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 pjt222/agent-almanac --skill configure-log-aggregationgit clone --depth 1 https://github.com/pjt222/agent-almanacWrote 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/pjt222/agent-almanac/configure-log-aggregation)<a href="https://agentmods.dev/skills/pjt222/agent-almanac/configure-log-aggregation"><img src="https://agentmods.dev/badge/skills/pjt222/agent-almanac/configure-log-aggregation/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/pjt222/agent-almanac/configure-log-aggregation"><img src="https://agentmods.dev/badge/skills/pjt222/agent-almanac/configure-log-aggregation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 433 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00086 | $0.03661 |
| Opus 5 | $0.00043 | $0.01831 |
| Sonnet 5 | $0.00017 | $0.00732 |
| Haiku 4.5 | $0.00009 | $0.00366 |
Grade A, and why
configure-log-aggregation scanned grade A with 1 finding 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 6d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Monitor Promtail metrics: `curl http://localhost:9080/metrics | grep promtail` How it starts
The opening of the file, as written. The whole thing — 471 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Configure Log Aggregation
Implement centralized log collection, parsing, and querying with Loki/Promtail or ELK stack for operational visibility.
When to Use
- Consolidating logs from multiple services or hosts into a searchable system
- Replacing local log files with centralized, queryable log storage
- Correlating logs with metrics and traces for full observability
- Implementing structured logging with label extraction from unstructured logs
- Setting retention policies for log data based on storage and compliance needs
- Troubleshooting production incidents requiring log analysis across services
Inputs
- Required: Log sources (application logs, system logs, container logs)
- Required: Log format patterns (JSON, plaintext, syslog, etc.)
- Optional: Label extraction rules for structured querying
- Optional: Retention and compression policies
- Optional: Existing log shipper configuration (Fluentd, Filebeat, Promtail)
Procedure
See Extended Examples for complete configuration files and templates.
Step 1: Choose Log Aggregation Stack
Select between Loki (Prometheus-style) or ELK (Elasticsearch-based) based on requirements.
Loki advantages:
- Lightweight, designed for Kubernetes and cloud-native environments
- Label-based indexing (like Prometheus) for low storage overhead
- Native integration with Grafana for unified dashboards
- Horizontal scalability with object storage (S3, GCS)
- Lower resource consumption compared to Elasticsearch
ELK advantages:
- Full-text search across all log content (not only labels)
- Rich query DSL and aggregations
- Mature ecosystem with beats, logstash plugins
- Better for compliance/audit logs requiring deep historical search
For this guide, we'll focus on Loki + Promtail (recommended for most modern setups).
Decision criteria:
Use Loki if:
- You want label-based queries similar to Prometheus
- Storage costs are a concern (Loki indexes only labels)
- You already use Grafana for metrics
- Kubernetes/container-native deployment
Use ELK if:
- You need full-text search across all log content
- You have complex log parsing and enrichment requirements
- You require advanced analytics and aggregations
- Legacy systems with existing Logstash pipelines
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.
- 6d ago First seen · 471 lines · 86 tokens per session scan A 203271cfd37b
configure-log-aggregation is a skill published in the GitHub repository pjt222/agent-almanac (32 stars, last pushed yesterday), licensed MIT. It adds 86 tokens to every session and 3,661 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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