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 skills add vaquarkhan/data-engineering-agent-skills --skill source-reliability-and-extraction-resiliencegit 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/skills/vaquarkhan/data-engineering-agent-skills/source-reliability-and-extraction-resilience)<a href="https://agentmods.dev/skills/vaquarkhan/data-engineering-agent-skills/source-reliability-and-extraction-resilience"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/source-reliability-and-extraction-resilience/github.svg" alt="Measured on agentmods" height="20"></a>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.
<a href="https://agentmods.dev/skills/vaquarkhan/data-engineering-agent-skills/source-reliability-and-extraction-resilience"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/source-reliability-and-extraction-resilience.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00048 | $0.00438 |
| Opus 5 | $0.00024 | $0.00219 |
| Sonnet 5 | $0.00010 | $0.00088 |
| Haiku 4.5 | $0.00005 | $0.00044 |
Grade A, and why
source-reliability-and-extraction-resilience 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 9d 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
Source Reliability And Extraction Resilience
Overview
Use this skill when the real risk is upstream instability rather than downstream modeling. It helps agents design safe ingestion behavior around outages, late data, flaky responses, inconsistent source states, and operational dependencies.
When to Use
- unstable upstream systems
- intermittent extraction failures
- delayed source availability
- rate-limited or timeout-prone sources
- ingestion designs that must survive source incidents
Do not assume source availability is constant just because the contract exists.
Workflow
-
Characterize the upstream failure modes. Include:
- outages
- late availability
- inconsistent snapshots
- timeout behavior
- partial responses
-
Define safe extraction behavior. Decide:
- retry policy
- timeout handling
- quarantine behavior
- when to fail closed versus publish partial data
-
Add observability around the source, not only the pipeline.
-
Bound replay and catchup behavior for upstream recovery scenarios.
-
Document human-operable recovery steps.
Common Rationalizations
| Rationalization | Reality |
|---|---|
| "The source team says it is reliable." | Reliability claims still need runtime evidence and safe fallback behavior. |
| "We can just retry more." | More retries can worsen load, mask incidents, or still produce partial bad state. |
| "Partial data is better than stale data." | That depends on the business contract and must be explicit. |
Red Flags
- no documented source failure modes
- partial-source behavior is undefined
- the pipeline can publish partial data without warning
- source recovery depends on tribal knowledge
Verification
- Upstream failure modes are characterized
- Extraction and publish behavior under failure is explicit
- Source health is observable separately from downstream success
- Recovery and catchup rules are documented
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.
- 9d ago First seen · 66 lines · 48 tokens per session scan A d2e4639621d2
source-reliability-and-extraction-resilience is a skill published in the GitHub repository vaquarkhan/data-engineering-agent-skills (45 stars, last pushed 3mo ago), licensed MIT. It adds 48 tokens to every session and 438 once invoked, about $0.0002 per session on Opus 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.
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