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 latestaiagents/agent-skills --skill metrics-logs-tracesgit clone --depth 1 https://github.com/latestaiagents/agent-skillsWrote 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/latestaiagents/agent-skills/metrics-logs-traces)<a href="https://agentmods.dev/skills/latestaiagents/agent-skills/metrics-logs-traces"><img src="https://agentmods.dev/badge/skills/latestaiagents/agent-skills/metrics-logs-traces/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/latestaiagents/agent-skills/metrics-logs-traces"><img src="https://agentmods.dev/badge/skills/latestaiagents/agent-skills/metrics-logs-traces.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 | $0.00076 | $0.01976 |
| Opus 5 | $0.00038 | $0.00988 |
| Sonnet 5 | $0.00015 | $0.00395 |
| Haiku 4.5 | $0.00008 | $0.00198 |
Grade A, and why
metrics-logs-traces 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 8d 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 — 266 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Observability: Metrics, Logs, and Traces
The three pillars of observability for understanding system behavior.
The Three Pillars
┌─────────────────────────────────────────────────────────────┐
│ OBSERVABILITY PILLARS │
├─────────────────────────────────────────────────────────────┤
│ │
│ METRICS LOGS TRACES │
│ ──────── ───── ─────── │
│ What's happening Why it's happening How requests flow │
│ │
│ • Request rate • Error messages • Request path │
│ • Error rate • Stack traces • Service deps │
│ • Latency • Debug info • Timing breakdown │
│ • Saturation • Audit events • Correlation │
│ │
│ Aggregated Individual Request-scoped │
│ Time-series Events Distributed │
│ │
└─────────────────────────────────────────────────────────────┘
Metrics: The RED Method
For services, track Rate, Errors, and Duration:
# Example: Prometheus metrics in Python
from prometheus_client import Counter, Histogram, Gauge
# Rate: Request throughput
request_total = Counter(
'http_requests_total',
'Total HTTP requests',
['method', 'endpoint', 'status']
)
# Errors: Error rate
error_total = Counter(
'http_errors_total',
'Total HTTP errors',
['method', 'endpoint', 'error_type']
)
# Duration: Latency distribution
request_duration = Histogram(
'http_request_duration_seconds',
'HTTP request duration',
['method', 'endpoint'],
buckets=[.005, .01, .025, .05, .1, .25, .5, 1, 2.5, 5, 10]
)
# Usage in handler
@request_duration.labels(method='GET', endpoint='/api/users').time()
def get_users():
request_total.labels(method='GET', endpoint='/api/users', status='200').inc()
# ... handler logic
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.
- 8d ago First seen · 266 lines · 76 tokens per session scan A c5df1596be1c
metrics-logs-traces is a skill published in the GitHub repository latestaiagents/agent-skills (5 stars, last pushed 4mo ago), licensed MIT. It adds 76 tokens to every session and 1,976 once invoked, about $0.0004 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 2026-09-03.
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