kernel-ops

Natural-language operations for context-kernel, a system that selects and compresses conversation context for an agent.

In plain words
What is it for?
Checking saved tokens and system health, viewing pending comparisons, reviewing configuration, and retrieving context-kernel reports.
Why use it?
It lets you inspect the system and run checks without remembering special command syntax, while keeping changes explicit instead of automatic.

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/pinperepette/context-kernel/kernel-ops
Any agent
npx skills add Pinperepette/context-kernel --skill kernel-ops
Clone the repo
git clone --depth 1 https://github.com/Pinperepette/context-kernel

Made for: Claude Code, Codex.

Per session 207 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 862 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 $0.00207 $0.00862
Opus 5 $0.00103 $0.00431
Sonnet 5 $0.00041 $0.00172
Haiku 4.5 $0.00021 $0.00086

Measured yesterday against content hash 9224db6d8870, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

kernel-ops 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 yesterday.

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.

claude-context-kernel/skills/kernel-ops/SKILL.md · 45 lines

How it starts

The opening of the file, as written. The whole thing — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.

kernel-ops — la superficie operativa del context-kernel a parole

Questa skill è il gemello a linguaggio naturale dei comandi /ck-*: stessa funzione, stessi script, ma raggiungibile dicendo cosa vuoi invece di ricordare la sintassi. Gli script vivono sotto ${CLAUDE_PLUGIN_ROOT}/hooks/ (con la via plugin) oppure, per l'install manuale, nella cartella hooks/ del plugin — risolvi il path una volta e riusalo.

Principio (non tradire la filosofia)

Il plugin non fa mai tuning silenzioso. Questa skill può leggere e diagnosticare liberamente, ma tutto ciò che scrive stato va fatto solo su richiesta esplicita dell'utente, annunciando cosa sta per cambiare: apply-rates (relax-only), write-priors (add-only), charter clear, savings reset-canary. Nel dubbio: mostra, non attuare.

Instradamento dell'intento

Capisci cosa chiede l'utente e lancia il comando corrispondente (poi sintetizza l'output, non incollare referti lunghi):

L'utente vuole… Comando
stato/colpo d'occhio (risparmio, canary, coda A/B, carta) savings.py + ab_verify.py --status + charter.py get
salute dell'installazione (health-check) doctor.py
report risparmio token savings.py (--html [path] per la pagina)
acquietare il canary dopo indagine (esplicito) savings.py --reset-canary
giudicare i campioni A/B ab_verify.py (--status, --dry-run, --limit N)
recuperare un output parcheggiato recall.py --search REGEX | recall.py <chiave> --grep/--lines
vedere/rinfrescare/azzerare la carta del task charter.py get | refresh | clear
smoke test della compressione smoke.py generate poi smoke.py check
rilevanza rivelata (T5), solo report revealed.py --aggregate
attuare tassi/prior appresi (esplicito) revealed.py --aggregate --apply-rates | --write-priors

Tutti eseguibili con python3 <hooks>/<script>. Se l'utente preferisce la forma digitata, gli stessi passi sono i comandi /ck-status, /ck-doctor, /ck-savings, /ck-verify, /ck-recall, /ck-charter, /ck-smoke, /ck-tune.

Read the full file on GitHub · 45 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. yesterday First seen · 45 lines · 0 tokens per session scan A 9224db6d8870

Subscribe to this mod's changes

kernel-ops is a skill published in the GitHub repository Pinperepette/context-kernel (24 stars, last pushed 1mo ago), licensed MIT. It adds 207 tokens to every session and 862 once invoked, about $0.0010 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

babysit-pr

Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…

openai/codex · 114 tokens

imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…

openai/codex · 113 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens