Onsa

Send outreach message

send_outreach

Destructive

Queues one already-approved outreach draft for delivery to a real person on LinkedIn. It requires confirmText, the draft body character-for-character as stored, and confirmName, the recipient's name: drafts are often near-identical between people, so matching the body alone does not identify which one was meant. A mismatch is refused without returning the stored text, which list_pending_outreach supplies. The server additionally requires a confirmation from the person at the keyboard, rendered by the MCP client and quoting the draft as stored; that approval is single-use and bound to one recipient and one draft. A client that cannot render such a confirmation receives a refusal carrying a link to approve inside the Onsa app, and nothing is queued. On success the message is queued rather than delivered: Onsa sends it on its own schedule, subject to daily pacing limits.

Input Schema

TableJSON Schema

Name	Required	Description
`leadId`	Yes	Lead to message, from list_pending_outreach
`confirmName`	Yes	The recipient's name as shown to the user, to prove you meant this person
`confirmText`	Yes	The exact draft text you showed the user and they approved, verbatim

Output Schema

TableJSON Schema

Name	Required	Description	Default
`name`	Yes
`leadId`	Yes
`queued`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 8, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Goes well beyond annotations by detailing concrete behaviors: the message is queued rather than delivered immediately, subject to daily pacing limits; mismatches are refused without exposing stored text; and clients that cannot render confirmation receive a refusal with an approval link. This aligns with destructiveHint and idempotent=false.

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 description is thorough and logically structured, but it is somewhat wordy and repeats the confirmation and refusal behavior. Still, every sentence adds relevant operational detail and there is no irrelevant filler.

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?

Covers preconditions, exact-match requirements, failure modes, queue semantics, and pacing limits. Since an output schema exists, not detailing the return format is acceptable; the description gives enough context for an agent to call the tool correctly.

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

Parameters5/5

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

All three required parameters have meaningful descriptions in the schema and are reinforced in prose. confirmName and confirmText clarify that they must match the exact stored values, and leadId is explicitly sourced from list_pending_outreach.

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?

Clearly states it queues an already-approved outreach draft for delivery to a lead on LinkedIn, and distinguishes the action from immediate sending by emphasizing the queue. It references the source list_pending_outreach, making the tool's role easy to identify.

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?

Provides strong usage guidance by requiring exact confirmText and confirmName from list_pending_outreach and explaining that only already-approved drafts should be sent. It does not explicitly compare to sibling tools, but the approval and source requirements make selection unambiguous.

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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