ThinkNEO Control Plane

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

The description adds valuable behavioral context beyond annotations: it specifies the free-tier nature, lists the types of patterns checked (prompt injection, PII like credit card numbers, CPF, SSN, email, phone, passwords), and notes no authentication required. Annotations cover read-only and idempotent hints, but the description enhances understanding of the tool's scope and limitations.

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 front-loaded and concise, with three sentences that efficiently convey purpose, scope, and key behavioral traits without wasted words, making it easy for an AI agent to parse quickly.

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

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

Given the tool's moderate complexity, rich annotations (readOnlyHint, idempotentHint), and the presence of an output schema, the description is complete enough. It covers the tool's function, safety focus, and authentication details, leaving output specifics to the schema.

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

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

Schema description coverage is 100%, so the input schema fully documents the 'text' parameter. The description adds no additional parameter details beyond what the schema provides, such as examples or format specifics, meeting the baseline for 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?

The description clearly states the tool's purpose with specific verbs ('analyzes', 'returns') and resources ('text for prompt injection patterns and PII'), explicitly distinguishing it from siblings by focusing on free-tier safety checks rather than policy, spending, or compliance tools.

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

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

It provides clear context for when to use this tool ('Free-tier prompt safety check') and mentions 'No authentication required', but does not explicitly state when not to use it or name alternatives among siblings like thinkneo_check_policy or thinkneo_evaluate_guardrail.

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 authentication requirement beyond annotations. Annotations already establish readOnly/idempotent traits, so description carries lower burden. Does not elaborate on response semantics (e.g., boolean vs policy object), but output schema exists to cover this.

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

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

Two sentences with zero waste. Primary purpose front-loaded in first sentence; constraint (authentication) follows. No redundant or filler content.

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?

Adequate for a read-only policy check with complete schema coverage and existing output schema. Captures purpose and auth requirements. Minor gap: does not clarify behavior when optional parameters are null (wildcard check vs error).

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%, establishing baseline 3. Description references the parameter concepts ('specific model, provider, or action') but does not add semantic clarifications beyond the schema descriptions (e.g., no syntax guidance, no enum values, no inter-parameter relationships).

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?

Clear verb ('Check') + resource ('governance policies') + scope ('workspace'). Specifies what is being validated (model/provider/action allowance). Distinguishes implicitly from siblings like check_spend (budget) and evaluate_guardrail (runtime content filtering) by specifying 'governance policies', though lacks explicit sibling contrast.

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?

States prerequisite ('Requires authentication') and implies usage context ('Check if... is allowed' suggests pre-invocation validation). However, lacks explicit when-to-use guidance versus alternatives like evaluate_guardrail or get_compliance_status, and does not specify when all optional parameters should be null vs populated.

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

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

Annotations declare read-only/idempotent safety, allowing the description to focus on output structure ('cost breakdown by provider, model, and time period') and critical runtime requirements ('Requires authentication'). These additions provide valuable context 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?

Three sentences with zero waste: action/scope first, return value second, auth requirement third. Every sentence earns its place and the description is appropriately 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 presence of an output schema and comprehensive input annotations, the description provides sufficient high-level context about the return structure and authentication needs without duplicating schema details.

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 description coverage, the structured fields already document all parameters. The description mentions 'workspace, team, or project' which loosely maps to the workspace parameter and group_by options, but adds no syntax, format details, or semantic constraints 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 states a clear verb ('Check') and specific resource ('AI spend summary'), along with scope ('workspace, team, or project'). It implicitly distinguishes from siblings like thinkneo_get_budget_status (spend vs. budget) and thinkneo_check_policy (cost vs. compliance), though 'Check' is slightly less precise than 'Retrieve'.

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 provided on when to use this tool versus alternatives like thinkneo_get_budget_status or how it relates to cost management workflows. The description only states what the tool does, not when to invoke 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 declare readOnlyHint=true and idempotentHint=true, covering the safety profile. The description adds valuable operational context: it discloses the return structure ('risk assessment, violations found, and recommendations') and critical prerequisites ('Requires authentication') not present in 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 tightly constructed sentences with zero redundancy. The first sentence establishes the core action and timing, the second describes outputs, and the third states prerequisites. Every sentence earns its place with no filler.

