Claude-code-plugins-plus-skills cohere-data-handling
install
source · Clone the upstream repo
git clone https://github.com/jeremylongshore/claude-code-plugins-plus-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/jeremylongshore/claude-code-plugins-plus-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/plugins/saas-packs/cohere-pack/skills/cohere-data-handling" ~/.claude/skills/jeremylongshore-claude-code-plugins-plus-skills-cohere-data-handling && rm -rf "$T"
manifest:
plugins/saas-packs/cohere-pack/skills/cohere-data-handling/SKILL.mdsource content
Cohere Data Handling
Overview
Handle sensitive data when calling Cohere APIs. Cohere processes text server-side for Chat, Embed, Rerank, and Classify — any PII in your input reaches their servers. This skill covers pre-call redaction, post-call scrubbing, and compliance patterns.
Prerequisites
- Understanding of GDPR/CCPA requirements
SDK installedcohere-ai- Database for audit logging
Data Flow Awareness
Your App → [PII Redaction] → Cohere API → [Response Scrubbing] → Your App → User Key point: Everything you send to cohere.chat(), cohere.embed(), etc. is processed on Cohere's servers. Redact BEFORE the API call.
Instructions
Step 1: PII Detection
interface PIIFinding { type: string; match: string; start: number; end: number; } const PII_PATTERNS: Array<{ type: string; regex: RegExp }> = [ { type: 'email', regex: /[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}/g }, { type: 'phone', regex: /\b(\+\d{1,3}[-.]?)?\d{3}[-.]?\d{3}[-.]?\d{4}\b/g }, { type: 'ssn', regex: /\b\d{3}-\d{2}-\d{4}\b/g }, { type: 'credit_card', regex: /\b\d{4}[- ]?\d{4}[- ]?\d{4}[- ]?\d{4}\b/g }, { type: 'ip_address', regex: /\b\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}\b/g }, ]; function detectPII(text: string): PIIFinding[] { const findings: PIIFinding[] = []; for (const { type, regex } of PII_PATTERNS) { for (const match of text.matchAll(new RegExp(regex))) { findings.push({ type, match: match[0], start: match.index!, end: match.index! + match[0].length, }); } } return findings; }
Step 2: Pre-Call Redaction
function redactPII(text: string): { redacted: string; map: Map<string, string> } { const map = new Map<string, string>(); let redacted = text; let counter = 0; for (const { type, regex } of PII_PATTERNS) { redacted = redacted.replace(new RegExp(regex), (match) => { const placeholder = `[${type.toUpperCase()}_${counter++}]`; map.set(placeholder, match); return placeholder; }); } return { redacted, map }; } // Usage: redact before sending to Cohere async function safeCohereChat(userInput: string) { const { redacted, map } = redactPII(userInput); const response = await cohere.chat({ model: 'command-a-03-2025', messages: [{ role: 'user', content: redacted }], }); // Optionally restore PII in response (for internal use only) let answer = response.message?.content?.[0]?.text ?? ''; for (const [placeholder, original] of map) { answer = answer.replace(placeholder, original); } return answer; }
Step 3: Safe Embedding
// Embeddings are stored long-term in vector DBs — ensure no PII async function safeEmbed(texts: string[]): Promise<number[][]> { // Check for PII before embedding for (const text of texts) { const pii = detectPII(text); if (pii.length > 0) { console.warn(`PII detected in embed input: ${pii.map(p => p.type).join(', ')}`); // Option 1: Redact and embed // Option 2: Reject and throw throw new Error(`PII found in embedding input: ${pii.map(p => p.type).join(', ')}`); } } return cohere.embed({ model: 'embed-v4.0', texts, inputType: 'search_document', embeddingTypes: ['float'], }).then(r => r.embeddings.float); }
Step 4: Classify with Data Minimization
// Classify endpoint receives text + examples — minimize both async function safeClassify(inputs: string[]) { // Redact PII from classification inputs const safeInputs = inputs.map(text => redactPII(text).redacted); return cohere.classify({ model: 'embed-english-v3.0', inputs: safeInputs, examples: [ // Examples should never contain real PII { text: 'This product is great', label: 'positive' }, { text: 'Amazing experience', label: 'positive' }, { text: 'Terrible service', label: 'negative' }, { text: 'Very disappointed', label: 'negative' }, ], }); }
Step 5: Audit Logging
interface CohereAuditEntry { timestamp: Date; endpoint: string; model: string; piiDetected: string[]; redacted: boolean; tokensUsed: { input: number; output: number }; userId?: string; } async function auditCohereCall(entry: CohereAuditEntry): Promise<void> { // Log to database (not console — structured storage) await db.cohereAudit.insert({ ...entry, // Never log the actual API input/output — only metadata }); } // Usage async function auditedChat(userId: string, message: string) { const pii = detectPII(message); const { redacted } = redactPII(message); const response = await cohere.chat({ model: 'command-a-03-2025', messages: [{ role: 'user', content: redacted }], }); await auditCohereCall({ timestamp: new Date(), endpoint: 'chat', model: 'command-a-03-2025', piiDetected: pii.map(p => p.type), redacted: pii.length > 0, tokensUsed: { input: response.usage?.billedUnits?.inputTokens ?? 0, output: response.usage?.billedUnits?.outputTokens ?? 0, }, userId, }); return response; }
Step 6: Safety Modes for Content Filtering
// Cohere's built-in safety modes (separate from PII — these handle harmful content) await cohere.chat({ model: 'command-a-03-2025', messages: [{ role: 'user', content: userInput }], safetyMode: 'STRICT', // Maximum content filtering // Options: 'CONTEXTUAL' (default), 'STRICT', 'OFF' // Note: Not configurable when using tools or documents });
Data Retention Guidelines
| Data | Retention | Action |
|---|---|---|
| API request logs (redacted) | 30 days | Auto-delete |
| Audit entries | 7 years | Archive to cold storage |
| Cached embeddings | Until source changes | Invalidate on update |
| Cohere API responses | Do not persist | Process in memory only |
| PII mappings | Per-request only | Never persist |
Compliance Checklist
- PII redacted before all Cohere API calls
- Embeddings verified PII-free before vector DB storage
- Audit trail for all API calls with PII metadata
- Safety mode set to STRICT for user-facing applications
- API responses not persisted (processed in memory)
- Data retention policy enforced with automated cleanup
- Classify examples use synthetic data (no real PII)
Output
- PII detection and redaction pipeline
- Safe wrappers for Chat, Embed, and Classify
- Audit logging with PII metadata (not content)
- Data retention policy with automated cleanup
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| PII in embeddings | Missing pre-check | Add detectPII before embed |
| Redaction breaks context | Over-aggressive regex | Use domain-specific patterns |
| Audit gap | Async logging failed | Use sync fallback |
| Safety mode ignored | Used with tools/docs | Separate safety from RAG calls |
Resources
Next Steps
For enterprise access control, see
cohere-enterprise-rbac.