armor-coverage

A monitoring-coverage tool that reports which data assets are monitored, assigns a score and tier, and identifies gaps. Coverage means how much of an asset's important behavior is being checked.

In plain words
What is it for?
Use it to view an asset's coverage score, review company-wide coverage, find unmonitored tables, identify missing alerts, and prioritize improvements.
Why use it?
It shows where monitoring is missing instead of making you inspect each table separately. The score breakdown helps explain whether gaps involve schema changes, freshness, metrics, alerts, validity, or anomaly detection.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/anomalyarmor/agents/coverage
Any agent
npx skills add anomalyarmor/agents --skill coverage
Clone the repo
git clone --depth 1 https://github.com/anomalyarmor/agents

Made for: Claude Code, Codex.

Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 441 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured yesterday against content hash 0e4a19554841, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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.

skills/coverage/SKILL.md · 66 lines

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.

  • /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
Changes

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.

  1. yesterday First seen · 66 lines · 42 tokens per session scan A 0e4a19554841

Subscribe to this mod's changes

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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

babysit-pr

Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…

openai/codex · 114 tokens

imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…

openai/codex · 113 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens