WI

windsurf-data-handling

Configure Windsurf data access and privacy settings to handle sensitive information and ensure compliance.

Install

mkdir -p .claude/skills/windsurf-data-handling && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/3825" && unzip -o skill.zip -d .claude/skills/windsurf-data-handling && rm skill.zip

Installs to .claude/skills/windsurf-data-handling

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Control what code and data Windsurf AI can access and process in your
69 charsno explicit “when” trigger
Intermediate

Key capabilities

  • →Define file exclusion patterns for sensitive data
  • →Configure telemetry and snippet processing settings
  • →Disable autocomplete for sensitive file types
  • →Enforce safety patterns via .windsurfrules
  • →Audit workspaces for exposed secrets

How it works

The skill uses .codeiumignore files to prevent AI access to sensitive paths and provides configuration settings to disable telemetry and autocomplete for specific file types.

Inputs & outputs

You give it
Workspace security requirements
You get back
Configured privacy settings and exclusion patterns

When to use windsurf-data-handling

  • →Define file exclusions for PII protection
  • →Configure data retention for AI processing
  • →Implement privacy guardrails in workspaces
  • →Audit workspace indexing for security

About this skill

Devin Desktop Data Handling

Overview

Build an evidence-backed data map for Devin Desktop. Do not infer retention, residency, training use, certification coverage, or zero-data-retention from plan names; verify mutable vendor claims against the current contract and security documentation.

Prerequisites

  • Data-classification policy and approved repository inventory
  • Contract, DPA, or security evidence available to the authorized reviewer
  • Named security, privacy, and legal decision owners

Tool Use

  • Use Read to inspect only the repository files and configuration needed for the request.
  • Use Write only for a new artifact the user requested; never write credentials or unreviewed production configuration.
  • Use Edit for bounded, reviewable changes and preserve unrelated user work.

Instructions

Step 1: Inventory data flows

For Cascade, autocomplete, indexing, remote indexing, MCP, Hooks, diagnostics, and App Deploys, record inputs, destination, purpose, identity, retention evidence, administrator, and applicable policy. Include metadata and logs, not only source files.

Step 2: Minimize local context

Use .gitignore and repository .codeiumignore to exclude secrets, generated output, customer datasets, private keys, production exports, and irrelevant large files. Enterprise administrators may apply a global .codeiumignore under ~/.codeium/.

Ignored paths are context controls. They do not revoke filesystem access, rotate secrets, satisfy least privilege, or prove a regulatory requirement.

Step 3: Choose durable instructions

Put shared data-handling requirements in AGENTS.md or .devin/rules/*.md, for example:

# Regulated data boundary
- Never paste customer records, access tokens, or production exports into prompts.
- Use synthetic fixtures in tests and examples.
- Require security review for changes under `src/payments/`.
- Stop and escalate if a requested artifact contains regulated data.

Step 4: Review integrations

For every MCP server, Hook, deployment target, and analytics export, confirm an owner, authentication method, approved scopes, destination, log policy, revocation path, and incident contact. Disable integrations that lack an accountable owner.

Step 5: Reconcile vendor evidence

Capture the URL or contract section, observation date, product/plan scope, and reviewer for each claim. Where public documentation and negotiated terms differ, label the applicable authority rather than blending them.

Step 6: Test and approve

Use synthetic canaries to verify exclusions and policy behavior. Obtain the required security/privacy/legal approval before enabling regulated workloads, remote indexing, or external MCP access.

Output

Produce a data-boundary record identifying data classes, indexed and excluded paths, integrations, organization controls, telemetry and logging decisions, retention or residency evidence, open questions, approvals, and validation results. Never reproduce sensitive values.

Error Handling

IssueResponse
Vendor claim lacks current evidenceMark unverified and request contract/security review
Sensitive data entered CascadeStop, contain sharing, rotate affected secrets, and follow incident policy
Ignore test failsCorrect syntax or scope, refresh indexing through current controls, and retest
Integration owner is unknownDisable or quarantine the integration until ownership is established

Examples

Evidence row: "Customer export; excluded by .codeiumignore; no MCP access; repository owner: Data Platform; retention claim pending DPA confirmation; synthetic canary passed during the recorded review run."

Resources

Related Skill

Continue with windsurf-policy-guardrails to turn approved data controls into enforceable repository, terminal, MCP, deployment, and organization policy.

Prerequisites

Windsurf IDE installedIdentified sensitive files

Limitations

  • →Requires manual identification of sensitive files
  • →Requires team training to prevent accidental secret pasting

How it compares

It provides a specific audit workflow and configuration set for managing AI data access in regulated environments.

Compared to similar skills

windsurf-data-handling side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
windsurf-data-handling (this skill)12moReviewIntermediate
reverse-engineering-tools735moNo flagsAdvanced
game-hacking-techniques424moNo flagsAdvanced
solidity-security154moNo flagsIntermediate

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