Juicebox Reference ArchitectureSAFE
Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.
Overview
Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.
4f83675ca38aOBSERVED · 2026-10-09Host compatibility
What the documentation claims. We have not run a compatibility test.
| Host | Status | Notes |
|---|---|---|
| claude-code | mentioned | |
| cursor | mentioned |
What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
--- name: juicebox-reference-architecture description: 'Implement Juicebox reference architecture. Trigger: "juicebox architecture", "recruiting platform design". ' allowed-tools: Read, Write, Edit, Grep version: 1.16.0 license: MIT author: Jeremy Longshore <[email protected]> tags: - saas - recruiting - juicebox compatibility: Designed for Claude Code --- # Juicebox Reference Architecture ## Overview Production architecture for AI-powered candidate analysis integrations with Juicebox. Designed for recruiting teams needing automated dataset ingestion from job descriptions, intelligent candidate scoring and ranking, result caching for repeated searches, and seamless export to ATS platforms like Greenhouse and Lever. Key design drivers: search result freshness, candidate deduplication across sources, outreach sequencing, and analysis pipeline throughput for high-volume hiring. ## Architecture Diagram ``` Recruiter Dashboard ──→ Search Service ──→ Cache (Redis) ──→ Juicebox API ↓ /search Queue (Bull) ──→ Analysis Worker /profiles ↓ /outreach ATS Export Service ──→ Greenhouse/Lever ↓ Webhook Handler ←── Juicebox Events ``` ## Service Layer ```typescript class CandidateSearchService { constructor(private juicebox: JuiceboxClient, private cache: CacheLayer) {} async findAndRank(criteria: SearchCriteria): Promise<RankedCandidate[]> { const cacheKey = `search:${this.hashCriteria(criteria)}`; const cached = await this.cache.get(cacheKey); if (cached) return cached; const results = await this.juicebox.search(criteria); const ranked = results.profiles.map(p => ({ ...p, score: this.scoreCandidate(p, criteria) })) .sort((a, b) => b.score - a.score); await this.cache.set(cacheKey, ranked, CACHE_CONFIG.searchResults.ttl); return ranked; } async exportToATS(candidates: string[], jobId: string, ats: 'greenhouse' | 'lever'): Promise<ExportResult> { const deduped = await this.deduplicateAgainstATS(candidates, jobId, ats); return this.juicebox.export({ profiles: deduped, destination: ats, job_id: jobId }); } } ``` ## Caching Strategy ```typescript const CACHE_CONFIG = { searchResults: { ttl: 1800, prefix: 'search' }, // 30 min — candidate pools shift slowly profiles: { ttl: 3600, prefix: 'profile' }, // 1 hr — profile data stable short-term analysisRuns: { ttl: 7200, prefix: 'analysis' }, // 2 hr — analysis results are expensive to recompute atsState: { ttl: 300, prefix: 'ats' }, // 5 min — ATS pipeline freshness for dedup outreach: { ttl: 60, prefix: 'outreach' }, // 1 min — sequence status changes frequently }; // New search invalidates matching cached results; ATS export clears ats cache for that job ``` ## Event Pipeline ```typescript class RecruitingPipeline { private queue = new Bull('juicebox-events', { redis: process.env.REDIS_URL }); async onSearchComplete(searchId: string, results: RankedCandidate[]): Promise<void> { await this.queue.add('analyze', { searchId, candidateIds: results.map(r => r.id) }, { attempts: 3, backoff: { type: 'exponential', delay: 2000 } }); } async processOutreachEvent(event: OutreachEvent): Promise<void> { if (event.type === 'reply_received') await this.flagForRecruiterReview(event); if (event.type === 'bounced') await this.markInvalid(event.candidateId); await this.syncStatusToATS(event); } } ``` ## Data Model ```typescript interface SearchCriteria { role: string; skills: string[]; location?: string; experienceYears?: number; companySize?: string; } interface RankedCandidate { id: string; name: string; title: string; company: string; score: number; skills: string[]; profileUrl: string; } interface OutreachSequence { id: string; candidateId: string; jobId: string; steps: OutreachStep[]; status: 'active' | 'replied' | 'bounced' | 'opted-out'; } interface ExportResult { exported: number; duplicatesSkipped: number; atsJobId: string; } ``` ## Scaling Considerations - Parallelize search requests across role categories — Juicebox API supports concurrent queries - Cache analysis results aggressively — AI scoring is the most expensive operation per candidate - Batch ATS exports by job requisition to minimize Greenhouse/Lever API round-trips - Deduplicate candidates across searches before outreach to avoid double-contacting - Rate-limit outreach sequencing to maintain sender reputation and deliverability ## Error Handling | Component | Failure Mode | Recovery | |-----------|-------------|----------| | Candidate search | Juicebox API timeout | Retry with reduced result count, serve cached results if available | | Analysis pipeline | Scoring model latency spike | Queue with timeout, return unscored results with flag | | ATS export | Greenhouse rate limit | Batch retry with exponential backoff, notify recruiter on persistent failure | | Outreach sequence | Email bounce | Mark candidate invalid, remove from active sequences, update ATS | | Webhook handler | Duplicate event delivery | Idempotency key on event ID + candidate ID | ## Prerequisites - An approved architecture diagram, sandbox workspace, synthetic fixture set, source/destination allowlists, suppression controls, secrets references, and a tested rollback path. ## Instructions 1. Validate each component in a sandbox with synthetic data; reject literal credentials, unapproved integrations, and any contact-level export. 2. Enforce least privilege, idempotency, redacted telemetry, suppression checks, and `contacts_exported=0` before connecting a new component. 3. Run a staged canary and halt on scope, security, quota, policy, or retention drift; restore the prior component revision if it fails. 4. Promote only with owner approval and prese
Trust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | PASS |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (0)
No findings outside the package's declared scope.
Gates applied: no_behavioural_pass.
4f83675ca38afull audit observations/trust-audit/skill/jeremylongshore__juicebox-reference-architecture.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-09 | 4f83675ca38a | SAFE | B | 89 | first audit |
Questions
What does the Juicebox Reference Architecture skill do?
Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.
Is Juicebox Reference Architecture safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Juicebox Reference Architecture access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
Which assistants does Juicebox Reference Architecture work with?
Its documentation mentions claude-code and cursor. That is what the text claims, not a compatibility test we ran.
How current is this page?
The grade is for one exact copy of the source (4f83675ca38a), read on 2026-10-09. The repository is watched, and a new audit runs when it changes — this is the first audit.