Klarix Intelligence Engine

Generate insight-first outreach sequence

generate_outreach_sequence

Read-only

Write cold outreach that opens on a researched, dated insight about the prospect rather than a pleasantry. Supports a 3-step email sequence, a 3-step LinkedIn sequence, or 6 multivariant openers. Enforces the Klarix voice contract (banned AI words and phrases, punctuation tells, rhythm) and reports any violations. Writes to a job title, never to an individual, and never emits contact details.

Input Schema

TableJSON Schema

Name	Required	Description
`channel`	Yes	email = 3-step sequence, linkedin = connect + 2 follow-ups, multivariant = 3 competing openers per channel
`value_prop`	Yes	What you do for them, in your own words. Include the outcome and, if you have one, a number.
`target_title`	Yes	Job title or function you are writing to, e.g. "VP Revenue Operations". A title, never a person.
`prospect_domain`	No	Domain to research for the opening insight. Strongly recommended.
`prospect_company`	Yes	Company you are writing to

Output Schema

TableJSON Schema

Name	Required	Description	Default
`angle`	Yes
`channel`	Yes
`sources`	Yes
`messages`	Yes
`do_not_say`	Yes
`voice_check`	Yes
`target_title`	Yes
`anchor_source`	Yes
`anchor_insight`	Yes
`prospect_company`	Yes
`confidence_detail`	Yes
`evidence_confidence`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedSep 4, 2026

addedOutput schema / properties / confidence_detail
```
Added value: +{
+  "type": "string"
+}
```
addedOutput schema / properties / evidence_confidence
```
Added value: +{
+  "type": "string"
+}
```

changedOutput schema / required

Previous value: -[
-  "prospect_company",
-  "target_title",
-  "channel",
-  "anchor_insight",
-  "anchor_source",
-  "angle",
-  "messages",
-  "do_not_say",
-  "voice_check",
-  "sources"
-]New value: +[
+  "prospect_company",
+  "target_title",
+  "channel",
+  "anchor_insight",
+  "anchor_source",
+  "angle",
+  "messages",
+  "do_not_say",
+  "voice_check",
+  "evidence_confidence",
+  "confidence_detail",
+  "sources"
+]

First observedSep 4, 2026

TDQS

A4.7/5.0

Behavior5/5

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

The annotations already indicate readOnlyHint and openWorldHint, but the description adds valuable behavioral constraints: it enforces the Klarix voice contract, reports violations, writes only to job titles, and never emits contact details. This goes well beyond what annotations provide and clarifies the tool's exact output behavior.

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 four sentences, each carrying essential information: the core method, supported formats, enforced voice contract, and hard constraints. It is front-loaded with the primary purpose and contains no filler or redundant restatements of the title.

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 generative tool with a clear input schema, strong annotations, and an existing output schema, the description covers all necessary context. It explains the research basis, the deliverable formats, the compliance checks, and the boundary conditions (no contact details, no individual names). No critical behavioral gap remains.

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 description coverage is 100%, so the baseline is 3. The description adds meaningful semantics by explaining what each channel produces (3-step email, 3-step LinkedIn, 6 multivariant openers) and reinforcing the target_title constraint ('never to an individual'). This is genuine added value 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 opens with a specific verb and resource ('Write cold outreach') and immediately differentiates the tool by its insight-first approach. It also enumerates the three concrete deliverable types (email sequence, LinkedIn sequence, multivariant openers), which clearly separates it from sibling analysis and research tools.

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 intended use case is clear: generating cold outreach sequences across specific channels. While it does not explicitly name sibling tools to avoid, the channel breakdown and focus on outreach make the context obvious. It lacks an explicit 'when not to use' or direct alternative comparison, but the guidance is sufficient for an agent to select this tool appropriately.

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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