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 GoldenWing-360/claude-security-skills --skill log-strategygit clone --depth 1 https://github.com/GoldenWing-360/claude-security-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/goldenwing-360/claude-security-skills/log-strategy)<a href="https://agentmods.dev/skills/goldenwing-360/claude-security-skills/log-strategy"><img src="https://agentmods.dev/badge/skills/goldenwing-360/claude-security-skills/log-strategy/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/goldenwing-360/claude-security-skills/log-strategy"><img src="https://agentmods.dev/badge/skills/goldenwing-360/claude-security-skills/log-strategy.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 | $0.00078 | $0.02457 |
| Opus 5 | $0.00039 | $0.01229 |
| Sonnet 5 | $0.00016 | $0.00491 |
| Haiku 4.5 | $0.00008 | $0.00246 |
Grade A, and why
log-strategy 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 11d 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 — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Log Strategy
Most teams either log too little to investigate anything or too much to find anything (and end up storing PII they didn't mean to). This skill is the middle path: enough to support incident response, not so much that the log becomes a liability of its own.
Pairs with incident-response (where logs get used) and gdpr-technical-controls (where log privacy lives).
When to invoke
- Starting a new service or workflow
- Investigation revealed missing fields ("we don't know what request triggered this")
- Logs are leaking PII or secrets
- Log volume is becoming expensive / unwieldy
- Consolidating to a central logging stack (Loki, ELK, OpenObserve, hosted)
- After an incident where the log was insufficient
Three classes of log, three retention tiers
Treat your logs as three distinct streams. Conflating them is where the trouble starts.
| Class | Purpose | Typical retention | Storage tier |
|---|---|---|---|
| Operational | Debugging, performance, errors | 7–30 days | Hot index |
| Access | Who hit what, when (webserver + app request log) | 30–90 days | Hot + warm |
| Audit | Security-relevant events (auth, permission changes, sensitive actions) | 12 months+ | Append-only, immutable where possible |
Costs and tools differ per class. Mixing them gives the audit log's slow-and-expensive retention to the operational stream and is the most common reason logging gets killed by finance.
Operational logs — what to capture
Structured logging beats freeform every time. Choose JSON (or logfmt) and a single library for the whole app.
// pino example — Node
import pino from 'pino';
const log = pino({
level: process.env.LOG_LEVEL ?? 'info',
redact: {
paths: ['password', 'token', 'authorization', '*.password', '*.token', 'req.headers.authorization', 'req.headers.cookie'],
censor: '[REDACTED]',
},
serializers: {
req: (req) => ({
method: req.method,
url: req.url,
requestId: req.id,
// explicitly NOT: headers (except a few safe ones), body
}),
err: pino.stdSerializers.err,
},
});
log.info({ orderId, userId: anonymize(userId) }, 'order created');
log.warn({ requestId, latencyMs }, 'slow query');
log.error({ requestId, err }, 'unhandled error in handler');
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.
- 11d ago First seen · 207 lines · 78 tokens per session scan A 8ce8da7f6ece
log-strategy is a skill published in the GitHub repository GoldenWing-360/claude-security-skills (17 stars, last pushed 1mo ago), licensed MIT. It adds 78 tokens to every session and 2,457 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 2026-08-30.
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