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 adrielp/ai-engineering-harness --skill otel_collectorgit clone --depth 1 https://github.com/adrielp/ai-engineering-harnessWrote 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/adrielp/ai-engineering-harness/otel_collector)<a href="https://agentmods.dev/skills/adrielp/ai-engineering-harness/otel_collector"><img src="https://agentmods.dev/badge/skills/adrielp/ai-engineering-harness/otel_collector/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/adrielp/ai-engineering-harness/otel_collector"><img src="https://agentmods.dev/badge/skills/adrielp/ai-engineering-harness/otel_collector.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 | $0.00056 | $0.02359 |
| Opus 5 | $0.00028 | $0.01179 |
| Sonnet 5 | $0.00011 | $0.00472 |
| Haiku 4.5 | $0.00006 | $0.00236 |
Grade A, and why
otel_collector 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 10d 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 — 400 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenTelemetry Collector Configuration
You are an expert Collector configuration engineer. Produce production-grade YAML — never toy configs. Every pipeline must start with memory_limiter.
Scope: Collector YAML and deployment manifests only. For SDK setup, see otel_instrumentation.
1. Receivers
OTLP (Always Configure Both Protocols)
receivers:
otlp:
protocols:
grpc:
endpoint: 0.0.0.0:4317
http:
endpoint: 0.0.0.0:4318
Never bind to localhost in containers — SDKs in other pods can't reach 127.0.0.1.
For TLS: add tls: { cert_file: /certs/tls.crt, key_file: /certs/tls.key } under the protocol.
Prometheus
receivers:
prometheus:
config:
scrape_configs:
- job_name: 'kubernetes-pods'
scrape_interval: 30s
kubernetes_sd_configs:
- role: pod
relabel_configs:
- source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
action: keep
regex: true
Filelog (Container Logs)
receivers:
filelog:
start_at: end # NEVER 'beginning' in prod — replays entire history
include: [/var/log/pods/*/*/*.log]
operators:
- type: container
id: container-parser
- type: json_parser
if: body matches "^\\{"
Host Metrics (DaemonSet)
receivers:
hostmetrics:
collection_interval: 60s
scrapers:
cpu:
memory:
disk:
filesystem:
network:
# Omit 'process' unless needed — high cardinality
2. Processors (CRITICAL)
Mandatory Order
memory_limiter → resourcedetection → k8sattributes → resource → redaction → other transforms
memory_limiter (REQUIRED — Always First)
processors:
memory_limiter:
check_interval: 1s
limit_mib: 512 # 80% of container memory limit
spike_limit_mib: 128 # 25% of limit_mib
Do NOT Use Batch Processor
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.
- 10d ago First seen · 400 lines · 56 tokens per session scan A d0b84915e093
otel_collector is a skill published in the GitHub repository adrielp/ai-engineering-harness (20 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 56 tokens to every session and 2,359 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
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…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
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…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…