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 (per context signals) and rich annotations, the description provides sufficient context: purpose, return value summary, and authentication requirements. Minor gap: could briefly mention the guardrail_mode default behavior, but completeness is strong for a 3-parameter evaluation 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?

With 100% schema description coverage, the schema adequately documents all three parameters (text, workspace, guardrail_mode). The description implies the text parameter ('Evaluate a prompt or text') but does not add semantic meaning beyond what the structured schema already provides, warranting the baseline score.

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 ('Evaluate') and clearly identifies the resource (prompt/text against ThinkNEO guardrail policies). It distinguishes from siblings like 'check_policy' by specifying this evaluates content pre-submission ('before sending it to an AI provider') rather than checking policy configuration.

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 temporal context ('before sending it to an AI provider') indicating when to use it, which implies the workflow position. However, it lacks explicit guidance on when NOT to use this versus siblings like 'thinkneo_check_policy' or alternative approaches.

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 establish readOnlyHint=true, so the description adds value by disclosing 'Requires authentication' (auth needs) and clarifying the computational nature of the data ('projected overage'). It does not contradict annotations, though it could further describe caching behavior or rate limits.

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

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

Three distinct sentences efficiently distribute information: purpose (sentence 1), specific outputs (sentence 2), and prerequisites (sentence 3). Minor overlap exists between 'budget utilization' and 'spend vs limit,' but each sentence advances the agent's understanding without redundancy.

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

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

Given the tool's low complexity (single parameter, read-only operation), presence of an output schema, and complete schema coverage, the description provides sufficient context. The mention of authentication requirements compensates for the lack of annotation coverage on auth.

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 description coverage, the parameter 'workspace' is fully documented in the schema itself ('Workspace name or ID'). The description provides baseline adequacy by not duplicating this information, earning the standard score 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 uses a specific verb ('Get') with a clear resource ('budget utilization and enforcement status') and scope ('for a workspace'). It distinguishes from sibling thinkneo_check_spend by detailing specific outputs like 'enforcement status,' 'alert thresholds,' and 'projected overage,' though it doesn't explicitly name the sibling for comparison.

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

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

The description implies usage by detailing what it returns ('spend vs limit, alert thresholds'), allowing an agent to infer when this tool is appropriate. However, it lacks explicit guidance on when to use this versus thinkneo_check_spend or other siblings, and doesn't state exclusion criteria.

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

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

Annotations already establish readOnlyHint=true and idempotentHint=true. The description adds value by stating 'Requires authentication' (not in annotations) and previewing output content ('governance score, pending actions, and compliance gaps'). However, it omits rate limits, caching behavior, or framework-specific behaviors.

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 total, front-loaded with the core action ('Get compliance...'), followed by output preview and auth requirement. No redundant or wasted language; each sentence provides distinct information not available in structured fields.

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 (not shown but indicated in context signals) and comprehensive input schema, the description appropriately focuses on purpose and operational requirements rather than replicating return value documentation. It could improve by noting the framework parameter's default value.

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 description coverage, the schema fully documents both parameters (workspace and framework) including valid enum-like values for framework. The description adds no parameter-specific guidance, meeting the baseline expectation for well-schematized tools.

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

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

The description clearly states the tool 'Get[s] compliance and audit readiness status for a workspace' with specific verbs and resource types. It implicitly distinguishes from siblings like check_spend, check_policy, and get_budget_status by focusing on governance/compliance domain, though it doesn't explicitly contrast with similar monitoring tools like evaluate_guardrail.

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

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

The description provides no guidance on when to use this tool versus alternatives. It does not clarify the distinction between 'compliance status' (this tool) and 'policy checks' (thinkneo_check_policy) or 'guardrail evaluation' (thinkneo_evaluate_guardrail), leaving the agent to infer appropriate 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?

Adds valuable behavioral context beyond annotations: specifies 'active' alerts (temporal scope), enumerates content categories included, and states 'Requires authentication.' Annotations already declare readOnlyHint=true, so the description appropriately focuses on content scope and auth requirements rather than safety.

