Codex bedrock

You are an autonomous setup agent for OpenAI Codex on Amazon Bedrock. Do NOT ask the user questions. Detect the environment, apply the right configuration, and verify it works end-to-end.

TARGET: $ARGUMENTS

============================================================ CONTEXT — what changed on June 1, 2026

OpenAI GPT-5.5, GPT-5.4, and the Codex coding agent went GA on Amazon Bedrock. Key facts that drive this skill's decisions:

• Authentication: Bedrock API key (AWS_BEARER_TOKEN_BEDROCK) or standard AWS SDK credential chain (IAM roles, instance profiles, ECS task roles, SSO)
• API surface: Responses API only (not Chat Completions)
• Regional availability at GA:
  • GPT-5.5: us-east-1 (N. Virginia) + us-east-2 (Ohio)
  • GPT-5.4: us-east-2 (Ohio) + us-west-2 (Oregon)
• Pricing: pure per-token, no seat licenses, applies to AWS EDP/cloud commitments
• Data residency: all processing stays within selected Bedrock region
• Queue-not-reject under high demand (design timeouts accordingly)

============================================================ PHASE 1: ENVIRONMENT DISCOVERY

1. CHECK EXISTING AWS CREDENTIALS

   • Run aws sts get-caller-identity to verify active credentials
   • If it fails, check for AWS_BEARER_TOKEN_BEDROCK env var instead
   • Inspect ~/.aws/credentials and ~/.aws/config for profile names
   • Check if running in EC2/ECS/Lambda (instance profile may be active)
   • Check for existing Codex config at ~/.codex/config.json or .codex/ in repo

2. DETECT CODEX CLI VERSION

   • Run codex --version; if not installed, note the install command
   • Check for VS Code extensions: code --list-extensions | grep -i codex
   • Check for .vscode/settings.json with codex.provider config
   • Check package.json devDependencies for @openai/codex-sdk

3. ASSESS NETWORK PATH

   • Check if VPC endpoint exists: aws ec2 describe-vpc-endpoints --filters Name=service-name,Values=com.amazonaws.*.bedrock
   • If no VPC endpoint found, recommend creating one (instructions in Phase 3)
   • Check /etc/hosts and proxy env vars for any OpenAI endpoint overrides

4. IDENTIFY EXISTING OPENAI USAGE

   • Grep for OPENAI_API_KEY, openai.com, /chat/completions, createCompletion
   • These signal Chat Completions usage that needs migration to Responses API
   • List all files that will need updating

============================================================ PHASE 2: CREDENTIAL CONFIGURATION

Choose the right auth path based on Phase 1 findings:

PATH A: Bedrock API Key (preferred for developer machines)

# Generate in AWS Console → Amazon Bedrock → API Keys
# Store securely — do not commit to version control

# Add to shell profile (~/.zshrc or ~/.bashrc):
export AWS_BEARER_TOKEN_BEDROCK="<bedrock-api-key>"

# Verify:
curl "https://bedrock-runtime.us-east-2.amazonaws.com/model/gpt-5.5/responses" \
  -H "Authorization: Bearer $AWS_BEARER_TOKEN_BEDROCK" \
  -H "Content-Type: application/json" \
  -d '{"model":"gpt-5.5","input":"ping"}'

PATH B: AWS SDK Credential Chain (preferred for CI/CD + production)

# No additional credential setup if AWS env is already configured.
# Confirm the chain resolves:
aws sts get-caller-identity

# The Codex CLI picks up the chain automatically when AWS_BEARER_TOKEN_BEDROCK
# is not set. Ensure the IAM role/user has these permissions:
# - bedrock:InvokeModel
# - bedrock:InvokeModelWithResponseStream
# - bedrock:GetFoundationModel

IAM policy (minimum required):

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "bedrock:InvokeModel",
        "bedrock:InvokeModelWithResponseStream"
      ],
      "Resource": [
        "arn:aws:bedrock:us-east-1::foundation-model/gpt-5.5",
        "arn:aws:bedrock:us-east-2::foundation-model/gpt-5.5",
        "arn:aws:bedrock:us-east-2::foundation-model/gpt-5.4",
        "arn:aws:bedrock:us-west-2::foundation-model/gpt-5.4"
      ]
    }
  ]
}

VERIFY CONNECTIVITY

# Quick connectivity check — should return model metadata
aws bedrock get-foundation-model \
  --model-identifier gpt-5.5 \
  --region us-east-2

============================================================ PHASE 3: VPC ENDPOINT (production / regulated environments)

Skip this phase if: running on a developer machine not in a VPC, or if the aws ec2 describe-vpc-endpoints check in Phase 1 found an existing endpoint.

Proceed if: regulated industry (HIPAA, SOC 2), internal security policy requires traffic to stay off the public internet, or running in ECS/EKS.

# 1. Find the right VPC and subnet
aws ec2 describe-vpcs --query 'Vpcs[*].[VpcId,Tags[?Key==`Name`].Value]'
aws ec2 describe-subnets --filters Name=vpc-id,Values=<VPC_ID> \
  --query 'Subnets[*].[SubnetId,AvailabilityZone,Tags[?Key==`Name`].Value]'

# 2. Create a security group for the endpoint
aws ec2 create-security-group \
  --group-name bedrock-endpoint-sg \
  --description "Allow HTTPS to Bedrock VPC endpoint" \
  --vpc-id <VPC_ID>

aws ec2 authorize-security-group-ingress \
  --group-id <SG_ID> \
  --protocol tcp \
  --port 443 \
  --source-group <YOUR_APP_SG_ID>

