MCP CPG Human in the Loop (HITL)

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

With no annotations, the description discloses that the tool returns current status and an answer when available, and implies a polling behavior. It does not mention side effects, but the behavior is clear.

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.

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 poll tool with one parameter and no output schema, the description sufficiently covers purpose, input expectation, and return value. It does not explain how to obtain the ticket_id from sibling tools, but that is implicit.

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 already describes the ticket_id parameter with format. The description adds no additional 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 uses a specific verb ('Poll') and resource ('ticket previously lodged'), and lists the ticket types (RFQ, terms request, escalation), clearly distinguishing from sibling tools that create tickets.

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 after submitting a ticket via sibling tools, but does not explicitly state when not to use it or provide alternatives.

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

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

With no annotations, the description carries full burden. It discloses that the tool emits an ACM-451 ESCALATE event and returns a ticket ID. However, it lacks details on authorization, latency, error states, or what happens to the escalated matter (e.g., human response time, callback expectations).

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 with zero waste. It front-loads the primary purpose and includes key behavioral details (event emission, return value).

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

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

Given the tool's complexity (5 params, no output schema), the description adequately covers the input context, return value, and the event emitted. It could mention asynchronous nature or human review process, but it is fairly complete for a straightforward escalation 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%, so the baseline is 3. The description does not add any additional meaning beyond what is already in the schema. Parameters like context have clear descriptions in the schema, and the tool description does not elaborate further.

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: handing a matter to human review. It specifies the emitted event (ACM-451 ESCALATE) and the return value (ticket ID). While it distinguishes from siblings by mentioning non-deterministic resolution and referencing check_rfq_status for polling, it does not explicitly differentiate from other siblings like request_terms or submit_rfq.

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 when to use: for matters that cannot be resolved deterministically. It also implies the follow-up action of polling via check_rfq_status, which is a sibling tool. It does not explicitly state when not to use or provide alternatives for the optional related_ticket parameter.

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

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

No annotations are provided, so the description carries full burden. It discloses that a ticket is created and returns a ticket ID for polling, but lacks details on authorization, processing time, or failure modes.

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 purpose, and contains no unnecessary information. Every word 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?

The description explains the human-in-the-loop process and polling mechanism. With 5 parameters and no output schema, it covers usage context adequately, though it omits expected response time or error handling.

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 detailed descriptions for all 5 parameters. The description adds context about the return value but does not enhance parameter understanding 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 is for asking commercial or procedural questions that are answered by a human. It distinguishes from siblings: check_rfq_status (polling), escalate, submit_rfq (submission).

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 defines when to use: when a human answer is needed. It does not explicitly exclude cases, but the sibling tools provide context for alternatives.

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

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

Discloses that the tool returns a ticket ID for polling, that a human responds (no automation), and that it optionally references GTIN and market codes. Without annotations, the description carries full burden for behavioral disclosure and provides adequate insight.

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

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

Three efficient sentences: first states purpose, second adds key behavioral trait, third lists optional parameters. No fluff, front-loaded with main 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?

No output schema, but description explains return value (ticket ID for polling). Covers all essential aspects: name, purpose, behavioral info, optional parameters, and follow-up tool. Complete for the complexity level.

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 baseline is 3. Description adds value by specifying that GTIN should be resolved on mcp.cpgknowledgegraph.ai and market uses SM-ECO-10060 codes, beyond the schema descriptions.

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

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

Clear verb+resource: 'Lodge a request-for-quotation with GreenCore Solutions Corp.' Differentiates by stating human review and no order decision, and references sibling tool check_rfq_status for polling.

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

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

Explicitly states that a human reviews every ticket and no order is decided by this tool, clarifying when to use it (for quote requests, not orders). Mentions check_rfq_status for polling but doesn't contrast with escalate or request_terms, though context is clear enough.

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