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 totaling 21 words. Front-loaded with core purpose first, followed by content scope, then authentication requirement. Zero redundancy—every sentence provides distinct information not available in structured fields.

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?

Appropriate for complexity level: output schema exists (covering return values), input schema is fully documented, and description covers auth requirements and content filtering. Minor gap regarding pagination behavior or default sorting, but 'limit' parameter implies pagination support.

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 3 parameters fully documented with types, ranges, and valid values). Description does not explicitly discuss parameters, but baseline 3 is appropriate when schema carries the full semantic load.

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?

Specific verb ('List') + resource ('active alerts and incidents') + scope ('for a workspace'). Distinguishes from siblings (check_policy, check_spend, evaluate_guardrail, provider_status) by explicitly enumerating the alert types it aggregates: 'budget alerts, policy violations, guardrail triggers, and provider issues.'

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 through enumeration of included alert categories (suggesting it's an aggregate view), but lacks explicit when-to-use guidance versus the specific check/evaluation sibling tools. No prerequisites or exclusions stated beyond authentication.

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

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

Annotations declare readOnlyHint=true; description adds valuable behavioral context including 'real-time' data nature, specific metrics returned (latency, error rates, availability), and authentication requirements. No contradictions with annotations. Could enhance further with rate limit or caching details.

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 tightly crafted sentences with zero waste. Front-loaded with core purpose ('Get real-time health...'), followed by specific metrics, then auth requirements. Every sentence earns its place with no redundant or filler content.

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 100% schema coverage, existing output schema, and readOnly annotations, the description adequately covers tool purpose, return data characteristics, and access requirements. Complete for a monitoring tool of this complexity, though explicit mention of the 'all providers' default could strengthen it further.

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%, documenting both provider options (including the 'omit for all' behavior) and workspace context. Description provides general context about 'AI providers' and 'gateway' but does not add parameter-specific semantics beyond what the schema already provides. Appropriate baseline for 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 uses specific verb 'Get' with clear resource 'health and performance status of AI providers routed through the ThinkNEO gateway'. Explicitly distinguishes from siblings (budget/compliance/policy tools) by focusing on operational metrics like latency and availability.

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

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

Provides clear context that this is for monitoring provider health/performance vs financial or compliance concerns. Explicitly states 'No authentication required' which is valuable usage constraint. Lacks explicit 'when to use vs sibling X' guidance, though the functional distinction is clear.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the agent knows this is a safe, repeatable read operation. The description adds valuable context beyond annotations by explaining what types of content are stored ('project context, user preferences, feedback, and reference notes') and that they persist across sessions. It doesn't describe rate limits or authentication needs, but adds meaningful 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 efficiently structured in three sentences: first states the core purpose, second explains the two usage modes, third provides context about what types of memories are accessed. Every sentence earns its place with no wasted words.

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

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

Given the tool has comprehensive annotations (readOnlyHint, idempotentHint), 100% schema description coverage, and an output schema exists (so return values are documented elsewhere), the description provides complete contextual information. It explains the tool's purpose, usage patterns, and what types of data it accesses.

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 fully documents the single optional parameter. The description adds marginal value by explaining the behavioral difference when the parameter is omitted vs. provided, but doesn't add semantic details beyond what's in the schema. Baseline 3 is appropriate when schema 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's purpose with specific verbs ('read', 'returns') and resources ('Claude Code project memory files', 'MEMORY.md index', 'specific memory file'). It distinguishes from sibling tools by focusing on reading memory files rather than policy checks, budget monitoring, or writing operations.

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

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

The description provides explicit guidance on when to use this tool: 'Without arguments, returns the MEMORY.md index listing all available memories. With a filename argument, returns the full content of that specific memory file.' It also implicitly distinguishes from the sibling 'thinkneo_write_memory' by being a read operation.

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 idempotentHint: false (write operation, not idempotent). The description adds valuable behavioral context about authentication requirements not found in annotations. However, it omits consequences of the non-idempotent nature (duplicate submissions) and what happens after scheduling (e.g., confirmation 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?

