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Submit conversation feedback

submit_conversation_feedback

Submit a concise, redacted, task-specific product issue to agentcentral only after the user explicitly asks to send feedback and confirms the packet. Include only the minimum redacted evidence needed to investigate. Do not request or submit conversation history, prior-turn arrays, or raw transcripts. Do not submit API keys, bearer tokens, Connector URLs, refresh tokens, buyer names, addresses, phone numbers, emails, order IDs, tracking IDs, gift messages, full tool payloads, or unrestricted seller metrics. Free-text ASINs are aliased automatically; use related_asins only when specific ASINs are necessary for debugging. This creates a product feedback item for human review, not a support ticket and not model training data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
evidenceNoSpecific redacted evidence for review: tool names, freshness dates, short error fragments, or observed contradictions. Do not include raw payloads.
severityNo
user_goalNoBrief task goal, when needed to understand the issue. Do not include conversation history, prior-turn arrays, or raw transcripts.
user_requestYesThe user's explicit request to send this product-quality feedback to agentcentral.
issue_summaryYesConcise, task-specific product issue with only the minimum redacted details needed to investigate. Do not include conversation history, prior-turn arrays, or raw transcripts.
privacy_notesNoShort note about sensitive details that were omitted, generalized, or redacted from the case packet.
related_asinsNoOptional explicit ASINs needed for product debugging. ASINs in free text are aliased automatically.
client_contextNo
issue_categoryYesNeutral classification of the issue; do not assign blame.
agent_confidenceNo
expected_behaviorNo
observed_behaviorNo
reproduction_notesNo
agentcentral_tools_usedNoagentcentral tool names involved in the issue, if known.
relevant_error_messagesNoShort error messages only. Do not include raw payloads, credentials, Connector URLs, or transcripts.
submission_acknowledgementYesMust be true. Confirms the user reviewed the summary and explicitly asked to submit it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.8/5.0
Behavior5/5

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

Annotations only declare the safety profile (write, openWorld, non-destructive); the description adds destination (agentcentral), downstream handling (creates a product feedback item for human review, not training data), and extensive redaction rules. It goes well beyond what the structured annotations convey and contradicts nothing.

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

Conciseness4/5

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

Front-loads the action and its precondition in the first sentence, then layers constraints. It is dense and long, but nearly every clause carries actionable redaction or routing guidance rather than filler.

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

Completeness5/5

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

For a 16-parameter submission tool with no output schema, the description supplies the prerequisites, privacy boundaries, field-level hints, and the nature of the created artifact. Nothing critical to invoking it correctly appears to be missing.

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

Parameters4/5

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

With 63% schema coverage across 16 parameters, the description adds real meaning: it explains the evidence field's redaction intent, the automatic aliasing of free-text ASINs and when to use related_asins, and that issue_category must be neutral. It stops short of describing several other fields (severity, agent_confidence, reproduction_notes), so it complements rather than fully covers the schema.

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

Purpose5/5

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

States a specific verb (submit) plus resource (a redacted, task-specific product issue sent to agentcentral), and draws a clear line from every sibling, which are all read-oriented get_* tools. An agent can tell instantly that this is the single write/submission tool in the set.

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

Usage Guidelines5/5

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

Gives an explicit precondition ('only after the user explicitly asks to send feedback and confirms the packet') and explicit exclusions ('not a support ticket and not model training data'). It also states what not to do (no conversation history, no raw transcripts), leaving little to inference.

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

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