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/anomalyarmor/agents/coveragenpx skills add anomalyarmor/agents --skill coveragegit clone --depth 1 https://github.com/anomalyarmor/agentsWhat 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 | $0.00042 | $0.00441 |
| Opus 5 | $0.00021 | $0.00220 |
| Sonnet 5 | $0.00008 | $0.00088 |
| Haiku 4.5 | $0.00004 | $0.00044 |
Grade A, and why
armor-coverage 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.
What it actually says
Monitoring Coverage and Tiers
Analyze what is being monitored, view your coverage tier, and identify gaps in your data observability.
Prerequisites
- AnomalyArmor API key configured
- Python SDK installed (pip install anomalyarmor)
When to Use
- What am I monitoring?
- What tier is my database at?
- Show monitoring gaps
- How do I improve my coverage score?
- What tables have no alerts?
Coverage Tiers
Every asset earns a coverage score (0-100) based on 6 monitoring features:
| Tier | Score | What You Catch |
|---|---|---|
| Monitored | 10-29 | Schema changes that break pipelines |
| Protected | 30-49 | Pipeline failures, data disappearing |
| Verified | 50-69 | Stale data, value corruption |
| Intelligent | 70+ | AI-powered anomaly detection |
Score weights: Schema Drift (25%), Freshness (25%), Metrics (20%), Alert Routing (15%), Validity (10%), Intelligence (5%).
Steps
Get Coverage Score and Tier
Use client.coverage.get(asset_id) to get score, tier, and breakdown.
Get Company-Wide Coverage
Use client.coverage.company() for company rollup with per-asset scores.
Find Coverage Gaps
Use client.coverage.gaps(asset_id) for prioritized recommendations.
Apply Recommendations
Use client.coverage.apply(asset_id) to batch-apply all recommendations.
Related Skills
- /armor:recommend - Get AI-driven recommendations for what to monitor
- /armor:monitor - Set up freshness and schema monitoring
- /armor:quality - Add metrics and validity rules
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.
- yesterday First seen · 66 lines · 42 tokens per session scan A 0e4a19554841
armor-coverage is a skill published in the GitHub repository anomalyarmor/agents (1 stars, last pushed 3mo ago), licensed MIT. It adds 42 tokens to every session and 441 once invoked, about $0.0002 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.
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