Three sentences, zero waste. Front-loaded with the core action ('Schedule a demo...'), followed by parameter categorization, and closes with the critical auth constraint. Every sentence earns its place 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 presence of an output schema (not shown but indicated in context signals), the description appropriately omits return value details. For a 7-parameter scheduling tool, it covers the essential action and auth requirements, though mentioning the side effect (creating a request/ticket) would strengthen completeness given the idempotentHint: false annotation.

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 description coverage, the baseline is met. The description categorizes parameters as 'contact information and preferences,' which loosely maps to the schema fields, but does not add significant semantic detail, validation rules, or format guidance 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 uses specific verbs ('Schedule') and identifies the resource clearly ('demo or discovery call with the ThinkNEO team'). It effectively distinguishes from siblings, which are all read-only query operations (check_, get_, list_), while this is the sole booking/action tool.

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

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

Provides clear context that 'No authentication required' is needed to invoke this tool, which is critical usage information. While it lacks explicit 'when not to use' guidance, the singular nature of this scheduling tool among query-focused siblings makes the appropriate use case self-evident.

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, but the description adds valuable context beyond this: it specifies that it works without authentication and returns general info, which clarifies access requirements and data scope. It also lists the specific metrics returned (e.g., calls today, top tools used), enhancing behavioral understanding. No contradictions with annotations are present.

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 front-loaded with the core purpose in the first sentence, followed by specific details in a concise list. Every sentence adds value: the first states what it does, the second enumerates returned statistics, and the third provides authentication context. There is no wasted text, making it highly efficient and well-structured.

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

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

Given the tool's simplicity (0 parameters, read-only/idempotent annotations, and an output schema), the description is complete. It explains the purpose, usage context, behavioral traits, and output details (e.g., statistics like top tools used and estimated cost), which aligns well with the structured data. No gaps are present for this low-complexity tool.

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

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

The input schema has 0 parameters with 100% coverage, so the schema fully documents the lack of inputs. The description compensates by explaining that no parameters are needed and clarifies the tool's behavior (e.g., returns general info without authentication). This adds meaningful context beyond the schema, though it's not required for 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 tool's purpose with specific verbs ('Returns usage statistics') and resources ('ThinkNEO API key'), and distinguishes it from siblings by focusing on usage metrics rather than checks, policies, budgets, or other functions. It explicitly lists the specific statistics returned, making the purpose highly specific and differentiated.

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

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

The description provides clear context on when to use this tool: for retrieving usage statistics, including details like calls, limits, costs, and tier. It mentions it 'Works without authentication,' which is useful guidance. However, it does not explicitly state when not to use it or name alternatives among the sibling tools, such as for budget or compliance checks, which prevents a perfect score.

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 idempotentHint=true, and the description adds valuable context beyond this: it specifies filename constraints ('must end in .md and contain only lowercase letters...'), mentions path traversal blocking, and clarifies that it handles both writing and updating. This enriches behavioral understanding without contradicting annotations.

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

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

The description is front-loaded with the core purpose in the first sentence, followed by essential details like usage context, filename rules, and security note. Every sentence adds value without waste, making it efficient and well-structured for quick comprehension.

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 (write/update operation), rich annotations (readOnlyHint, idempotentHint), and the presence of an output schema, the description is complete. It covers purpose, usage, behavioral traits, and parameter context adequately, leaving no significant gaps for the agent to understand and invoke the tool correctly.

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

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

Schema description coverage is 100%, so the schema already documents both parameters fully. The description adds minimal extra meaning by reinforcing the filename format with examples and noting that content is 'markdown', but this is largely redundant with the schema. Baseline 3 is appropriate as the schema carries the primary burden.

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 specific action ('Write or update') and resource ('a Claude Code project memory file (.md)'), distinguishing it from sibling tools like 'thinkneo_read_memory'. It specifies the exact type of file and its purpose ('persist project context, user preferences, feedback, and reference notes across Claude Code sessions'), making the purpose unambiguous and 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 provides clear context for when to use this tool ('to persist project context... across Claude Code sessions') and includes a sibling tool ('thinkneo_read_memory') that serves as an alternative for reading. However, it does not explicitly state when not to use it or compare it to other write-related tools, which slightly limits guidance.

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