.

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

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

Given the tool's simplicity (2 optional parameters, read-only, idempotent, output schema exists), the description covers purpose, usage, and behavior comprehensively. No gaps remain for an agent to misinterpret.

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

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

Schema description coverage is 100%, so the schema already documents both parameters adequately. The description does not add meaning beyond what the schema provides (e.g., list of providers and optional workspace context). Baseline score of 3 is appropriate.

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

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

The description clearly states the tool's purpose: getting real-time health and performance status of AI providers routed through ThinkNEO. It specifies the metrics shown (latency, error rates, availability), making it distinct from sibling tools like thinkneo_sla_status or thinkneo_get_observability_dashboard.

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

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

The description explicitly states no authentication is required and includes parameter-level guidance (list of specific providers and default behavior). It doesn't explicitly say when not to use it, but given the clarity of the purpose, usage is well implied.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds value by explaining the two operational modes (index listing vs. content retrieval) and what kind of data is stored, which is useful context beyond annotations.

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

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

Three sentences, front-loaded with purpose, no fluff. Each sentence adds distinct value: purpose, mode distinction, and use case.

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 only one optional parameter and rich annotations, the description fully explains both use cases and the content type. Output schema exists but is not needed for completeness here.

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 essentially echoes the schema's parameter description. It adds concrete filename examples, which is helpful but not essential. Baseline 3 is appropriate.

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

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

The description clearly states it reads memory files, distinguishes between listing the index (no argument) and retrieving a specific file (with filename argument), and contrasts with sibling write_memory 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?

It explains when to use the tool: 'to access project context, user preferences, feedback, and reference notes.' No explicit exclusions or alternative tools mentioned, but the context is clear.

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

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

The description discloses authentication requirements and the verification process. Annotations indicate it is mutating but not destructive or idempotent. No contradictions. Adds value beyond annotations by explaining the verification flow.

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

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

The description is three concise sentences, front-loading the core purpose and adding essential context (verification, claim_id, authentication) without 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 tool's complexity (7 params, 3 required, output schema, annotations), the description is adequate. It covers purpose, verification, and authentication. Could mention that verification is asynchronous or that claim_id is needed for later verification, but it's still complete enough.

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

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

Schema description coverage is 100%, so baseline is 3. The description does not add parameter-specific details beyond what the schema provides, but the overall context (Outcome Validation Loop) adds some 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 registers an action claim from an AI agent, specifies the action (declaring performed action) and that ThinkNEO verifies it. It distinguishes from sibling tools like thinkneo_verify_claim by focusing on registration and returning a claim_id for tracking.

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 context that the tool is part of the Outcome Validation Loop, implying it is used when an agent claims an action. However, it does not explicitly mention when not to use it or suggest alternative tools (e.g., thinkneo_verify_claim for subsequent verification).

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description's addition of 'No authentication required' and the list of return values provide further 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?

Two sentences front-load the purpose and source, followed by return items and authentication status. Every sentence adds value with no redundancy.

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

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

Given the simplicity of a lookup tool (1 required param, good annotations, output schema present), the description covers the main return items and auth requirements, though it omits potential error cases like missing package names.

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% for the single parameter 'name', with examples provided. The tool description does not add extra parameter semantics beyond what the schema already offers, meeting the baseline of 3.

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

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

The description clearly states this tool 'Get full details for an MCP server package' and lists specific returned items (readme, tools list, version history, etc.), distinguishing it from sibling registry tools like search, install, publish, and review.

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 comprehensive info on a specific package and notes 'No authentication required', but does not explicitly contrast with siblings like thinkneo_registry_search for searching or thinkneo_registry_install for installation.

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 tracking of downloads and no authentication required. Annotations provide no safety hints (all false), so description carries the burden and adds value with these behavioral notes.

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 covering purpose, output, side effect, and access. No fluff or repetition. Front-loaded with key action.

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

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

Simple tool with output schema; description covers all necessary aspects: what it does (returns config), side effect (tracks download), access (no auth). Parameter details in schema are sufficient.

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

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

Schema coverage is 100% and schema descriptions are complete. Description does not add new meaning beyond what the schema already provides for the two 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?

