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 New1Direction/korgex --skill observability-and-logginggit clone --depth 1 https://github.com/New1Direction/korgexWrote 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/new1direction/korgex/observability-and-logging)<a href="https://agentmods.dev/skills/new1direction/korgex/observability-and-logging"><img src="https://agentmods.dev/badge/skills/new1direction/korgex/observability-and-logging.svg" alt="Measured on agentmods" 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 | $0.00019 | $0.00340 |
| Opus 5 | $0.00010 | $0.00170 |
| Sonnet 5 | $0.00004 | $0.00068 |
| Haiku 4.5 | $0.00002 | $0.00034 |
Grade A, and why
observability-and-logging 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 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.
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.
What it actually says
You can't fix what you can't see. Good observability is the difference between a five-minute diagnosis and an all-night guess — but noisy logging is its own problem.
- Log events, not narration. Record meaningful state transitions, decisions, and errors — not "entering function". Each log line should help answer "what happened and why" later.
- Use levels deliberately. ERROR = needs attention; WARN = recoverable oddity; INFO = significant lifecycle events; DEBUG = detail for diagnosis. Don't log everything at INFO.
- Make logs structured + correlatable. Prefer key/value (or JSON) over prose so they're searchable; carry an id (request/trace/session) through related lines so one flow can be reconstructed.
- Include the context to act. On an error, log what was being attempted, the key inputs, and the cause — enough to reproduce. A bare "failed" is useless.
- NEVER log secrets or PII. Tokens, passwords, keys, personal data must not hit logs. Redact at the boundary.
- Metrics for the steady state, logs for the incident. Count/timing for rates and latency (the "is it healthy?"); detailed logs for the "why did THIS fail?".
- Fail-safe: instrumentation must never crash or materially slow the path it measures.
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 · 28 lines · 19 tokens per session scan A 0d6dffd8b452
observability-and-logging is a skill published in the GitHub repository New1Direction/korgex (5 stars, last pushed 2mo ago), licensed MIT. It adds 19 tokens to every session and 340 once invoked, about $0.0001 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.
Other skills, from other repositories
cce-routing
Use Cursor Bridge's read-only cursorcontextengine for unfamiliar project understanding when the exact code location is unknown or the task requires tracing behavior, symbols, callers and callees, data flow, registrations, interface implementations, ownership boundaries, or cross-module relationships. Trigger for…
gh-fix-ci
Use when a user asks to debug or fix failing GitHub PR checks that run in GitHub Actions. Use the GitHub app from this plugin for PR metadata and patch context, and use gh for Actions check and log inspection before implementing any approved fix.
rel-ai-debugging
Use when repository behavior is reproducibly wrong and needs causal diagnosis or repair, including errors, broken tests, crashes, regressions, failed contracts, or incorrect runtime behavior. Do not use for general audits or final verification when no active defect is being diagnosed.
rel-ai-investigation
Use for read-only repository questions that need evidence, including architecture audits, feasibility studies, dependency or caller tracing, impact analysis, implementation-status checks, and proof of how something works. Do not use to implement fixes or for final completion or release verification of changes already…
fix-default
A default procedure for handling bug fixes, organised as a three-step scan and a CP process. The input does not explain what the three steps or CP process contain.
repair-prevention-assessment
A completion gate for fixes and self-repair work. It creates a machine-checkable assessment that separates evidence a current issue is closed from evidence that the fix will remain effective.