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Glama

Onsa

Send outreach message

send_outreach
Destructive

Queue an approved outreach draft for sending to a real person on LinkedIn. THIS REACHES A HUMAN. Show the user the exact message AND the recipient, and get their explicit go-ahead for that person, every time — even if they said "send them all". You must pass back both confirmText (character-for-character, not re-typed) and confirmName (the recipient's name), because these drafts are often near-identical between people and matching the body alone does not prove you meant this one. A mismatch refuses without telling you the real text: re-read it with list_pending_outreach. This tool ALSO puts a confirmation dialog in front of the person at the keyboard, quoting the draft as stored — you cannot answer it, and nothing is sent until they do. If they decline or dismiss it, STOP: do not call this again for that lead, ask what they want changed. Note this QUEUES the message — Onsa sends it on its own schedule, subject to daily limits — so report it as queued, not delivered.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
leadIdYesLead to message, from list_pending_outreach
confirmNameYesThe recipient's name as shown to the user, to prove you meant this person
confirmTextYesThe exact draft text you showed the user and they approved, verbatim

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
leadIdYes
queuedYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Beyond annotations (destructiveHint=true), the description discloses that the tool queues rather than delivers, puts a confirmation dialog in front of the user, refuses on mismatch, and instructs to stop if the user declines. This provides significant behavioral detail beyond the annotation flags.

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 a single dense paragraph but every sentence adds value, covering safety, confirmation requirements, and error behavior. While it could be broken into bullets for readability, it is not redundant or padded.

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?

Given the safety-critical nature and lack of an output schema, the description covers what the tool does, when to use it, failure modes (mismatch, user decline), and the queuing behavior. It does not explicitly state the success return value, but that is less critical for an action tool with clear side effects.

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?

Schema descriptions for all three parameters are present and meaningful: leadId is sourced from list_pending_outreach, confirmName proves the intended recipient, and confirmText requires verbatim user-approved text. The tool description further explains why these confirmations are needed, adding context beyond the schema.

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 states the tool 'Queue an approved outreach draft for sending to a real person on LinkedIn.' It specifies the action (queueing/sending), the resource (outreach draft, person), and distinguishes it from siblings like rewrite_outreach and list_pending_outreach by emphasizing 'approved' and 'queue.'

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 provides usage context: leadId comes from list_pending_outreach, and the tool requires explicit user confirmation. It also gives alternative guidance by instructing to 're-read it with list_pending_outreach' on mismatch. However, it does not explicitly contrast with all sibling tools (e.g., continue_campaign), though the purpose is clear enough.

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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