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 skills/soden46/engineer-flow/data-processingnpx skills add soden46/engineer-flow --skill data-processinggit clone --depth 1 https://github.com/soden46/engineer-flowWhat 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 | $0.00025 | $0.00238 |
| Opus 5 | $0.00013 | $0.00119 |
| Sonnet 5 | $0.00005 | $0.00048 |
| Haiku 4.5 | $0.00003 | $0.00024 |
Grade A, and why
data-processing 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 yesterday.
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
data-processing
Use this skill for imports, exports, transformations, batch processing, files, large datasets, and data pipelines.
Principles
Make data boundaries explicit.
Validate external data before relying on it.
For large workloads prefer bounded processing such as:
- streaming
- chunking
- pagination
- iterators
- batches
Avoid loading unbounded datasets into memory.
Define behavior for:
- malformed records
- partial failure
- retries
- duplicates
- ordering
- checkpointing
- resumability
Keep transformation logic separate from transport/storage concerns where useful.
For destructive or bulk operations, consider dry-run or preview mechanisms when appropriate.
Verify record counts and important invariants after processing.
Adaptation
Use project evidence to determine the actual language, framework, runtime, and existing conventions.
When stack-specific implementation guidance is needed, prefer project evidence, native framework or language mechanisms, and relevant user-installed specialist skills. Technology-specific guidance must not redefine or weaken the core engineering requirement.
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.
- yesterday First seen · 48 lines · 25 tokens per session scan A 1db3b51ef9c4
data-processing is a skill published in the GitHub repository soden46/engineer-flow (3 stars, last pushed 4d ago), licensed MIT. It adds 25 tokens to every session and 238 once invoked, about $0.0001 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 2026-08-31.
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