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js-cohn
by js-cohn

create_draft_reply

Compose a reply within an existing conversation without sending it, including optional CC/BCC fields, to review later or send when ready.

Instructions

Create a draft reply in an existing conversation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ccNo
toNo
bccNo
bodyYes
api_tokenNo
member_idNo
message_idNo
conversation_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden of disclosing behavior. It merely states the action and does not mention side effects, permissions, return behavior, or whether the draft is stored pending further edits, leaving the agent without critical context.

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

Conciseness3/5

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

The single sentence is brief and front-loaded, but it is under-specified for a tool with 8 parameters and no schema descriptions. It lacks vital details that would make the description self-sufficient, so while it is concise, it is not appropriately sized for the tool's complexity.

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

Completeness2/5

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

The description is incomplete given the tool's complexity: 8 parameters, no annotations, and zero schema descriptions. Although an output schema exists, the description does not provide the necessary context for parameter usage, behavioral expectations, or selection among sibling tools, making it inadequate for reliable invocation.

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

Parameters1/5

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

Schema description coverage is 0%, and the description adds no meaning to the parameters. The tool has 8 parameters, including ambiguous ones like api_token, member_id, and message_id, but neither the schema nor the description explains their purpose or relationships, leaving the agent to guess.

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?

The description clearly specifies the action (create), the object (draft reply), and the scope (existing conversation). It distinguishes the tool from siblings like create_draft_conversation, which creates a new conversation, and update_draft, which modifies existing drafts.

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?

The description provides no guidance on when to use this tool versus alternatives such as add_comment or create_draft_conversation. There are no explicit exclusions or preferred contexts, forcing the agent to infer usage from the tool name alone.

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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