ops-monitor

ops-monitor is a skill for Claude Code from Lifecycle-Innovations-Limited/claude-ops. It costs 29 tokens per session (1,680 once invoked), scanned D, original, MIT.

A set of operating instructions for checking application monitoring systems. Monitoring systems collect signals about errors, performance, and service health.

In plain words
What is it for?
Running a health check, setting up monitoring backends, or watching application alerts and telemetry.
Why use it?
It gives the agent a defined way to configure or inspect Datadog, New Relic, and OpenTelemetry connections.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions subagents; names the AskUserQuestion tool.

Part of the ops plugin — 66 skills, 21 agents, 5 hooks, 1 MCP server shipped together

Good fit Running a health check, setting up monitoring backends, or watching application alerts and telemetry.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lifecycle-innovations-limited/claude-ops/ops-monitor
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.

Any agent
npx skills add Lifecycle-Innovations-Limited/claude-ops --skill ops-monitor
Clone the repo
git clone --depth 1 https://github.com/Lifecycle-Innovations-Limited/claude-ops

Made for: Claude Code.

Or install ops, the plugin that ships this one along with the rest of its 66 skills, 21 agents, 5 hooks, 1 MCP server.

Wrote 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.

agentmods badge for ops-monitor

README.md
[![agentmods](https://agentmods.dev/badge/skills/lifecycle-innovations-limited/claude-ops/ops-monitor/github.svg)](https://agentmods.dev/skills/lifecycle-innovations-limited/claude-ops/ops-monitor)
Your own site
<a href="https://agentmods.dev/skills/lifecycle-innovations-limited/claude-ops/ops-monitor"><img src="https://agentmods.dev/badge/skills/lifecycle-innovations-limited/claude-ops/ops-monitor/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.

agentmods 80×15 button for ops-monitor

Your own site · 80×15
<a href="https://agentmods.dev/skills/lifecycle-innovations-limited/claude-ops/ops-monitor"><img src="https://agentmods.dev/badge/skills/lifecycle-innovations-limited/claude-ops/ops-monitor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 29 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,680 The whole file, excluding the scripts and references it only reads on demand.
Security scan D 3 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00029 $0.01680
Opus 5 $0.00015 $0.00840
Sonnet 5 $0.00006 $0.00336
Haiku 4.5 $0.00003 $0.00168

Measured 12d ago against content hash 66d766b268a8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade D, and why

ops-monitor scanned grade D with 3 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 12d 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.

Sends data to an external URLmediumData exfiltration

A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.

- **New Relic**: `curl -sf -H "Api-Key: $NR_API_KEY" "https://api.newrelic.com/graphql" -d '{"query":"{ actor { user { name } } }"}'` → expect `data.actor.user`

Harvests environment variableshighData exfiltration

Enumerating or grepping the environment for keys collects credentials unrelated to what the mod says it does.

For each selected backend, collect credentials via `AskUserQuestion` free-text input (one at a time, ≤4 options per call):

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- **Datadog**: `curl -sf -H "DD-API-KEY: $DD_API_KEY" -H "DD-APPLICATION-KEY: $DD_APP_KEY" "https://api.datadoghq.com/api/v1/validate"` → expect `{"valid": true}`
claude-ops/skills/ops-monitor/SKILL.md · 171 lines

How it starts

The opening of the file, as written. The whole thing — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Runtime Context

PREFS="${CLAUDE_PLUGIN_DATA_DIR:-$HOME/.claude/plugins/data/ops-ops-marketplace}/preferences.json"
DD_API_KEY=$(jq -r '.datadog_api_key // empty' "$PREFS" 2>/dev/null)
NR_API_KEY=$(jq -r '.newrelic_api_key // empty' "$PREFS" 2>/dev/null)
OTEL_ENDPOINT=$(jq -r '.otel_endpoint // empty' "$PREFS" 2>/dev/null)

Determine $ARGUMENTS mode:

  • Contains --setup → run Setup flow
  • Contains --watch → run Watch mode
  • Otherwise → run Default health check

OPS ► MONITOR

Load ops-rules before acting. Public repo (no personal data). Outbound: one draft → one approval → one send. If AskUserQuestion / Workflow are missing, follow Rule 10 in ops-rules (Hermes: numbered options / two-turn Telegram card; delegate_task).

