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 shennawardana23/skillme --skill layered-logging-and-alerting-patternsgit clone --depth 1 https://github.com/shennawardana23/skillmeWrote 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/shennawardana23/skillme/layered-logging-and-alerting-patterns)<a href="https://agentmods.dev/skills/shennawardana23/skillme/layered-logging-and-alerting-patterns"><img src="https://agentmods.dev/badge/skills/shennawardana23/skillme/layered-logging-and-alerting-patterns/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/shennawardana23/skillme/layered-logging-and-alerting-patterns"><img src="https://agentmods.dev/badge/skills/shennawardana23/skillme/layered-logging-and-alerting-patterns.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 | $0.00095 | $0.01240 |
| Opus 5.5 | $0.00038 | $0.00496 |
| Sonnet 5.5 | $0.00019 | $0.00248 |
| Haiku 4.5 | $0.00010 | $0.00124 |
Grade A, and why
layered-logging-and-alerting-patterns 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 1mo 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Layered Logging and Alerting
In some services, a single logger.Error(...) call is not "just a log
line" — it can simultaneously capture an event to an error tracker, ship
the log to a centralized collection endpoint, and (for certain severities
or subsystems) fire a chat/webhook alert. Treating a call site as if it
only writes local output is the source of most surprising regressions in
this shape of system — the fix here is understanding what a given log call
actually fans out to before changing or removing it.
A log call can be a multi-sink side effect
func Errorf(ctx context.Context, format string, args ...any) {
msg := fmt.Sprintf(format, args...)
logToLocalOutput(msg)
captureToErrorTracker(ctx, msg) // e.g. Sentry
go sendToCentralizedLogEndpoint(msg) // async, fire-and-forget by design
}
Before removing or "simplifying" a logging call in a codebase with this shape, check what it actually does — an apparently-redundant log line can be the only thing populating an external dashboard or triggering an on-call alert; deleting it silently removes that signal with no local indication anything changed.
Async side effects need a flush guarantee on exit paths
If a log call ships data asynchronously (a background goroutine posting to
an external endpoint), a process that exits immediately after logging a
fatal error can terminate before that goroutine's request completes,
silently losing the log. A deliberate short delay before actually
terminating (after a Fatal/Panic-style log call specifically) is a
real, intentional pattern to give an in-flight async log delivery time to
finish — not dead code or an accidental performance issue to "optimize
away."
Sampling and filtering are usually deliberate, not accidental
Error-tracking integrations commonly sample by environment (log everything
in development, sample a smaller percentage in production to control
volume/cost) and filter certain error classes before sending (a known-
noisy, low-value error message excluded via a beforeSend-style hook).
Both are typically deliberate operational decisions — verify the actual
current sampling rate and any filter rules before assuming an error "isn't
being tracked" is itself a bug, versus a documented filtering choice.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 111 lines · 95 tokens per session scan A e95e54e671cc
layered-logging-and-alerting-patterns is a skill published in the GitHub repository shennawardana23/skillme (3 stars, last pushed 12d ago), licensed Apache-2.0. It adds 95 tokens to every session and 1,240 once invoked, about $0.0004 per session on Opus 5.5. 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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