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 OneDro1d/dark-factory --skill df-infrastructuregit clone --depth 1 https://github.com/OneDro1d/dark-factoryWrote 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/onedro1d/dark-factory/df-infrastructure)<a href="https://agentmods.dev/skills/onedro1d/dark-factory/df-infrastructure"><img src="https://agentmods.dev/badge/skills/onedro1d/dark-factory/df-infrastructure/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/onedro1d/dark-factory/df-infrastructure"><img src="https://agentmods.dev/badge/skills/onedro1d/dark-factory/df-infrastructure.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 | $0.00064 | $0.00605 |
| Opus 5 | $0.00032 | $0.00302 |
| Sonnet 5 | $0.00013 | $0.00121 |
| Haiku 4.5 | $0.00006 | $0.00060 |
Grade A, and why
df-infrastructure 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.
How it starts
The opening of the file, as written. The whole thing — 31 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dark Factory — Infrastructure Architect (where data lives + the boundaries)
Overview
Infra decides where the architecture runs and makes it deployable across all environments. It produces one must-have output: the Deployment & Infrastructure Spec. Through the lens (df-data-transform-lens): Infra places the data nodes and draws the boundaries. Runs in parallel with the Developer lane.
When to use
Deploying across DTAP, provisioning clusters/secrets/network/storage, wiring observability sinks + operational knobs, or enforcing runtime trust.
What Infra does
locationper data node → storage class, region, residency. Thegovernancetag (PHI/PII, residency) is enforced by where you put the data.- Every unit edge is a trust boundary. "Inside the cluster is trusted" is the sticky-trust anti-pattern. Secrets/IAM enforce the boundary, not network position. Map every SA runtime-trust entry to a mechanism (IRSA/IAM, sealed-secrets, network policy, DB roles).
- Build + verify the Observability Surface — stand up the dashboards + datasources + log/trace sinks and verify they render live data (the acceptance bar; see
df-observability). Ship dashboards as code (deployments/grafana/…), not hand-clicked. - Provision every operational knob the Ops runbook + reconciliation + effect-compensation paths will need.
Reversibility (the autonomy gate)
Building manifests is reversible and high-autonomy; applying them to production is irreversible → a human gate regardless of how green the evidence is (see df-adversary-gate / the two-axis autonomy model). A production change requires a ticket + announcement.
Instructions
- Start from the platform's standard environment progression (Dev → Test → Acceptance → Production), base + overlays. Record per-product deltas only.
- Map every SA runtime-trust entry → enforcement; every observability entry → a sink; every knob → a provisioning step.
- Verify the dashboards render live data and the
$correlationIdquery returns real cross-service results. - Write the deploy procedure QA follows to stand the system up.
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 · 31 lines · 64 tokens per session scan A 6d9e3d7a191c
df-infrastructure is a skill published in the GitHub repository OneDro1d/dark-factory (0 stars, last pushed yesterday), licensed Apache-2.0. It adds 64 tokens to every session and 605 once invoked, about $0.0003 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 2026-09-01.
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