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machfive

by io.github.Bluecraft-AI

Generate Batch

generate_batch

Submit multiple leads for batch email sequence generation (ASYNC).

Returns IMMEDIATELY with a list_id. Processing runs in the background. After calling this, poll get_list_status every 15-30 seconds until processing_status is 'completed' or 'failed', then call export_list.

You must have a campaign_id first. Call list_campaigns if you don't have one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
list_nameNoDisplay name for this batch in MachFive UI.
leads_jsonYesJSON array of lead objects. Each MUST have "email". Optional: name, title, company, company_website, linkedin_url. Example: '[{"email":"jane@acme.com","name":"Jane Doe"}]'
campaign_idYesCampaign UUID from list_campaigns.
email_countNoNumber of emails per lead, 1-5.
approved_ctasNoComma-separated CTAs. Omit to use campaign defaults.
campaign_angleNoAdditional context/angle for personalization.
email_signatureNoSignature appended to each email.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.7/5.0
Behavior5/5

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

The description discloses critical asynchronous behavior beyond the annotations: 'Returns IMMEDIATELY with a list_id. Processing runs in the background.' It also explains the polling pattern with get_list_status and the eventual export_list call. This is valuable context not captured in the annotations or schema.

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 compact and front-loaded, with the key behavior ('ASYNC', 'Returns IMMEDIATELY') stated upfront. It delivers the workflow in three sentences without fluff or redundancy.

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?

Given the tool's async nature and the need for follow-up steps, the description covers all critical context: prerequisite, immediate return, background processing, polling, and final export. The output schema is not shown, but the description explicitly mentions the returned list_id, so the agent has the necessary information to use the tool correctly.

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

Parameters3/5

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

The schema has 100% parameter description coverage, so the baseline is 3. The description adds minimal parameter-specific detail beyond the schema, only mentioning the need for a campaign_id first. It doesn't enrich the schema's existing parameter descriptions.

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's function: 'Submit multiple leads for batch email sequence generation (ASYNC).' It uses a specific verb and resource, and the ASYNC qualifier distinguishes it from synchronous operations. Sibling tools like generate_sequence are implicitly differentiated by the 'batch' focus.

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?

The description provides explicit usage guidance: it starts with the prerequisite 'You must have a campaign_id first' and tells users to call list_campaigns if needed. It also outlines the post-call workflow: poll get_list_status, then call export_list. This clearly indicates when and how to use the tool relative to its siblings.

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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TDQS

A4.7/5.0
Disambiguation5/5

Each tool has a distinct purpose: list_campaigns provides campaign IDs, generate_batch and generate_sequence handle async batch and sync single generation respectively, get_list_status polls progress, export_list retrieves completed results, and list_lists browses past batches. The descriptions clearly differentiate the overlapping generate tools with explicit usage guidance.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case (e.g., list_campaigns, generate_batch, export_list). The verbs are clear and the nouns accurately reflect the resources/actions, making the API predictable.

Tool Count5/5

With 6 tools, the server is well-scoped for its purpose of generating and managing email sequences. Each tool serves a necessary role in the workflow, and the count is ideal—not overwhelming, not sparse.

Completeness5/5

The tool set covers the full lifecycle: discover campaigns, submit batch or single-lead generation, poll status, retrieve results, and browse past batches. There are no obvious missing operations that would prevent an agent from completing the core workflow.

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