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yax_build_email_sequence

Researches each prospect and writes personalized cold email sequences with subject lines, body, and send schedule based on your offer and preferred tone.

Instructions

Builds a personalized cold email sequence for a list of prospects. Researches each prospect and writes tailored copy. Returns subject lines, body, and send schedule per prospect.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
prospectsYesList of prospect objects. Each needs at minimum: email and name. Optional: company, title, linkedin_url.
offerYesOne sentence describing your offer or value proposition, e.g. 'We help SaaS companies reduce churn by 30%'.
sequence_lengthNoNumber of emails in the sequence. Defaults to 3.
toneNoEmail tone: 'professional', 'casual', or 'direct'. Defaults to 'professional'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNoTrue if sequence was built.
run_idNoRun ID for receipt retrieval.
sequencesNoArray of email sequences per prospect. Each has subject lines, body copy, and send schedule.
Behavior4/5

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

Annotations indicate readOnlyHint=false and destructiveHint=false, but the description adds context: it researches each prospect and writes tailored copy. No contradictions. However, it doesn't disclose any side effects or limitations beyond what's implied by annotations.

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?

Two sentences, front-loaded with the main action, and every word earns its place. No redundancy or fluff.

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?

The tool has moderate complexity with 4 params and an output schema (present but not detailed). The description covers the core functionality, though it doesn't mention output schema specifics, which is acceptable as the schema handles that.

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% with descriptions for all 4 parameters. The description adds value by stating it researches prospects and writes tailored copy, which complements parameter meanings but doesn't add significant detail beyond schema for each param.

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 builds a personalized cold email sequence, researches prospects, and writes tailored copy, specifying the verb 'builds' and resource 'cold email sequence'. It distinguishes from siblings like `yax_enrich_lead_data` (data enrichment) and `yax_score_leads` (scoring) by focusing on email generation.

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

Usage Guidelines3/5

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

The description implies use when needing personalized cold email sequences but lacks explicit when-to-use/when-not-to-use guidance. No alternatives or exclusions are mentioned, leaving the agent to infer context from purpose alone.

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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