Argorant

Bring people back into a campaign

argorant_restore_campaign_leads

Bring back people who were taken out of a campaign and never got an email, by lead_ids, addresses, tag, a CSV file (up to 100,000) or all_removed=true. Use it to undo a removal; to add new people use argorant_add_campaign_leads. Always call it first with preview=true and tell the user how many would come back and how many stay out. People who were emailed, replied, bounced, unsubscribed or are blocked never come back. The ones who come back wait for the first email, and nothing is sent until the campaign runs. Doing it needs confirmed=true after the user's clear yes. 2,000 people or more come back in the background, with a job_id for argorant_add_campaign_leads_status. More in the docs at https://docs.argorant.com/docs/agents/tools#campaigns

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "campaign_id": "<campaign_id>"
    },
    "name": "argorant_restore_campaign_leads"
  }
}

Input Schema

Name	Required	Description
`tag`	No	Everyone who carries this tag.
`file`	No	CSV text of lead ids or email addresses, up to 100,000.
`emails`	No	The people's email addresses.
`preview`	No	Set it to true to only count, without changing anything.
`lead_ids`	No	Ids from argorant_list_campaign_leads.
`confirmed`	No	true only after the user's clear yes to bringing these people back
`all_removed`	No	Everyone taken out of this campaign who was never emailed.
`campaign_id`	Yes	The campaign's id, from argorant_list_campaigns.

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 8, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Goes well beyond the annotations, which only say this is a non-read-only, non-destructive, closed-world mutation. The description discloses the eligibility rules (emailed, replied, bounced, unsubscribed or blocked people never come back), the post-restore state (they wait for the first email; nothing sends until the campaign runs), the preview/confirm gating, and the async threshold with the job_id routed to argorant_add_campaign_leads_status. The only gap is that it restates the 2,000+ background job without saying how to poll it precisely, but that is minor.

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?

Front-loaded with purpose and selectors, then workflow, exclusions, and async behavior in a logical order with no filler. The first sentence is long and packs five alternatives into one clause, which slightly hurts scannability, but every sentence carries operational information.

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 mutation tool with 8 parameters and an output schema already present, the description covers the workflow (preview then confirm), eligibility limits, resulting lead state, and long-running behavior with the correct status sibling. Nothing an agent needs in order to call this safely is missing.

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?

Schema coverage is 100%, so the baseline is 3, and the description adds real meaning on top: the selectors are presented as alternatives, and all_removed is scoped to 'never emailed', which sharpens what the schema's one-line field description leaves ambiguous. It does not, however, explain what happens if multiple selectors are supplied together, which is the main unresolved semantic question for an 8-parameter tool.

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 a specific verb plus resource (bring back removed campaign leads) and immediately enumerates the selection modes: lead_ids, addresses, tag, CSV file, or all_removed=true. It explicitly distinguishes itself from the sibling argorant_add_campaign_leads ('to add new people use ...'), so an agent can route between restore and add without opening schemas.

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

Usage Guidelines5/5

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

Gives explicit when-to-use ('Use it to undo a removal'), the alternative for the other case (argorant_add_campaign_leads), and a mandatory workflow: 'Always call it first with preview=true and tell the user how many would come back and how many stay out.' It also states the confirmation precondition ('confirmed=true after the user's clear yes'), leaving nothing to inference.

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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