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/rlaope/nen/vownpx skills add rlaope/nen --skill vowgit clone --depth 1 https://github.com/rlaope/nenWrote 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/rlaope/nen/vow)<a href="https://agentmods.dev/skills/rlaope/nen/vow"><img src="https://agentmods.dev/badge/skills/rlaope/nen/vow.svg" alt="Measured on agentmods" 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 | $0.00142 | $0.02195 |
| Opus 5 | $0.00071 | $0.01097 |
| Sonnet 5 | $0.00028 | $0.00439 |
| Haiku 4.5 | $0.00014 | $0.00219 |
Grade A, and why
vow 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 6d 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Stance
制約と誓約 — Restriction and Pledge: an ability grows stronger through what its user swears not to do, and a broken oath forfeits the power itself. For an agent this law is not thematic, it is generation mechanics. An agent writes toward what already sits in its context: a constraint declared before the first action conditions every action after it, while the same constraint recalled at review time merely grades the damage. Stated up front, "no new dependencies" steers the fix away from the tempting library; remembered afterward, it is a rejection comment on a finished diff.
The stakes are the two chronic failures of agent work, visible in any week of transcripts. The wandering diff: asked for one fix, the agent "also cleaned up" four files nobody mentioned, and the review burden lands on the person who wanted one line changed. And the hollow done: "fixed" claimed with no run evidence, discovered unfixed by the next person to pull. The failures share a root — the constraints existed, in the request or in the engaged skill's own Done means, but nothing forced them into the transcript before the work began. A vow is that forcing, and its law is strict: falsifiable and visible, or it is not a vow. "I'll be careful" binds nothing; "the diff touches src/billing/ only" can be checked by anyone holding the diff.
Boundaries
Vow binds work; it never selects it. Reading a request's problem shape and choosing which abilities engage is en's field — vow begins the moment en's engagement line is posted, turning that routing decision into pledges the work can be audited against. En announces which disciplines act; vow declares what the acting work swears not to do. Neither does the other's job.
When work is dispatched across agents, the acceptance criteria attached to each unit are that delegate's vows, and their form is this discipline: falsifiable, declared before the unit starts, audited on return. Manipulator owns the decomposition, the dispatch, and the verification — vow only defines what a criterion must look like for that verification to be possible. A delegate's "done" arriving without its audit is manipulator's to reject, in vow's format.
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.
- 6d ago First seen · 99 lines · 142 tokens per session scan A 070c9d972fa8
vow is a skill published in the GitHub repository rlaope/nen (3 stars, last pushed 1mo ago), licensed MIT. It adds 142 tokens to every session and 2,195 once invoked, about $0.0007 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.
Other skills, from other repositories
claude-md-improver
Audit and improve CLAUDE.md files in repositories. Use when user asks to check, audit, update, improve, or fix CLAUDE.md files. Scans for all CLAUDE.md files, evaluates quality against templates, outputs quality report, then makes targeted updates. Also use when the user mentions "CLAUDE.md maintenance" or "project…
agent-platform-rag-engine-management
Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google…
gke-reliability
Improves GKE workload reliability, using PDBs, health probes, and topology spread constraints. Use when configuring GKE workload reliability, setting up PDBs, or configuring GKE health probes (liveness, readiness, startup). Don't use for disaster recovery setup or full cluster backups (use gke-backup-dr instead).
gke-workload-security
Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running cluster security audits (auditcluster.sh), configuring Workload Identity Federation (impersonation, KSA/GSA binding, and pod setup), enforcing Network Policies (default-deny…
agent-platform-model-registry
Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.
google-cloud-solution-agentic-analytics-spark-knowledge-catalog
Discovers requirements and generates guidance to design and deploy a governed, secure agentic-analytics solution for data that's distributed across Google Cloud, other cloud providers, or on-premises. Data that's outside Google Cloud (such as data from Databricks, Snowflake, Salesforce, SAP, or Oracle systems) is…