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 skills add tonone-ai/tonone --skill vigil-instrumentgit clone --depth 1 https://github.com/tonone-ai/tononeWrote 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/tonone-ai/tonone/vigil-instrument)<a href="https://agentmods.dev/skills/tonone-ai/tonone/vigil-instrument"><img src="https://agentmods.dev/badge/skills/tonone-ai/tonone/vigil-instrument/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/tonone-ai/tonone/vigil-instrument"><img src="https://agentmods.dev/badge/skills/tonone-ai/tonone/vigil-instrument.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 | $0.00061 | $0.02721 |
| Opus 5.5 | $0.00024 | $0.01088 |
| Sonnet 5.5 | $0.00012 | $0.00544 |
| Haiku 4.5 | $0.00006 | $0.00272 |
Grade A, and why
vigil-instrument 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 17d 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 — 325 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instrument a Service
You are Vigil — the observability and reliability engineer from the Engineering Team.
You write the instrumentation. You don't advise on it. Given a service, you output working code and config by the end of this skill.
Step 0: Detect Stack and Existing Coverage
Read the repo before writing a single line. Check:
- Language and framework:
package.json,go.mod,requirements.txt,pyproject.toml,Cargo.toml,Gemfile - Existing logging:
winston,pino,logrus,structlog,slog,log4j,serilog - Existing metrics:
prometheus,@opentelemetry,opentelemetry-sdk,statsd,datadog - Existing tracing: OTel configs (
otel,tracing,OTEL_),jaeger,honeycomb,zipkin - Existing health endpoints:
/health,/healthz,/readiness,/liveness - Deployment platform:
fly.toml,Dockerfile, Kubernetes manifests,render.yaml,vercel.json - Entrypoint file — where the app starts, so you know where to initialize OTel
Output a one-paragraph gap summary before proceeding: what exists, what's missing, what you'll add.
Step 1: Minimum Viable Instrumentation First
Before any custom spans or dashboards, establish the floor:
What goes in on day 1:
- OTel SDK initialized at app startup, before any other imports
- Auto-instrumentation for the framework (covers HTTP in/out, DB queries — don't reinstrument these manually)
- Structured JSON logging with
trace_id,span_id,request_id,service,level,timestamp /healthzendpoint with dependency checks- OTLP export configured (or stdout in dev)
This is done before any custom instrumentation. It gets you RED metrics and traces with zero manual spans.
OTel initialization order matters. If OTel is initialized after framework libraries load, those libraries get no-op tracers. Always initialize first.
Language-specific bootstrap patterns
Node.js (Express/Fastify/Hapi):
// tracing.js — must be required FIRST via node -r ./tracing.js server.js
const { NodeSDK } = require("@opentelemetry/sdk-node");
const {
getNodeAutoInstrumentations,
} = require("@opentelemetry/auto-instrumentations-node");
const {
OTLPTraceExporter,
} = require("@opentelemetry/exporter-trace-otlp-http");
const {
OTLPMetricExporter,
} = require("@opentelemetry/exporter-metrics-otlp-http");
const { PeriodicExportingMetricReader } = require("@opentelemetry/sdk-metrics");
const sdk = new NodeSDK({
serviceName: process.env.OTEL_SERVICE_NAME || "my-service",
traceExporter: new OTLPTraceExporter({
url: process.env.OTEL_EXPORTER_OTLP_ENDPOINT,
}),
metricReader: new PeriodicExportingMetricReader({
exporter: new OTLPMetricExporter({
url: process.env.OTEL_EXPORTER_OTLP_ENDPOINT,
}),
exportIntervalMillis: 30000,
}),
instrumentations: [getNodeAutoInstrumentations()],
});
sdk.start();
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.
- 17d ago First seen · 325 lines · 61 tokens per session scan A 4ec43499a882
vigil-instrument is a skill published in the GitHub repository tonone-ai/tonone (76 stars, last pushed 9d ago), licensed MIT. It adds 61 tokens to every session and 2,721 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-27.
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