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IvanBBaev
by IvanBBaev

x_dm_send

Send an X (Twitter) direct message to one user or existing conversation, creating a 1:1 conversation when necessary. Enforces recipient follow/DM restrictions and daily send limits.

Instructions

Send an X (Twitter) direct message to exactly one target: an existing conversation (conversation_id) or a user (participant), creating the 1:1 conversation if needed. Fails with a forbidden error when the recipient does not follow the sender, has DMs closed, or blocked them. Subject to the platform cap of ~1,440 DMs per 24 hours. Requires user-context auth; never enabled by any policy preset — an operator must explicitly opt in. (disabled by policy read-only)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesMessage text to send (1-10,000 characters).
participantNoTarget user for a 1:1 DM: numeric id, handle, or @handle.
conversation_idNoTarget conversation id (numeric, or two numeric ids joined by "-").

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
metaYes
summaryNo
Behavior5/5

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

Beyond the annotations, the description discloses specific failure modes (forbidden when blocked, DMs closed, or non-follower), the ~1,440 DM/24h cap, the need for user-context auth, and the operator opt-in policy requirement. It also explains side effects like creating the 1:1 conversation if needed. No contradiction with readOnlyHint=false or destructiveHint=false.

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?

The description is concise despite its length: each sentence contributes a distinct operational fact (target selection, failure cases, rate limit, auth/policy). The core purpose is front-loaded before edge conditions.

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 three-parameter send action with a full schema and output schema present, the description covers target selection, required auth, policy opt-in, rate limits, and failure behavior. Nothing essential to invoking the tool correctly is omitted.

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?

Although schema coverage is 100%, the description adds selection semantics by requiring exactly one of conversation_id or participant and explaining the effect of each target type. This clarifies mutual exclusivity and the create-if-needed behavior that the schema alone does not state.

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 an unambiguous action ('Send an X direct message') and names exactly one target with its two supported forms, conversation_id or participant. This distinguishes it from sibling DM-list tools and other x_* write actions without needing the 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?

The description clearly defines when to call the tool (sending a DM to one target) and the prerequisites/limitations (auth, rate cap, recipient constraints), giving an agent enough context. It does not explicitly name an alternative for related tasks like reading DM events, but sibling names make that separation evident.

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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