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-observabilitygit 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-observability)<a href="https://agentmods.dev/skills/onedro1d/dark-factory/df-observability"><img src="https://agentmods.dev/badge/skills/onedro1d/dark-factory/df-observability/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-observability"><img src="https://agentmods.dev/badge/skills/onedro1d/dark-factory/df-observability.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 | $0.00075 | $0.00707 |
| Opus 5 | $0.00037 | $0.00353 |
| Sonnet 5 | $0.00015 | $0.00141 |
| Haiku 4.5 | $0.00007 | $0.00071 |
Grade A, and why
df-observability 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 — 34 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dark Factory — Observability Standard (the agents' eyes)
Overview
Observability is the sensory apparatus the agents use to build, deploy, and test — not optional garnish. Emitting telemetry is necessary but not sufficient: a :9090/metrics endpoint nobody can see is not observability. This standard makes the consumable surface a named, verified deliverable.
Rule of thumb: if an agent cannot answer "did scenario TS-0x run, and where did it succeed or fail?" by looking at a dashboard or running one query, the system is not observable yet — no matter how many metrics it emits.
The three legs — Emit → Surface → Act
| Leg | Question | Owner | Artifact |
|---|---|---|---|
| Emit | Is telemetry produced? | Developer (service anatomy) | :9090/metrics, JSON logs w/ correlationId, :8080/healthz, DLQ depth |
| Surface | Can a human/agent see and query it? | SA designs · Infra builds · QA verifies | dashboards + queryable log/trace views that render live data (the historically missing leg) |
| Act | Does it fire before customers notice? | SA names · Infra wires | alerts → a sink |
Emission is platform default (deltas only). Surface is product-specific and must be delivered + verified — that is the gap this standard closes.
Required baseline dashboard set (the floor)
Flow/saga (end-to-end path of each PO scenario) · Throughput · Tiered failure log filtered by the log level field ("level":"ERROR"), not a substring (?i)error (substring matching floods false positives from name collisions) · Correlation/trace lookup (a $correlationId variable pulling every log + span across services) · DLQ + queue depth · Latency (p50/p95/p99) · System health. Panels keyed to PO scenarios.
The acceptance bar — "verified rendering live data"
A dashboard that POSTs valid JSON but shows "No data" is not delivered. Every view reachable at a known URL; every panel renders live data (against the datasource, not just schema-valid); $correlationId returns real cross-service results; every alert rule evaluates. Verification is by observation, not assertion.
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 · 34 lines · 75 tokens per session scan A bfd450fe168f
df-observability is a skill published in the GitHub repository OneDro1d/dark-factory (0 stars, last pushed today), licensed Apache-2.0. It adds 75 tokens to every session and 707 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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