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-data-transform-lensgit 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-data-transform-lens)<a href="https://agentmods.dev/skills/onedro1d/dark-factory/df-data-transform-lens"><img src="https://agentmods.dev/badge/skills/onedro1d/dark-factory/df-data-transform-lens/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-data-transform-lens"><img src="https://agentmods.dev/badge/skills/onedro1d/dark-factory/df-data-transform-lens.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 | $0.00079 | $0.00944 |
| Opus 5 | $0.00039 | $0.00472 |
| Sonnet 5 | $0.00016 | $0.00189 |
| Haiku 4.5 | $0.00008 | $0.00094 |
Grade A, and why
df-data-transform-lens 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 8d 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 — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dark Factory — The Data-Transform Lens
Overview
An application is not a machine with features; it is a data-transformation algorithm: input data → transforms → output data, carrying state forward in time. Modelling a system this way collapses the design space and concentrates effort where the risk actually lives. Every other df-* skill is this model applied at one stage.
The model: two primitives + two tags
- Data node = a schema + its single-datum invariants, carrying context:
location— which store/system holds it now (not a trust signal).origin— where it came from (web/mobile/scan/API/another service). Travels for audit; never a trust signal.authority— is this the system-of-record for this fact? A ranking; the conflict resolver.governance— security class, retention, residency. Travels with the datum.
- Transform =
(state, inputs) → (state', outputs), tagged:pure— replayable, no marker needed.effect— irreversible world-change (send / charge / publish / notify / external write). Must carry an idempotency key (retry ≠ double-action) + a compensation path (the hand-written un-transform).
- Validation rule (tag over data) = a predicate that must hold. The only axis that changes architecture is enforcement locus:
LOCAL— checkable at one ingress/commit with all operands present → reject at the door.GLOBAL— ranges across records/systems/time → flag, then reconcile byauthority.- "Invariants" are just one species; the genus also covers parity bits, regex, Schematron, NEMSIS, double-entry.
- Authority = the resolution policy a GLOBAL failure appeals to (who wins on conflict; drives reconciliation).
Two rules that are the heart of the model
- The boundary is the data. Every input edge of every unit (function, service, DB, queue) is a boundary. Data crossing in is untrusted until validated here. Trust is non-transitive and does not travel — re-earned at every crossing. Your own services can be corrupt; a message off your own bus still gets validated.
- Authority ≠ origin. A 3rd-party (bank, exchange) can be the authoritative source-of-truth that overrides your own well-formed cached copy. "Ours vs theirs" carries zero trust signal.
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.
- 8d ago First seen · 49 lines · 79 tokens per session scan A 5e7089014bf5
df-data-transform-lens is a skill published in the GitHub repository OneDro1d/dark-factory (0 stars, last pushed today), licensed Apache-2.0. It adds 79 tokens to every session and 944 once invoked, about $0.0004 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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