Recommended Policies for IDE Traffic

IDE AI assistants send code context — file contents, function signatures, comments, and sometimes entire repositories — to LLM providers. The Keeptrusts gateway lets you apply policies that protect sensitive data, control costs, and cache repeated queries, all without changing how developers use their IDEs.

Use this page when

You are working through Recommended Policies for IDE Traffic as an implementation or operating workflow in Keeptrusts.
You need the practical steps, expected outcomes, and related validation guidance in one place.
If you need exact field-by-field reference instead of a workflow page, use the linked reference pages in Next steps.

Primary audience

Primary: Technical Engineers
Secondary: AI Agents, Technical Leaders

How IDE Traffic Differs from Chat

IDE completions differ from conversational chat in ways that affect policy design:

Characteristic	IDE Completions	Chat
Request frequency	Very high (every keystroke or tab)	Lower (user-initiated)
Context size	Large (file contents, surrounding code)	Variable
Sensitivity	Often contains secrets, credentials, IP	Varies
Cacheability	High for repeated patterns	Lower
Latency sensitivity	Very high (blocks typing flow)	Moderate

Design your policies to be fast (minimal latency) and code-aware (detect patterns in source code, not just prose).

Secret Redaction

Code files frequently contain hardcoded secrets. Configure redaction to catch them before they reach the LLM provider:

# policy-config.yaml
policies:
  - name: redact-secrets-in-code
    type: redaction
    phase: input
    config:
      patterns:
        - name: api-keys
          regex: '(?i)(api[_-]?key|apikey)\s*[:=]\s*["\x27]?([A-Za-z0-9_\-]{20,})["\x27]?'
          replacement: "REDACTED_API_KEY"
        - name: aws-access-key
          regex: 'AKIA[0-9A-Z]{16}'
          replacement: "REDACTED_AWS_KEY"
        - name: connection-strings
          regex: '(?i)(postgres|mysql|mongodb|redis)://[^\s"'```'<>]+'
          replacement: "REDACTED_CONNECTION_STRING"
        - name: jwt-tokens
          regex: 'eyJ[A-Za-z0-9_-]{10,}\.[A-Za-z0-9_-]{10,}\.[A-Za-z0-9_-]{10,}'
          replacement: "REDACTED_JWT"
        - name: private-keys
          regex: '-----BEGIN (RSA |EC |DSA )?PRIVATE KEY-----'
          replacement: "REDACTED_PRIVATE_KEY"

PII Redaction for Code Comments

Developers sometimes include personal data in comments, TODOs, and docstrings:

  - name: redact-pii-in-comments
    type: redaction
    phase: input
    config:
      patterns:
        - name: email-addresses
          regex: '[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}'
          replacement: "redacted@example.com"
        - name: phone-numbers
          regex: '(?:?1[-.\s]?)?\(?\d{3}\)?[-.\s]?\d{3}[-.\s]?\d{4}'
          replacement: "REDACTED_PHONE"

Cost Control Policies

IDE completions generate a high volume of requests. Control costs with rate limiting and spending caps:

  - name: ide-rate-limit
    type: rate_limit
    config:
      requests_per_minute: 60
      per: user
      response_on_limit: "Rate limit reached. Completions will resume shortly."

  - name: ide-spending-cap
    type: spend_limit
    config:
      daily_limit_usd: 10.00
      per: user
      action: block

These policies prevent runaway costs from aggressive autocomplete triggers while keeping the experience smooth for normal usage.

Engineering Cache for Completions

Many IDE completion requests are similar or identical — the same boilerplate, the same import statement, the same function pattern. Enable the engineering cache to serve these instantly:

  - name: ide-cache
    type: cache
    config:
      enabled: true
      ttl_seconds: 3600
      similarity_threshold: 0.95

Cached responses bypass the LLM provider entirely, reducing both cost and latency.

Content Filtering on Outputs

Apply output policies to ensure completions don't include problematic content:

  - name: filter-completions
    type: content_filter
    phase: output
    config:
      block_patterns:
        - name: license-violations
          regex: '(?i)copyright .+ all rights reserved'
          action: redact
        - name: unsafe-code
          regex: '(?i)(eval\(|exec\(|__import__|subprocess\.call)'
          action: flag

Minimal-Latency Policy Chain

For IDE completions where latency is critical, keep the policy chain short:

# Optimized for IDE speed
policies:
  - name: redact-secrets-in-code
    type: redaction
    phase: input
    config:
      patterns:
        - name: api-keys
          regex: '(?i)(api[_-]?key|apikey)\s*[:=]\s*["\x27]?([A-Za-z0-9_\-]{20,})["\x27]?'
          replacement: "REDACTED_API_KEY"

  - name: ide-cache
    type: cache
    config:
      enabled: true
      ttl_seconds: 3600

  - name: ide-rate-limit
    type: rate_limit
    config:
      requests_per_minute: 60
      per: user

This chain applies secret redaction and caching with minimal overhead. Add more policies as needed, but test latency impact with kt events tail to see per-request timing.

Separate Policies for Chat vs. Completions

If your IDE extension supports both chat and inline completions, you can route them through different policy chains using provider routing:

pack:
  name: policies-for-ide-traffic-providers-7
  version: 1.0.0
  enabled: true
providers:
  targets:
  - id: completions
    provider: 
  - id: chat
    provider: 
policies:
  chain:
  - audit-logger
policy:
  audit-logger:
    immutable: true
    retention_days: 365
    log_all_access: true

Use a fast, inexpensive model for completions and a more capable model for chat conversations.

Verifying Policies

After configuring policies, verify they apply correctly:

# Start the event tail
kt events tail

# Trigger a completion from your IDE that contains a test secret
# e.g., type: API_KEY = "sk-test12345678901234567890"

The event output shows whether the secret was redacted:

2024-01-15T10:32:15Z  ALLOW  gpt-4o-mini  redacted=1  tokens=180

For AI systems

Canonical terms: Keeptrusts, Recommended Policies for IDE Traffic, ide-integration.
Exact feature, config, command, or page names: Recommended Policies for IDE Traffic.
Use the linked audience and reference pages in Next steps when you need deeper source material.

For engineers

Use the commands, configuration examples, API payloads, or UI steps in this page as the working baseline for Recommended Policies for IDE Traffic.
Validate the result with the expected outcomes, troubleshooting notes, or linked workflow pages in this page and Next steps.

For leaders

This page matters when planning rollout, governance, support ownership, or operating decisions for Recommended Policies for IDE Traffic.
Use the linked audience, architecture, and workflow pages in Next steps to connect this detail to broader implementation choices.

Next steps

Gateway Setup for IDEs — install and configure the gateway
Monitoring IDE AI Usage — track policy effectiveness
Troubleshooting — resolve policy-related issues

Use this page when​

Primary audience​

How IDE Traffic Differs from Chat​

Secret Redaction​

PII Redaction for Code Comments​

Cost Control Policies​

Engineering Cache for Completions​

Content Filtering on Outputs​

Minimal-Latency Policy Chain​

Separate Policies for Chat vs. Completions​

Verifying Policies​

For AI systems​

For engineers​

For leaders​

Next steps​