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 jongpie/NebulaLogger --skill nebula-logger-instrumentationgit clone --depth 1 https://github.com/jongpie/NebulaLoggerWrote 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/jongpie/nebulalogger/nebula-logger-instrumentation)<a href="https://agentmods.dev/skills/jongpie/nebulalogger/nebula-logger-instrumentation"><img src="https://agentmods.dev/badge/skills/jongpie/nebulalogger/nebula-logger-instrumentation/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/jongpie/nebulalogger/nebula-logger-instrumentation"><img src="https://agentmods.dev/badge/skills/jongpie/nebulalogger/nebula-logger-instrumentation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, 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 Prompt Injection · line 189 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 202 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 194 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 205 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
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 | $0.00060 | $0.03489 |
| Opus 5 | $0.00030 | $0.01744 |
| Sonnet 5 | $0.00012 | $0.00698 |
| Haiku 4.5 | $0.00006 | $0.00349 |
Grade A, and why
nebula-logger-instrumentation 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 — 316 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instrumenting Code with Nebula Logger
Supported API Surface
Nebula Logger's supported API surface is everything marked global in Apex, and everything exported from the c/logger LWC module. The managed package (namespace Nebula) exposes only the global surface; the unlocked package technically exposes public classes and methods too, since there's no namespace boundary blocking access.
Do not rely on public Apex classes or methods from your own code. They are internal to Nebula Logger and can change, be renamed, or be removed in any release without a deprecation window. LoggerDataStore, LoggerConfigurationSelector, LogEntryHandler, LoggerPlugin (the class itself, not the LoggerPlugin__mdt records), and everything else without a global modifier is subject to change without notice.
If a capability you need isn't available through the global surface, file an issue at https://github.com/jongpie/NebulaLogger/issues rather than reaching into public methods. This skill and its companions only reference global APIs.
The Core Model
Every Nebula Logger runtime context follows the same pattern:
- Add one or more log entries at a level (
ERROR,WARN,INFO,DEBUG,FINE,FINER,FINEST). - Optionally enrich each entry with a record, exception details, or tags.
- Persist the buffered entries by calling
saveLog()once at the end of the transaction.
The rest of this skill shows what that looks like in each runtime context.
Cross-Cutting Concepts
Logging levels
Every context supports these seven levels: ERROR, WARN, INFO, DEBUG, FINE, FINER, FINEST. Which levels actually persist depends on the effective LoggerSettings__c.LoggingLevel__c for the user - see nebula-logger-install for the hierarchy setup and nebula-logger-best-practices for level selection guidance.
Scenarios and tags
Scenarios coarsely group a whole transaction under a business process; tags finely slice individual entries. Both are supported across every runtime.
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 · 316 lines · 60 tokens per session scan A c1472d6336e9
nebula-logger-instrumentation is a skill published in the GitHub repository jongpie/NebulaLogger (959 stars, last pushed yesterday), licensed MIT. It adds 60 tokens to every session and 3,489 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.
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