Setup flow (--setup)

Ask which backends to configure:

Which monitoring backends would you like to configure?
[Datadog]  [New Relic]  [OpenTelemetry]  [All three]

For each selected backend, collect credentials via AskUserQuestion free-text input (one at a time, ≤4 options per call):

Datadog:

  1. datadog_api_key — API Key from app.datadoghq.com/organization-settings/api-keys
  2. datadog_app_key — Application Key from app.datadoghq.com/organization-settings/application-keys

New Relic:

  1. newrelic_api_key — User API Key from one.newrelic.com/api-keys
  2. newrelic_account_id — Numeric Account ID from New Relic admin portal

OpenTelemetry:

  1. otel_endpoint — Base URL of your OTEL-compatible backend (e.g., https://otlp.grafana.net)

Write each credential to preferences.json using atomic tmpfile swap:

tmp=$(mktemp)
jq --arg k "$KEY" --arg v "$VALUE" '.[$k] = $v' "$PREFS" > "$tmp" && mv "$tmp" "$PREFS"

Run smoke test after saving:

  • Datadog: curl -sf -H "DD-API-KEY: $DD_API_KEY" -H "DD-APPLICATION-KEY: $DD_APP_KEY" "https://api.datadoghq.com/api/v1/validate" → expect {"valid": true}
  • New Relic: curl -sf -H "Api-Key: $NR_API_KEY" "https://api.newrelic.com/graphql" -d '{"query":"{ actor { user { name } } }"}' → expect data.actor.user
  • OTEL: curl -sf "$OTEL_ENDPOINT/healthz" → expect HTTP 200

Read the full file on GitHub · 171 lines

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. 12d ago First seen · 171 lines · 29 tokens per session scan D 66d766b268a8

Subscribe to this mod's changes

ops-monitor is a skill published in the GitHub repository Lifecycle-Innovations-Limited/claude-ops (189 stars, last pushed today), licensed MIT. It adds 29 tokens to every session and 1,680 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it D with 3 findings (sends data to an external url, harvests environment variables, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

abm-campaign-builder

Builds targeted Account-Based Marketing campaigns by identifying ideal customer profiles, mapping buying committees, creating personalized outreach sequences, and designing multi-channel engagement strategies. Use when targeting enterprise accounts, building sales playbooks, or designing vertical market penetration…

Adri3l-R3nan/cognify-skills · 53 tokens

business-roi-analyzer

Calculates ROI, payback period, and financial projections for business investments including technology purchases, automation projects, hiring decisions, and equipment acquisitions. Use when evaluating whether a business investment is worth making, comparing multiple investment options, or building a business case for…

Adri3l-R3nan/cognify-skills · 58 tokens

client-discovery-interview

Conducts structured discovery interviews for consultants, agencies, and service providers. Guides conversation through problem identification, stakeholder mapping, success criteria definition, budget/timeline scoping, and produces a formatted discovery brief with next steps.

Adri3l-R3nan/cognify-skills · 49 tokens

cognify-workflow-analysis

Analyzes business workflows to identify automation opportunities, calculate ROI, and generate structured redesign recommendations. Use when a user describes operational pain points, wants to reduce manual work, improve team communication, automate repetitive tasks, or evaluate where AI can save time and money.

Adri3l-R3nan/cognify-skills · 58 tokens

competitive-intelligence

Conducts structured competitive analysis including market positioning, feature comparison, pricing intelligence, SWOT analysis, and strategic recommendations. Use when evaluating competitors, preparing for a sales battle card, planning market entry, differentiating a product, or building a competitive strategy.

Adri3l-R3nan/cognify-skills · 53 tokens

customer-feedback-analyzer

Analyzes customer feedback from surveys, reviews, support tickets, and interviews to identify themes, prioritize improvements, and quantify sentiment. Use when processing NPS results, analyzing churn reasons, reviewing product feedback, understanding support ticket patterns, or building a product or service…

Adri3l-R3nan/cognify-skills · 59 tokens