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Funkel AI

get_reply_attempt

Read-onlyIdempotent

Read one reply attempt by its stable request_key in the selected product. Returns actual delivery evidence and next_action. Uncertain delivery requires manual provider review unless an exact outgoing provider message is confirmed. Never retries or sends.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
request_keyYesStable request identity from send_conversation_reply, 8-128 characters

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive, closed-world), so the description rightly focuses elsewhere. It adds real behavioral context the annotations cannot convey: what is returned (delivery evidence, next_action), that uncertain delivery needs manual provider review unless an outgoing message is confirmed, and that it never retries or sends.

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 purpose is front-loaded in the first sentence, followed by return contents and one behavioral caveat. Every sentence carries weight, though the 'selected product' clause is slightly vague.

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

Completeness4/5

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

With no output schema, the description correctly compensates by naming the returned fields (delivery evidence, next_action) and the uncertain-delivery caveat. For a one-parameter read tool with full annotation coverage, this is nearly complete; only explicit routing guidance 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% and the single request_key parameter is fully documented there (including its origin in send_conversation_reply and length bounds). The description adds only the framing 'stable request_key in the selected product', so the baseline 3 is appropriate.

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

Purpose4/5

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

States a specific verb and resource ('Read one reply attempt by its stable request_key in the selected product'), which clearly separates it from the send_/prepare_ conversation tools. It does not explicitly name a sibling it might be confused with, but the resource is narrow enough that an agent can identify it.

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

Usage Guidelines2/5

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

There is no explicit statement of when to use this versus alternatives like get_conversation_context or the reply-preparation tools. Usage is only weakly implied by 'Returns actual delivery evidence and next_action', which hints at a status-check role but names no condition or exclusion.

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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