Agent skill

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.

View SKILL.md on GitHub Repository
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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/bedrock-ops

SKILL.md

Bedrock Ops Skill

Safely manage the RAG data pipeline: S3 uploads, Bedrock KB ingestion, session management.

Setup

First time per project

bash
# 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

bash
# 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)

  1. Identity check: Before any write operation, sts get-caller-identity must match account_id in aws-project.json. Abort on mismatch.
  2. Explicit profile: Every command uses --profile from config. Never rely on env vars or default.
  3. Dry-run first: For s3 sync/cp/mv, always --dryrun first. Show output. User must confirm with --execute.
  4. No silent deletes: --delete and destructive operations blocked unless --i-understand-this-deletes is passed.
  5. Service blocklist: Respect safety.denied_services in aws-project.json (default: iam, organizations).
  6. Confirmation banner: Before write ops, display profile, account ID, command, and mode (dry-run/live).
  7. 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, defaults
  • aws-project.local.json (project root, gitignored) — totp_secret, mfa_serial, personal overrides

Path Variables

  • SKILLS_DIR = .claude/skills/bedrock-ops

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