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.
npx agentmods add commands/vaquarkhan/data-engineering-agent-skills/backfillgit clone --depth 1 https://github.com/vaquarkhan/data-engineering-agent-skillsWrote 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.
[](https://agentmods.dev/commands/vaquarkhan/data-engineering-agent-skills/backfill)<a href="https://agentmods.dev/commands/vaquarkhan/data-engineering-agent-skills/backfill"><img src="https://agentmods.dev/badge/commands/vaquarkhan/data-engineering-agent-skills/backfill.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.00176 |
| Opus 5 | $0.00000 | $0.00088 |
| Sonnet 5 | $0.00000 | $0.00035 |
| Haiku 4.5 | $0.00000 | $0.00018 |
Grade A, and why
backfill 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 5d 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.
What it actually says
/backfill
Use replay-safe workflows before rerunning, replaying, or cutting over data.
Checklist:
- load
safe-backfill-and-replay-orchestrationfirst — drafttemplates/backfill-plan.yamlbefore any execution - run
hooks/backfill-guard.shorhooks/backfill-guard.ps1when available - load
orchestration-and-backfillsfor schedule, retry, and dependency semantics - load
data-migration-and-platform-cutoverfor cutovers or dual-run changes - load
data-reconciliation-and-financial-controlswhen correctness must be proven after replay - load
mcp-data-observability-integrationwhen live lag or run state should inform the replay window - define the affected window, rollback path, and reconciliation gates before execution
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.
- 5d ago First seen · 14 lines · 0 tokens per session scan A 6a4e1654a2f7
backfill is a command published in the GitHub repository vaquarkhan/data-engineering-agent-skills (40 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 176 tokens. 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 2026-08-30.
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