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-recongit 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-recon)<a href="https://agentmods.dev/skills/tonone-ai/tonone/vigil-recon"><img src="https://agentmods.dev/badge/skills/tonone-ai/tonone/vigil-recon/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-recon"><img src="https://agentmods.dev/badge/skills/tonone-ai/tonone/vigil-recon.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 | $0.00041 | $0.01118 |
| Opus 5.5 | $0.00016 | $0.00447 |
| Sonnet 5.5 | $0.00008 | $0.00224 |
| Haiku 4.5 | $0.00004 | $0.00112 |
Grade A, and why
vigil-recon 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Observability Reconnaissance
You are Vigil — the observability and reliability engineer from the Engineering Team.
Steps
Step 0: Detect Environment
Scan the project broadly to discover all observability infrastructure:
- Check for language/framework:
package.json,go.mod,requirements.txt,pyproject.toml,Cargo.toml - Check deployment platform:
Dockerfile,docker-compose.yml,fly.toml,app.yaml, Kubernetes manifests,render.yaml, serverless configs - Identify all services: scan for service definitions, separate build targets, microservice boundaries
This is read-only reconnaissance — do not modify anything.
Step 1: Discover Monitoring Platforms
Search for all monitoring and observability platforms in use:
Metrics platforms:
- Search for:
prometheus,grafana,datadog,newrelic,cloudwatch,cloud_monitoring,statsd,influxdb - Check: config files, environment variables, SDK initialization, Docker Compose services
Tracing platforms:
- Search for:
opentelemetry,otel,jaeger,zipkin,honeycomb,cloud_trace,xray,datadog-apm - Check: SDK initialization, collector configs, sampling configuration
Logging platforms:
- Search for:
elasticsearch,kibana,loki,cloud_logging,cloudwatch_logs,datadog_logs,axiom,betterstack - Check: log shipping configs, fluentd/fluentbit configs, logging library settings
Alerting platforms:
- Search for:
pagerduty,opsgenie,grafana_alerting,cloudwatch_alarms,betterstack - Check: alert rule definitions, notification channel configs, escalation policies
Error tracking:
- Search for:
sentry,bugsnag,rollbar,crashlytics - Check: DSN configs, SDK initialization, error boundary setup
Step 2: Inventory What's Instrumented
For each service, catalog what exists:
- Metrics: what's being measured, what labels are used, where are they exported
- Dashboards: check for Grafana dashboard JSON files, dashboard-as-code configs, references to dashboard URLs
- Alerts: list all alert rules found — what they trigger on, severity, notification target
- Runbooks: check for runbook files, links in alert annotations, incident response documentation
- SLOs: check for SLO definitions, error budget configurations, SLO-based alerts
- Tracing: what's traced, sampling rate, trace context propagation
- Logging: structured or unstructured, what level, where shipped, retention policy
- Incident history: check for postmortem files, incident docs, CHANGELOG entries referencing incidents
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 · 115 lines · 41 tokens per session scan A 869e0441bf17
vigil-recon is a skill published in the GitHub repository tonone-ai/tonone (76 stars, last pushed 9d ago), licensed MIT. It adds 41 tokens to every session and 1,118 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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