---
name: juicebox-core-workflow-b
description: 'Execute Juicebox enrichment and outreach workflow.

  Trigger: "juicebox enrich", "candidate enrichment", "talent pool".

  '
allowed-tools: Read, Write, Edit, Bash(npm:*), Grep
version: 1.16.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- saas
- recruiting
- juicebox
compatibility: Designed for Claude Code
---
# Juicebox — Advanced Analysis

## Overview

Build custom queries, apply multi-dimensional filters, and run cross-dataset analysis
on your Juicebox people-intelligence data. Use this workflow when you need to go beyond
standard search — comparing candidate pools across roles, analyzing skill density by
geography, or identifying talent trends over time. This is the secondary workflow;
for basic search and enrichment, see `juicebox-core-workflow-a`.

## Instructions

### Step 1: Build a Custom Query with Filters

```typescript
const query = await client.analysis.query({
  dataset: 'candidates',
  filters: [
    { field: 'skills', operator: 'contains_any', value: ['TypeScript', 'Rust', 'Go'] },
    { field: 'experience_years', operator: 'gte', value: 5 },
    { field: 'location.country', operator: 'eq', value: 'US' },
  ],
  sort: { field: 'relevance_score', order: 'desc' },
  limit: 100,
});
console.log(`Found ${query.total} candidates matching filters`);
query.results.forEach(c =>
  console.log(`  ${c.name} — ${c.title} (${c.relevance_score}/100)`)
);
```

### Step 2: Run Cross-Dataset Comparison

```typescript
const comparison = await client.analysis.compare({
  datasets: ['candidates_q1_2026', 'candidates_q4_2025'],
  group_by: 'primary_skill',
  metrics: ['count', 'avg_experience', 'avg_salary_estimate'],
});
comparison.groups.forEach(g =>
  console.log(`${g.skill}: Q1=${g.datasets[0].count} vs Q4=${g.datasets[1].count} (${g.delta > 0 ? '+' : ''}${g.delta}%)`)
);
```

### Step 3: Aggregate Skill Density by Region

```typescript
const density = await client.analysis.aggregate({
  dataset: 'candidates',
  group_by: 'location.metro_area',
  metric: 'skill_density',
  skill_filter: ['ML Engineering', 'Data Science'],
  top_n: 10,
});
density.regions.forEach(r =>
  console.log(`${r.metro}: ${r.candidate_count} candidates, density=${r.density_score}`)
);
```

### Step 4: Export Analysis Results

```typescript
const exportJob = await client.analysis.export({
  query_id: query.id,
  format: 'csv',
  fields: ['name', 'email', 'primary_skill', 'experience_years', 'location'],
});
console.log(`Export ready: ${exportJob.download_url} (${exportJob.row_count} rows)`);
```

## Error Handling

| Issue | Cause | Fix |
|-------|-------|-----|
| `400 Invalid filter` | Unsupported operator for field type | Check field schema with `client.schema.fields()` |
| `404 Dataset not found` | Stale dataset ID or typo | List datasets with `client.datasets.list()` |
| `408 Query timeout` | Too many filters on large dataset | Add `limit` or narrow date range |
| `429 Rate limited` | Exceeded analysis quota | Implement backoff; check plan limits |
| Partial comparison data | One dataset has sparse coverage | Expected — use `include_nulls: true` for completeness |

## Output

A successful workflow produces filtered candidate lists with relevance scores,
cross-dataset comparison tables showing talent market shifts, and regional
skill-density rankings. Results can be exported as CSV for downstream reporting.

## Prerequisites

- An approved analysis purpose, sandbox datasets containing only synthetic records, source/destination allowlists, a suppression check, and a named owner for review and rollback.

## Examples

Run the comparison in `workspace=ci-synthetic`, restrict output to aggregate metrics, verify `suppression=pass; contacts_exported=0`, then delete the staged dataset after the redacted receipt is approved.

## Resources

- Juicebox API Docs

## Next Steps

See `juicebox-sdk-patterns` for authentication and query builder helpers.


---
Source attribution: jeremylongshore
Original project: https://github.com/jeremylongshore/claude-code-plugins-plus-skills/blob/ab85a061f7bcc039dac13ee193de7a4cd4388571/plugins/saas-packs/juicebox-pack/skills/juicebox-core-workflow-b/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2025 Jeremy Longshore

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: jeremylongshore
Original project: https://github.com/jeremylongshore/claude-code-plugins-plus-skills/blob/ab85a061f7bcc039dac13ee193de7a4cd4388571/plugins/saas-packs/juicebox-pack/skills/juicebox-core-workflow-b/SKILL.md
Attribution basis: Source repository record

Fields of work: Human Resources, Sales
Roles: Customer Success Manager, HR Generalist, Recruiter
Specialties: API, Design, Frontend
Tools: Juicebox Sdk
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: a8dee453b437bbd38c6e09501697c7e5cd24cf7158f438598cf2b846500d0b4a