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 d4rkNinja/arcforge --skill production-operationsgit clone --depth 1 https://github.com/d4rkNinja/arcforgeWrote 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/d4rkninja/arcforge/production-operations)<a href="https://agentmods.dev/skills/d4rkninja/arcforge/production-operations"><img src="https://agentmods.dev/badge/skills/d4rkninja/arcforge/production-operations.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00074 | $0.02658 |
| Opus 5 | $0.00037 | $0.01329 |
| Sonnet 5 | $0.00015 | $0.00532 |
| Haiku 4.5 | $0.00007 | $0.00266 |
Grade A, and why
production-operations 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 4d 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 — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Think Through Production Operations
Overview
Production guidance for running systems. Each reference paper captures what separates operable systems from hopeful ones: logs without correlation IDs, metrics with unbounded cardinality, health checks that pass while the system is down, audit trails that can be edited, and backups that have never been restored.
Core principle: An operational claim is only as real as its evidence. If a journey cannot be observed, an alert has no owner, or a restore has never been rehearsed, the system does not actually have that capability.
Domain Law
NO PRODUCTION-OPERATIONS CHANGE WITHOUT:
1. the minimum required primary paper(s) for the practice selected from the context table;
2. the user journey or failure the signal protects named first;
3. "Existing-codebase checks" run when changing existing telemetry;
4. every applicable MUST mapped to an enforcement point (emitter, alert,
runbook, drill) and evidence — never silently downgraded.
When to Use
Use this skill when thinking through, reviewing, changing, or verifying:
- structured logging, log levels, redaction, and retention;
- metrics, SLI selection, and cardinality limits;
- distributed tracing, context propagation, and sampling;
- health checks: liveness vs readiness, dependency depth, synthetic probes;
- audit logging: actor, action, target, immutable retention;
- async-system observability: lag, depth, backlog, poison queues;
- runbooks, escalation paths, and on-call ownership;
- incident readiness: detection, severity, communication, postmortems;
- data import pipelines with validation and quarantine;
- data export with authorization and rate control;
- backup: scope, isolation, retention, encryption;
- restore: rehearsal, RPO/RTO evidence, cross-region recovery;
- high availability topology and failover authority;
- multi-region systems, residency, and conflict policy.
When Not to Use
- Deployment ordering and zero-downtime rollout mechanics: use
migration-evolution(134, 106 pairs here). - Architecture-level SLO/SLA design and review: use
system-architecture-harness/architecture-review-gate. - Security log redaction policy ownership:
security-privacy(066) defines what is sensitive; this skill implements the emitters. - Cost modeling: use
system-architecture-harnessPhase 10.
What ships with it
18 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 295 B
- examples/worked-example-checkout-observability.md 4.3 KB
- references/papers/056-logging.md 34 KB
- references/papers/057-metrics.md 33 KB
- references/papers/058-distributed-tracing.md 35 KB
- references/papers/059-health-checks.md 32 KB
- references/papers/060-audit-logging.md 35 KB
- references/papers/074-data-import.md 30 KB
- references/papers/075-data-export.md 30 KB
- references/papers/076-backup.md 31 KB
- references/papers/077-restore.md 30 KB
- references/papers/078-disaster-recovery.md 31 KB
- references/papers/097-high-availability.md 33 KB
- references/papers/132-multi-region-systems.md 31 KB
- references/papers/133-data-residency.md 32 KB
- references/papers/137-observability-for-async-systems.md 33 KB
- references/papers/138-operational-runbooks.md 30 KB
- references/papers/139-incident-readiness.md 32 KB
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.
- 4d ago Changed · +2 lines 373966cc4570
- 8d ago First seen · 155 lines · 74 tokens per session scan A 4818659cae76
production-operations is a skill published in the GitHub repository d4rkNinja/arcforge (16 stars, last pushed 4d ago), licensed MIT. It adds 74 tokens to every session and 2,658 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 2026-08-30.
Other skills, from other repositories
code-to-diagram
Analyze codebases and automatically generate architecture diagrams, flowcharts, and org charts. Uses AST parsing to map import dependencies for Python, JS/TS, Go, and Java, outputting Mermaid or SVG files. Triggered when users ask to visualize code architecture, understand dependencies, draw a flowchart, or create a…
architecture-diagram
Dark-themed SVG architecture/cloud/infra diagrams as HTML.
studio
Architecture Studio control plane — initialize or inspect a studio workspace, create and register projects, or route an architecture/AEC task to the right agent or skill. Use when the user runs /as:studio, asks to set up or open their studio, manage its projects, or describes a task without naming a skill.
modular-skills
Build composable skill modules with hub-and-spoke loading. Use when token budget is tight.
csv-to-sif
Export a project's FF&E product-library CSV as dealer-system SIF. Use to produce a .sif schedule; use sif-to-csv for the reverse direction.
architecture-aware-init
Selects architecture paradigm via research before scaffolding. Use when architecture is undecided and the choice needs justification and documentation.