# 3. Create the interface endpoint
aws ec2 create-vpc-endpoint \
  --vpc-id <VPC_ID> \
  --service-name com.amazonaws.us-east-2.bedrock-runtime \
  --vpc-endpoint-type Interface \
  --subnet-ids <SUBNET_IDS> \
  --security-group-ids <SG_ID> \
  --private-dns-enabled

# 4. Verify DNS resolves inside VPC (run from an instance in the VPC)
nslookup bedrock-runtime.us-east-2.amazonaws.com
# Should resolve to a 10.x.x.x address, not a public IP

============================================================ PHASE 4: IDE + CLI WIRING

Codex CLI global config

# ~/.codex/config.json — created if absent
codex config set provider bedrock
codex config set region us-east-2
codex config set model gpt-5.5

# Verify:
codex config get

VS Code

Add to .vscode/settings.json (project level) or settings.json (user level):

{
  "codex.provider": "bedrock",
  "codex.region": "us-east-2",
  "codex.model": "gpt-5.5",
  "codex.timeout": 120000
}

JetBrains (IntelliJ / WebStorm / PyCharm)

Settings → Tools → Codex → Provider: bedrock, Region: us-east-2

The JetBrains plugin reads the same AWS credential chain as the CLI. No additional configuration needed if Path B was used in Phase 2.

Xcode

Codex → Preferences → Inference Provider → Amazon Bedrock. Enter the region; credentials are read from the macOS Keychain item com.openai.codex.bedrock (set via codex auth bedrock).

============================================================ PHASE 5: RESPONSES API MIGRATION

Run this phase only if Phase 1 found Chat Completions usage (/chat/completions, createChatCompletion, ChatCompletionMessage).

Key differences between Chat Completions and Responses API:

Aspect	Chat Completions	Responses API
State mgmt	Client-side (messages[])	Model-managed (thread_id)
Tool calls	Manual round-trip	Hosted tools
Streaming	SSE chunks	SSE events (new format)
Bedrock support	NOT supported	GA June 2026

Migration pattern:

# BEFORE — Chat Completions (not available on Bedrock)
response = client.chat.completions.create(
    model="gpt-5.5",
    messages=[{"role": "user", "content": prompt}]
)
answer = response.choices[0].message.content

# AFTER — Responses API on Bedrock
import boto3
import json

bedrock = boto3.client("bedrock-runtime", region_name="us-east-2")

response = bedrock.invoke_model(
    modelId="gpt-5.5",
    body=json.dumps({"input": prompt, "model": "gpt-5.5"}),
    contentType="application/json",
    accept="application/json",
)
body = json.loads(response["body"].read())
answer = body["output"]["text"]

For TypeScript:

// AWS SDK v3
import { BedrockRuntimeClient, InvokeModelCommand } from "@aws-sdk/client-bedrock-runtime";

const client = new BedrockRuntimeClient({ region: "us-east-2" });
const command = new InvokeModelCommand({
  modelId: "gpt-5.5",
  body: JSON.stringify({ model: "gpt-5.5", input: prompt }),
  contentType: "application/json",
  accept: "application/json",
});
const response = await client.send(command);
const body = JSON.parse(new TextDecoder().decode(response.body));
const answer = body.output.text;

============================================================ PHASE 6: COST MODELING

Per-token pricing on Bedrock (check current rates at AWS pricing page):

• GPT-5.5 input: check AWS pricing for current rate per 1K tokens
• GPT-5.5 output: check AWS pricing for current rate per 1K tokens
• Applies to existing EDP/cloud commitment drawdowns — no incremental spend if you have headroom in an existing commitment

Estimate monthly cost:

# Rough estimate: typical Codex session = 50K input + 10K output tokens
# Team of 10, 3 sessions/day, 22 working days = 660 sessions/month
# Multiply by your per-token rates from the AWS pricing page
# Compare against current seat-license spend

# To see actual usage:
aws cloudwatch get-metric-statistics \
  --namespace AWS/Bedrock \
  --metric-name InvocationLatency \
  --dimensions Name=ModelId,Value=gpt-5.5 \
  --start-time $(date -u -d '7 days ago' +%Y-%m-%dT%H:%M:%SZ) \
  --end-time $(date -u +%Y-%m-%dT%H:%M:%SZ) \
  --period 86400 \
  --statistics Sum

Timeout design for queued requests:

• Set Codex CLI / SDK timeout ≥ 120 seconds for long-horizon sessions
• Do not retry immediately on timeout — use exponential backoff (2s, 4s, 8s)
• Add jitter (±20%) to prevent thundering herd during demand spikes

============================================================ OUTPUT

Codex on Bedrock Setup Report

Environment

• AWS credentials: [PATH A (API key) | PATH B (SDK chain) | MISSING]
• Active identity: [ARN from sts get-caller-identity, or "API key"]
• Codex CLI version: [version or "not installed"]
• IDE extensions: [list or "none detected"]

Connectivity

• GPT-5.5 endpoint: [REACHABLE | UNREACHABLE | NOT TESTED]
• VPC endpoint: [EXISTS | CREATED | NOT APPLICABLE | RECOMMENDED]
• Region: [selected region]

Migrations Required

• Chat Completions → Responses API: [N files, list them]
• Files updated: [list]

Configuration Written

• Codex CLI config: [path]
• IDE settings: [paths]
• IAM policy: [attached to role X | manual action required]

Estimated Monthly Cost

• Sessions/month: [estimate or "provide usage for estimate"]
• Per-token estimate: [$ range or "check AWS pricing page"]
• vs. seat license: [comparison if baseline provided]

Remaining Actions

• [anything requiring console access, human approval, or external confirmation]
• [FedRAMP / HIPAA: confirm with AWS account team before routing regulated data]