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Mark replied

mark_replied

Logs that the user posted a reply to a cue, the same as copy + open in the app. Pass the text they actually posted, and draft_id when it started from a draft. CueHQ then checks how the thread grew at 6, 24 and 72 hours. Only call this after the user says they posted.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

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

Input Schema

NameRequiredDescriptionDefault
idYesThe cue id from list_cues.
textNoThe reply exactly as the user posted it.
draft_idNoThe draft the reply started from, from get_cue or draft_reply.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations declare readOnlyHint=false, destructiveHint=false, idempotentHint=false; the description adds meaningful downstream behavior beyond that — CueHQ measures thread growth at 6, 24 and 72 hours, so the call has delayed side effects. It does not state what happens on a duplicate call, which matters given the non-idempotent hint, so not a 5.

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

Conciseness5/5

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

Four short sentences, front-loaded with the core action and ending with the call-safety rule. Every sentence carries distinct information: what it does, argument intent, downstream consequence, and gating condition.

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?

No output schema exists, and the description compensates by explaining the observable consequence of the call (thread-growth checks at 3 intervals). For a three-parameter logging tool with full schema coverage and annotations, nothing an agent needs is 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?

Schema coverage is 100%, so baseline is 3, but the description adds real semantics: text should be verbatim as posted, and draft_id is conditional on the reply having started from a draft. That conditional guidance is not obvious from the schema alone.

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 ('Logs that the user posted a reply to a cue') and grounds it in concrete app behavior ('the same as copy + open in the app'). This is clearly distinguishable from siblings like draft_reply and skip_cue, which create drafts or dismiss cues rather than recording an actual post.

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?

Explicit gating condition: 'Only call this after the user says they posted.' Combined with the equivalence note (copy + open), an agent knows both the trigger and the alternative path it replaces. No inference required.

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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