Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/getsentry/sentry-for-ainpx agentmods add skills/getsentry/sentry-for-ai/sentry-instrumentation-guideWrote 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/getsentry/sentry-for-ai/sentry-instrumentation-guide)<a href="https://agentmods.dev/skills/getsentry/sentry-for-ai/sentry-instrumentation-guide"><img src="https://agentmods.dev/badge/skills/getsentry/sentry-for-ai/sentry-instrumentation-guide.svg" alt="Measured on agentmods" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Memory Poisoning · line 16 Skill attempts to fill the context window with filler content, displacing legitimate instructions and safety constraints. This can degrade agent performance or bypass safety boundaries.Fix: Implement context-window management that detects and rejects padding or stuffing attempts. Prioritize system instructions over user-injected content.
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 | $0.00108 | $0.01896 |
| Opus 5 | $0.00054 | $0.00948 |
| Sonnet 5 | $0.00022 | $0.00379 |
| Haiku 4.5 | $0.00011 | $0.00190 |
Grade A, and why
sentry-instrumentation-guide 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 8d 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
All Skills > Feature Setup > Instrumentation Guide
Sentry Instrumentation Guide: When to Reach for What
Errors, traces, logs, and metrics are the four kinds of telemetry most apps run on, and they overlap enough that the choice is rarely obvious. You can stuff context into a span attribute instead of logging it. You can count log lines instead of emitting a metric. You can add a duration to a log and call it a span.
But each signal exists because it answers a different question and feeds a different workflow once it lands. Reaching for the wrong one means the data is technically there but useless for the job you actually have later. This skill is the decision framework: given a value or an event in front of you, which signal should carry it, and why.
It decides what to emit. For how to turn each pillar on for a given stack, hand off to the
sentry-*-sdk skills and sentry-setup-ai-monitoring.
Invoke This Skill When
- You're instrumenting a piece of code and unsure whether something should be a log, a span, a span attribute, or a metric
- You're deciding "what to instrument where" across a service or request handler
- You're reviewing existing instrumentation for gaps (e.g. an error feed that's empty while users report problems)
- A coding agent needs a consistent rule for choosing between errors, traces, logs, and metrics
Important: The SDK APIs and code samples here are illustrative. Verify exact signatures and
minimum versions against docs.sentry.io and the relevant sentry-*-sdk
skill before implementing.
The Four Signals, One Question Each
| Signal | The question it answers | Docs |
|---|---|---|
| Errors | "What just broke?" — a stack trace and exception type, grouped into a deduplicated Issue that gets assigned and tracked to resolution. If your code threw, it's an error. | Issues |
| Traces | "Did the request flow the way it was supposed to?" — a waterfall of timed spans. Mostly auto-instrumented. | Trace Explorer |
| Logs | "What was true at this point in the code, and why?" — the system's state at one moment as a structured event: config, flags, inputs/outputs, the decision that was made. | Logs |
| Metrics | "How's this trending over time?" — counters, gauges, distributions you can slice by attribute and chart, alert on, or compare across a deploy. | Metrics |
What ships with it
2 files 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.
- 8d ago First seen · 130 lines · 108 tokens per session scan A 0f0da7372004
sentry-instrumentation-guide is a skill published in the GitHub repository getsentry/sentry-for-ai (260 stars, last pushed 3d ago), licensed MIT. It adds 108 tokens to every session and 1,896 once invoked, about $0.0005 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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