stationkeeping

A process for running software reliably in production, where production means the live environment used by customers. It covers deployment, release planning, infrastructure configuration, monitoring, alerts, service targets, incident response, capacity, cost, backups, and disaster recovery.

In plain words
What is it for?
Use it when launching a system or keeping one healthy after launch. It helps plan releases, monitor user-facing behavior, respond to incidents, control costs, and recover from outages or data loss.
Why use it?
A merged change and a passing build do not prove that a live service will remain available. Deployment settings, capacity limits, dependencies, and other operational problems can fail only after release.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/iamk77/skill/stationkeeping
Any agent
npx skills add IamK77/Skill --skill stationkeeping
Clone the repo
git clone --depth 1 https://github.com/IamK77/Skill

Made for: Claude Code, Codex.

Per session 227 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,731 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00227 $0.04731
Opus 5 $0.00113 $0.02365
Sonnet 5 $0.00045 $0.00946
Haiku 4.5 $0.00023 $0.00473

Measured 2d ago against content hash 972e633455dd, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

stationkeeping 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 2d 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.

skills/engineering/stationkeeping/SKILL.md · 192 lines

How it starts

The opening of the file, as written. The whole thing — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.

stationkeeping

!checklist init ${CLAUDE_SKILL_DIR} --force

A merged PR and a green pipeline are not the finish line — they are the moment the real work starts. Software's life is not in the repository; it is in production, running and serving users, continuously and under stress. And the lesson written in every incident review is that most outages are not a logic bug that tests would have caught — they are a deployment, configuration, capacity, or dependency failure that only exists once the thing is live. This skill is the discipline of getting a system into production safely and keeping it healthy there, across seven gated stages, and it will not advance past a GATE until the checklist tool clears it.

Operations is where the agent era bites hardest, because the agent's blind spots map exactly onto how production kills you:

  • The agent equates green with done — a green dashboard reads as "safe," and silence reads as "healthy." But a system can be perfectly green on every machine metric while users are failing; absence of signal is not absence of failure. Monitoring must watch what the user experiences, and make the absence of a thing a signal in its own right.
  • The agent has no 3am dread and no memory between sessions — it will not feel an un-actionable page, and it cannot "remember how we fixed this last time." So incident response must be externalized into runbooks and blameless postmortems, and alerts must each be worth waking a human for.
  • The agent takes the cheapest path to green — facing a noisy alert it silences the alert; facing load it scales up (and blows the budget) instead of diagnosing; facing a broken prod box it patches it live, breeding a snowflake no one can reproduce.
  • The agent feels no friction leaking or over-granting — it will log a secret or PII, or grant broad permissions, to make something work.

So the same rule that governs the rest of the suite governs production: a property you do not encode as a rehearsed, automated, hard-to-game control is one the agent will violate while everything looks fine. Stationkeeping is the active, continuous work of holding a live system on station — against drift, failure, load, and attack — not a thing you do once at launch.

Discipline: finish every GATE before the next stage. GATEs are hard — never skip, batch past, or self-certify a stage you have not done. The checklist tool enforces the order; let it. Commands address stages by name.

Read references/agent-era-shifts.md first — it is the heart: what each operational practice becomes once production is operated by something that reads green as safety, silence as health, forgets every incident between sessions, and takes the cheapest path to a quiet dashboard. If $ARGUMENTS is a throwaway with no users and nothing to lose, this machinery is overkill — say so. The leanest sufficient operational floor is the goal, matched to blast radius, not maximum ceremony.

Speak the user's language, or the reliability target gets set blind. This skill commits the user to operational burdens their team will carry at 3am — an SLO they must defend, an on-call rotation, a budget. Only they can set how reliable is enough and what an outage costs. Read their fluency and gloss a term on first use (SLO, error budget, canary, blue-green, RTO/RPO, the golden signals, a runbook). A user who signs off on a "99.95% SLO" they never parsed has not set the target — and the CALIBRATE and RELIABILITY judgments this skill leans on them for are then hollow.

Read the full file on GitHub · 192 lines

Changes

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.

  1. 2d ago First seen · 192 lines · 227 tokens per session scan A 972e633455dd

Subscribe to this mod's changes

stationkeeping is a skill published in the GitHub repository IamK77/Skill (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 227 tokens to every session and 4,731 once invoked, about $0.0011 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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