Description clearly states 'Get installation config for an MCP server' – a specific verb+resource. It distinguishes from sibling registry tools by noting it returns ready-to-use JSON config for multiple clients and tracks downloads.

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

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

Description implies usage context (when installing from Marketplace) but does not explicitly state when to use this vs. registry_search or registry_get. No alternatives 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?

Annotations indicate readOnlyHint=false and destructiveHint=false, but the description adds valuable behavioral details: endpoint validation (initialize + tools/list), automated security scan (secrets, injection patterns), security score (0-100), and version history storage. It also mentions authentication. However, it does not clarify behavior on re-publish (update vs. duplicate), which is a 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 two sentences but contains redundancy: 'Validates the endpoint by calling initialize and tools/list...' is repeated almost verbatim. It is front-loaded with the main purpose, but the repetition wastes space. Could be more 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 the tool's complexity (10 params, 4 required, with output schema), the description covers the core process (validation, security scan, storage). It mentions authentication and the overall workflow. However, it lacks edge-case details (e.g., what happens on duplicate name, any retention limits). Output schema exists, so return values are not required.

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 does not add meaningful parameter-level information beyond what the schema already provides. It restates that four parameters are required but does not explain, for example, how endpoint_url is used in validation. No additional semantics are provided.

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

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

The description clearly states the tool publishes an MCP server to the ThinkNEO Marketplace. It specifies the verb (publish), resource (MCP server), and destination, distinguishing it from sibling registry tools like thinkneo_registry_get, thinkneo_registry_search, 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 does not provide guidance on when to use this tool versus alternatives. It mentions authentication required but does not specify prerequisites, nor does it compare to other registry tools (e.g., when to install vs. publish). The agent receives no context about 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?

Beyond annotations (idempotent, non-destructive), the description adds that reviews are per-user per-package and update on repeat (consistent with idempotent hint), requires authentication, and affects average rating. This adds valuable behavioral context beyond structured metadata.

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 mostly concise but redundantly repeats 'One review per user per package (updates on repeat)' twice. While the structure is clear, the redundancy reduces 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 moderate complexity, the description adequately covers purpose, behavior (idempotent updates), constraints (authentication, rating scale), and impact (average rating). It doesn't explore all edge cases but is sufficient for an agent to use 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%, and the description adds minimal extra meaning: it reiterates rating range and optional comment with max chars (already in schema). No additional semantics beyond schema, so baseline 3 is appropriate.

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

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

The description clearly states the tool rates and reviews MCP servers, distinguishing it from sibling tools like thinkneo_registry_get, install, publish, and search. It specifies the resource (MCP server in ThinkNEO Marketplace) and action (rate and review).

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 context: to submit or update a review for a package. It mentions authentication requirement and that ratings affect search results. However, it does not explicitly mention when not to use or alternatives for viewing reviews, but the context is strong.

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

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds value by detailing return fields (name, description, tools count, rating, downloads, verified badge) and the fact that no authentication is required, which goes beyond what annotations provide.

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 succinct sentences. The first sentence serves as a clear tagline, and the second provides key details about search facets and return fields. Every sentence is purposeful with no 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 existence of an output schema, the description does not need to explain return values. It covers the tool's purpose, search dimensions, and key constraints (no auth). The metaphor 'npm for MCP tools' sets appropriate context. All important aspects are addressed.

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

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

Schema description coverage is 100%, so the schema already documents all five parameters. The description summarizes search dimensions (keyword, category, rating, verified status) but does not add significant meaning beyond the schema. Baseline of 3 is appropriate.

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

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

The description uses a specific verb 'Search' and clearly identifies the resource as the 'ThinkNEO MCP Marketplace.' It lists search dimensions (keyword, category, rating, verified status) and distinguishes itself from sibling tools like thinkneo_registry_get and thinkneo_registry_install by focusing on discovery.

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 for when to use the tool (discovering MCP servers and tools) and mentions no authentication required. However, it does not explicitly state when not to use it or name alternative tools, which would help in distinguishing from similar registry 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?

Annotations already declare destructiveHint=true, so the description confirms destructive behavior. However, it does not elaborate on what rotation entails (e.g., key invalidation, transition period), missing an opportunity to add value 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?

One sentence, no wasted words. Conciseness is good, though slightly more detail would not hurt.

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