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 avizmarlon/agent-skills --skill observability-when-to-addgit clone --depth 1 https://github.com/avizmarlon/agent-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/avizmarlon/agent-skills/observability-when-to-add)<a href="https://agentmods.dev/skills/avizmarlon/agent-skills/observability-when-to-add"><img src="https://agentmods.dev/badge/skills/avizmarlon/agent-skills/observability-when-to-add/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/avizmarlon/agent-skills/observability-when-to-add"><img src="https://agentmods.dev/badge/skills/avizmarlon/agent-skills/observability-when-to-add.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 | $0.00053 | $0.00863 |
| Opus 5.5 | $0.00021 | $0.00345 |
| Sonnet 5.5 | $0.00011 | $0.00173 |
| Haiku 4.5 | $0.00005 | $0.00086 |
Grade A, and why
observability-when-to-add 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 2mo 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Observability & Instrumentation — Directed, Not Preventive
Industry principle (Google SRE Book, Honeycomb, Charity Majors): instrumentation carries maintenance cost proportional to its value. Every metric is code to maintain, schema that can break, storage cost, and signal to interpret. You instrument when you have confirmed pain, not "just in case."
When to add observability
- Performance bug you cannot locate (classic in multi-threaded, async, or distributed systems)
- External SLA or performance requirement demands metrics
- System is in production with real user traffic
- Flow analysis is part of the product itself (user journey tracking, etc.)
When NOT to add observability
- "Good practice" or preventive coverage before pain is identified
- Small side projects in active development
- Before you have identified a concrete bottleneck or failure mode
- To satisfy an abstract rule like "instrument everything"
What to use when you decide to instrument
- Production / real traffic → OpenTelemetry (CNCF graduated project) + collector + backend (Honeycomb, Tempo, Jaeger, or cloud equivalent)
- Local development / single-user → structured JSON logging +
jq/grep. Addcorrelation_idif the call crosses process boundaries. - Spot performance hunt → use language builtins (
console.time/console.timeEndin JavaScript,time.perf_counter()in Python, etc.). Discard after resolving the issue.
Universal principles when instrumenting
Instrument boundaries, not internals
- Entry points (API handlers, RPC endpoints)
- Network calls (HTTP, gRPC, database queries)
- External service boundaries
- NOT every function, NOT every variable assignment
Aggressive sampling in production
- Default: 1-10% of requests
- 100% only in development or for high-value (error) events
- Sampling reduces noise and cost without losing signal on aggregate behavior
Telemetry failure must not cascade
- All log writes go in try/catch blocks (silent failure okay)
- If the observability system is down, the application runs normally
- Observability is about understanding running systems, not blocking them
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.
- 2mo ago First seen · 77 lines · 53 tokens per session scan A 7877a7981729
observability-when-to-add is a skill published in the GitHub repository avizmarlon/agent-skills (2 stars, last pushed 4mo ago), licensed MIT. It adds 53 tokens to every session and 863 once invoked, about $0.0002 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 2026-08-31.
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