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 agentmods add skills/mvschwarz/openrig/rig-lifecyclenpx skills add mvschwarz/openrig --skill rig-lifecyclegit clone --depth 1 https://github.com/mvschwarz/openrigWhat 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 | $0.00108 | $0.01361 |
| Opus 5 | $0.00054 | $0.00681 |
| Sonnet 5 | $0.00022 | $0.00272 |
| Haiku 4.5 | $0.00011 | $0.00136 |
Grade A, and why
rig-lifecycle 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 3d 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rig Lifecycle
The family of operations that create, start, stop, resume, restore, snapshot, release, unclaim, and destroy OpenRig-managed topologies. Includes the user story after reboot: "bring my work back without turning a clean recovery into a cleanup project."
If lifecycle is brittle, every higher-level primitive inherits that brittleness. Queue, workflow, seat continuity, cross-host operation, and RSI all assume that rigs and seats can be restored into known states.
Use this when
- Operating
rig up / down / restore / resume / snapshot / release / unclaim / destroy - Reading
rig psafter a reboot or recovery and deciding what to trust - Designing proof for a lifecycle scenario (clean start / warm resume / host reboot / provider auth loss / partial boot / operator recovery)
- Reasoning about restore-outcome semantics (
resumed/rebuilt/fresh/failed/attention_required) - Auditing whether a lifecycle proof is in-process bedrock vs requires real reboot evidence
Don't use this when
- The operation is single-command and deterministic — use
openrig-userskill for CLI surface - The work is operator-level configuration of OpenRig itself — use
openrig-operator - The work is rig spec authoring — use
openrig-architect
Failure modes (4)
- Auto-restore creates a partially restored rig that must be cleaned up before real recovery. Partial restore looks like recovery but isn't; cleanup-before-recovery becomes the actual workload.
rig psor lifecycle projections report a healthier state than the runtime actually has. Projections are summaries; the runtime is truth. Don't trust projections silently.- Provider auth is unavailable after reboot and the system treats that as implementation work instead of a human/environment decision. Auth issues are environmental; route to human.
- Resume succeeds for one runtime/provider but fails for another scenario that was never tested. Per-runtime parity assumptions break silently; matrix proof catches them.
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.
- 3d ago First seen · 128 lines · 108 tokens per session scan A 8346e01d5327
rig-lifecycle is a skill published in the GitHub repository mvschwarz/openrig (64 stars, last pushed 3d ago), licensed Apache-2.0. It adds 108 tokens to every session and 1,361 once invoked, about $0.0005 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
autoprompt
Explicit-only useful-first orchestration. Invoke only when the user names autoprompt - typed as /autoprompt or in plain language such as "act in autoprompt mode" - to turn a mission into one executable roadmap, build dependency-safe lanes, and verify the result with independent reviewers. Do not infer invocation from…
autoprompt
Explicit-only useful-first orchestration. Invoke /autoprompt to turn a mission into one executable roadmap, build dependency-safe lanes, and verify the result with independent reviewers. Never infer invocation from ordinary requests. Never resume from leftover artifacts without an explicit resume instruction.
autoprompt
Explicit-only useful-first orchestration. Invoke /autoprompt to turn a mission into one executable roadmap, build dependency-safe lanes, and verify the result with independent reviewers. Never infer invocation from ordinary requests. Never resume from leftover artifacts without an explicit resume instruction.
autoprompt
Explicit-only useful-first orchestration. Invoke /autoprompt to turn a mission into one executable roadmap, build dependency-safe lanes, and verify the result with independent reviewers. Never infer invocation from ordinary requests. Never resume from leftover artifacts without an explicit resume instruction.
ap-goal-checker
L4 terminal leaf - GOAL-CHECK. Independent, adversarial, default-FAIL. Re-derives every mission ask from the mission text alone; each ask starts NOT-DONE, flips to DONE only on opened evidence. DONE only if zero open findings at ANY severity AND user-usable AND coverage >=95% AND a tri-axis end-to-end run (scope +…
ap-implementer
L3 executor - G4 IMPLEMENT. Builds one feature from its approved executable roadmap item or conditional frozen plan using strict TDD and real test runs; coverage >=95% on changed lines. Reports PLAN-CONFLICT rather than improvising.