Mark

List Wrong Answers

list_wrong_answers

Read-onlyIdempotent

Lists wrong AI answers, newest seen first: ones members logged from any engine (including ones Mark doesn't check weekly), and competitor_instead ones the weekly check filed (source weekly_check). Each has a reason. Filter by status and buyer question. Does not change anything. Related: save_wrong_answer, get_buyer_question_answers, save_idea (wrongAnswerId).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_wrong_answers"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No	At most this many rows, newest first (default 25).
`status`	No	open (default), resolved, or all.	open
`question`	No	Active buyer question id, or its exact text.

Output Schema

Name	Required	Description	Default
`appUrl`	Yes
`wrongAnswers`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed6 schema fields changedOct 20, 2026

addedOutput schema / properties / wrongAnswers / items / properties / createdById / description
```
Added value: +"Null for weekly_check."
```
changedOutput schema / properties / wrongAnswers / items / properties / createdById / type
```
Previous value: -"string"New value: +[
+  "string",
+  "null"
+]
```

changedOutput schema / properties / wrongAnswers / items / properties / quote / description

Previous value: -"What the engine said, as the member pasted it."New value: +"What the engine said: as the member pasted it, or the whole answer for weekly_check."

addedOutput schema / properties / wrongAnswers / items / properties / reason

Added value: +{
+  "enum": [
+    "wrong_fact",
+    "competitor_instead",
+    "negative_framing",
+    "outdated",
+    "missing_citation",
+    "other"
+  ],
+  "type": "string"
+}

addedOutput schema / properties / wrongAnswers / items / properties / source

Added value: +{
+  "description": "weekly_check: the weekly check filed it because the answer named an active competitor and not the brand.",
+  "enum": [
+    "member",
+    "weekly_check"
+  ],
+  "type": "string"
+}

changedOutput schema / properties / wrongAnswers / items / required

Previous value: -[
-  "id",
-  "engine",
-  "prompt",
-  "quote",
-  "seenOn",
-  "note",
-  "question",
-  "market",
-  "createdById",
-  "createdAt",
-  "resolvedAt",
-  "resolvedById"
-]New value: +[
+  "id",
+  "engine",
+  "reason",
+  "source",
+  "prompt",
+  "quote",
+  "seenOn",
+  "note",
+  "question",
+  "market",
+  "createdById",
+  "createdAt",
+  "resolvedAt",
+  "resolvedById"
+]

AddedOct 8, 2026

TDQS

A4/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, and the sentence 'Does not change anything' largely restates those. It does add that every row carries a reason and that results are newest-first across two distinct provenance sources, which is modest but real context 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.

Conciseness4/5

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

The core statement is front-loaded and the trailing 'Related:' line is efficient routing signal. The parenthetical about what Mark does or doesn't check weekly is domain flavor that costs a few words but does convey why some answers may appear missing.

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?

With an output schema covering return shape, full annotation coverage, and 100% schema description coverage, the description supplies the remaining needed context: ordering, dual provenance of rows, presence of a reason field, and sibling routing. Nothing an agent needs to call it correctly is absent.

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

Parameters3/5

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

Schema coverage is 100%, so all three parameters including defaults, enum values and length bounds are already documented. The description only restates two of them ('Filter by status and buyer question') and says nothing about limit, so it adds no syntax or behavioral detail beyond 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 and resource ('Lists wrong AI answers') plus ordering ('newest seen first') and enumerates the two sources: member-logged answers from any engine and competitor_instead entries filed by the weekly check. This distinguishes it from siblings like get_buyer_question_answers and save_wrong_answer without opening either schema.

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

Usage Guidelines4/5

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

Gives clear usage context — read-only listing, filterable by status and question — and names related tools (save_wrong_answer, get_buyer_question_answers, save_idea) for routing. It stops short of explicit when-not guidance, e.g. when to prefer get_buyer_question_answers over this list.

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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