safe-backfill-and-replay-orchestration

safe-backfill-and-replay-orchestration is a skill for Claude Code, Codex from vaquarkhan/data-engineering-agent-skills. It costs 61 tokens per session (1,005 once invoked), scanned A, original, MIT.

A planning guide for rerunning historical data processing or rebuilding a past time range. A backfill recomputes older data, while a replay processes the same events or partitions again.

In plain words
What is it for?
It is for backfills, historical reprocessing, failed publish windows, incident recovery, and migrations that temporarily process overlapping data ranges.
Why use it?
Unplanned reruns can count records twice, overwrite trusted results, or damage downstream reports. This requires bounded work, reconciliation checks, approval gates, and a way to roll back before execution.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It is for backfills, historical reprocessing, failed publish windows, incident recovery, and migrations that temporarily process overlapping data ranges.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/vaquarkhan/data-engineering-agent-skills/safe-backfill-and-replay-orchestration
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add vaquarkhan/data-engineering-agent-skills --skill safe-backfill-and-replay-orchestration
Clone the repo
git clone --depth 1 https://github.com/vaquarkhan/data-engineering-agent-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for safe-backfill-and-replay-orchestration

README.md
[![agentmods](https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/safe-backfill-and-replay-orchestration/github.svg)](https://agentmods.dev/skills/vaquarkhan/data-engineering-agent-skills/safe-backfill-and-replay-orchestration)
Your own site
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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for safe-backfill-and-replay-orchestration

Your own site · 80×15
<a href="https://agentmods.dev/skills/vaquarkhan/data-engineering-agent-skills/safe-backfill-and-replay-orchestration"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/safe-backfill-and-replay-orchestration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,005 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00061 $0.01005
Opus 5.5 $0.00024 $0.00402
Sonnet 5.5 $0.00012 $0.00201
Haiku 4.5 $0.00006 $0.00101

Measured 2mo ago against content hash 756cfd872322, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

safe-backfill-and-replay-orchestration scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/safe-backfill-and-replay-orchestration/SKILL.md · 110 lines

How it starts

The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Safe Backfill And Replay Orchestration

Overview

Backfills are among the highest-risk data engineering operations. Agents that rerun jobs without bounded windows, publish gates, or reconciliation checks routinely cause double-counting, corrupted metrics, and downstream trust loss. This skill blocks execution until a written replay plan, rollback path, and validation gates exist.

When to Use

  • running /backfill or any historical reprocessing request
  • repairing a failed or partial publish window
  • replaying events or partitions after an incident
  • changing transformation logic that requires recomputation
  • cutting over to new pipeline behavior with overlapping data windows

Always load this skill before orchestration-and-backfills execution steps. Treat plan approval as a hard gate, not a suggestion.

Workflow

  1. Stop before execution. Do not trigger reruns, delete partitions, or open publish paths until the replay plan is drafted and reviewed.

  2. Run the backfill guard hook when available. Execute hooks/backfill-guard.sh or hooks/backfill-guard.ps1 before planning destructive or wide-impact replay work.

  3. Draft the replay plan from templates/backfill-plan.yaml. Require explicit values for:

    • affected time window and partitions
    • source of truth and downstream targets
    • execution mode (replay, merge, overwrite) and idempotency proof
    • publish pause state and downstream notifications
    • rollback strategy in plain language
    • validation checks with thresholds
    • required approvals
  4. Separate incremental from backfill semantics. Confirm:

    • concurrency limits differ from daily runs when needed
    • watermark or cursor behavior will not skip or duplicate late data
    • metric definitions remain comparable across the replay window
    • downstream consumers know publish is paused
  5. Define reconciliation gates before reopening publish. Load data-reconciliation-and-financial-controls when correctness must be proven. Minimum gates:

    • row count or volume parity within threshold
    • duplicate check on business keys
    • metric reconciliation for business-critical aggregates
    • contract checks on schema and nullability

Read the full file on GitHub · 110 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2mo ago First seen · 110 lines · 61 tokens per session scan A 756cfd872322

Subscribe to this mod's changes

safe-backfill-and-replay-orchestration is a skill published in the GitHub repository vaquarkhan/data-engineering-agent-skills (62 stars, last pushed 4mo ago), licensed MIT. It adds 61 tokens to every session and 1,005 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

safe-backfill-and-replay-orchestration compared with skills from other repositories

safe-backfill-and-replay-orchestration next to 6 skills from other repositories
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