Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Bilal140202/the-lord-of-the-skillsnpx agentmods add skills/bilal140202/the-lord-of-the-skills/anthony-chaudhary__dos-kernelWrote 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/bilal140202/the-lord-of-the-skills/anthony-chaudhary__dos-kernel)<a href="https://agentmods.dev/skills/bilal140202/the-lord-of-the-skills/anthony-chaudhary__dos-kernel"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/anthony-chaudhary__dos-kernel/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/bilal140202/the-lord-of-the-skills/anthony-chaudhary__dos-kernel"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/anthony-chaudhary__dos-kernel.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 | $0.00117 | $0.03017 |
| Opus 5.5 | $0.00047 | $0.01207 |
| Sonnet 5.5 | $0.00023 | $0.00603 |
| Haiku 4.5 | $0.00012 | $0.00302 |
Grade A, and why
dos-enforce-tune 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 1mo 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.
This is a copy
94% identical to dos-enforce-tune — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dos-enforce-tune — the loop where DOS tunes its OWN enforcement, from outcomes
DOS is a sound PDP with no feedback from the PEP. The kernel decides an intervention verdict, a host acts on it, the act is journaled — but nothing fed whether the act was right back into the policy that drove it. This loop closes that. It learns the enforcement thresholds from the journal's own ground truth: a deny the operator later overrode is a false-DENY (too aggressive); a deny that stood is a held catch. The loop tunes the policy to drive false-DENIES down while holding the catches — and keeps an edit only if the kernel, not the agent, measures that it helped.
This is [[dos-self-improve]] pointed at the enforcement policy, with one twist: the
metric is not a generic count, it is the docs/143 net_task_delta of the policy over
labelled cases the loop did not author.
A self-tuner's fatal failure mode is grading its own homework — relabelling its outcomes so its policy edit looks good.
dos enforce-tunecloses that hole the same waydos improvedoes: the metric is computed BY THE KERNEL from cases the loop did not author (a frozen corpus ∪ the live enforcement journal). The loop cannot keep a policy edit by claiming it is better. The only path to KEEP is to actually movenet_task_delta.
What the kernel decides vs. what you do
| Step | Who | What |
|---|---|---|
| Read the outcomes | dos enforce-outcomes |
the live false-DENY / held-catch ledger — what to tune toward |
| Propose ONE policy-knob edit | YOU (a subagent) | the untrusted step — edit [intervention_policy] / [intervention] ranks / [improve] in a worktree |
| Measure | dos enforce-tune |
score the candidate policy's net_task_delta over the corpus, on the worktree |
| Keep / revert / escalate | dos enforce-tune (rides dos improve) |
the kernel's typed verdict over env-authored facts — NOT your opinion |
| Merge / discard / escalate | YOU (or the autonomous cadence) | carry out the kernel's verdict |
What ships with it
1 file 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.
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.
- 1mo ago First seen · 214 lines · 117 tokens per session scan A c7669e683306
dos-enforce-tune is a skill published in the GitHub repository Bilal140202/the-lord-of-the-skills (6 stars, last pushed 1mo ago), licensed MIT. It adds 117 tokens to every session and 3,017 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to dos-enforce-tune, differing in 2 lines, and is treated as a copy.
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