Bedrock ops
Bedrock KB + S3 data pipeline management with safety guardrails. S3 sync (with force-upload for content-only changes), KB ingestion status polling, cost monitoring. Enforces identity verification, dry-run, and confirmation for all write operations.From its SKILL.md
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SKILL.md
5.5 KB, ~1.4k tokens by cl100k_base, as published. Nobody here has run it
Bedrock Ops Skill
Safely manage the RAG data pipeline: S3 uploads, Bedrock KB ingestion, session management.
Setup
First time per project
# 1. Generate aws-project.json (lists available profiles, generates config)
uv run python SKILLS_DIR/scripts/setup_project.py <profile-name> [s3-bucket]
# 2. Create aws-project.local.json with your TOTP secret
echo '{"totp_secret": "YOUR_BASE32_SECRET", "mfa_serial": "YOUR_MFA_ARN"}' > aws-project.local.json
Verify setup
# Check session and identity
uv run --with pyotp,boto3 python SKILLS_DIR/scripts/session.py ensure
Commands
All commands are handled by Claude interpreting the user's intent and routing to the appropriate script.
Identity & Session
| Intent | Implementation |
|---|---|
/bedrock-ops setup | Run uv run python SKILLS_DIR/scripts/setup_project.py to list profiles, then generate config |
/bedrock-ops verify | Run uv run --with pyotp,boto3 python SKILLS_DIR/scripts/session.py check |
/bedrock-ops session | Run uv run --with pyotp,boto3 python SKILLS_DIR/scripts/session.py ensure |
S3 Operations
| Intent | Implementation |
|---|---|
/bedrock-ops s3 ls [path] | Run uv run --with pyotp,boto3 python SKILLS_DIR/scripts/aws_safe.py s3 ls s3://<bucket>/<path> |
/bedrock-ops s3 sync <local> <s3> | Run uv run --with pyotp,boto3 python SKILLS_DIR/scripts/aws_safe.py s3 sync <local> <s3> (dry-run first, add --execute for real) |
/bedrock-ops s3 force-upload <local> <s3> | Use aws s3 cp --recursive instead of sync — required when only file content changed but byte count is the same (e.g. after adding chunk anchors). Run uv run --with pyotp,boto3 python SKILLS_DIR/scripts/aws_safe.py s3 cp <local> s3://<bucket>/ --recursive (dry-run first, add --execute for real) |
/bedrock-ops s3 upload <file> [s3path] | Run uv run --with pyotp,boto3 python SKILLS_DIR/scripts/aws_safe.py s3 cp <file> s3://<bucket>/<path> |
/bedrock-ops s3 download <s3path> [local] | Run uv run --with pyotp,boto3 python SKILLS_DIR/scripts/aws_safe.py s3 cp s3://<bucket>/<path> <local> |
Cost & Resources
| Intent | Implementation |
|---|---|
/bedrock-ops cost | Run uv run --with pyotp,boto3 python SKILLS_DIR/scripts/aws_safe.py ce get-cost-and-usage --time-period Start=$(date -v1d +%Y-%m-%d),End=$(date +%Y-%m-%d) --granularity MONTHLY --metrics UnblendedCost --group-by Type=DIMENSION,Key=SERVICE |
/bedrock-ops resources ec2 | Run uv run --with pyotp,boto3 python SKILLS_DIR/scripts/aws_safe.py ec2 describe-instances --query 'Reservations[].Instances[].{Id:InstanceId,Type:InstanceType,State:State.Name,Name:Tags[?Key==\Name`].Value |
/bedrock-ops resources s3 | Run uv run --with pyotp,boto3 python SKILLS_DIR/scripts/aws_safe.py s3 ls |
/bedrock-ops resources lambda | Run uv run --with pyotp,boto3 python SKILLS_DIR/scripts/aws_safe.py lambda list-functions --query 'Functions[].{Name:FunctionName,Runtime:Runtime,Memory:MemorySize}' |
Bedrock Knowledge Bases
| Intent | Implementation |
|---|---|
/bedrock-ops kb list | Run uv run --with pyotp,boto3 python SKILLS_DIR/scripts/aws_safe.py bedrock-agent list-knowledge-bases |
/bedrock-ops kb sync <kb-id> | Auto-detect data source ID, then run uv run --with pyotp,boto3 python SKILLS_DIR/scripts/aws_safe.py bedrock-agent start-ingestion-job --knowledge-base-id <kb-id> --data-source-id <ds-id> --execute |
/bedrock-ops kb status <kb-id> | Poll ingestion job status. Run aws bedrock-agent list-ingestion-jobs --knowledge-base-id <kb-id> --data-source-id <ds-id> --profile personal-session --region ap-northeast-1 --query 'ingestionJobSummaries[0].{status:status,started:startedAt,updated:updatedAt,stats:statistics}' --output json. Repeat every 15 seconds until status is COMPLETE or FAILED. Print elapsed time. |
Arbitrary Command
| Intent | Implementation |
|---|---|
/bedrock-ops exec <args> | Run uv run --with pyotp,boto3 python SKILLS_DIR/scripts/aws_safe.py <args> |
Safety Rules (ALWAYS enforced by aws_safe.py)
- Identity check: Before any write operation,
sts get-caller-identitymust matchaccount_idinaws-project.json. Abort on mismatch. - Explicit profile: Every command uses
--profilefrom config. Never rely on env vars or default. - Dry-run first: For s3 sync/cp/mv, always
--dryrunfirst. Show output. User must confirm with--execute. - No silent deletes:
--deleteand destructive operations blocked unless--i-understand-this-deletesis passed. - Service blocklist: Respect
safety.denied_servicesin aws-project.json (default: iam, organizations). - Confirmation banner: Before write ops, display profile, account ID, command, and mode (dry-run/live).
- Session auto-refresh: If session expired, auto-regenerate using TOTP from aws-project.local.json.
Config Files
aws-project.json(project root, committed) — profile, account_id, safety rules, defaultsaws-project.local.json(project root, gitignored) — totp_secret, mfa_serial, personal overrides
Path Variables
SKILLS_DIR=.claude/skills/bedrock-ops
What ships with it: 4 files
24.5 KB alongside SKILL.md, 4 of them executable
scripts/
- aws_safe.pyruns10.1 KB
- session.pyruns7.9 KB
- setup_project.pyruns4.6 KB
- totp.pyruns1.9 KB