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 getsentry/sentry-for-ai --skill sentry-instrument-logginggit clone --depth 1 https://github.com/getsentry/sentry-for-aiWrote 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-instrument-logging)<a href="https://agentmods.dev/skills/getsentry/sentry-for-ai/sentry-instrument-logging"><img src="https://agentmods.dev/badge/skills/getsentry/sentry-for-ai/sentry-instrument-logging.svg" alt="Measured on agentmods" 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 | $0.00020 | $0.02562 |
| Opus 5 | $0.00010 | $0.01281 |
| Sonnet 5 | $0.00004 | $0.00512 |
| Haiku 4.5 | $0.00002 | $0.00256 |
Grade A, and why
sentry-instrument-logging 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 7d 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 — 318 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instrument Sentry Logging
This skill adds structured Sentry logs to an application following the guidance in Instrumentation guidance.
The goal is to provide a small set of high-value log messages that make production behavior easier to understand and debug.
The log messages added by this skill should also serve as clear, repeatable, examples that users can follow when instrumenting the rest of their application.
Prerequisites
The repository should already have basic Sentry configuration.
If Sentry has not yet been configured, offer to set it up using the appropriate skills.
Steps
-
Inventory every application in the repository. Locate language/runtime manifests (
composer.json,package.json,go.mod,Gemfile,pyproject.toml,Cargo.toml, …). Each manifest typically marks a separately deployed application. Produce an explicit table and treat it as the work list for the rest of this skill:App Path Language Sentry SDK? Logging abstraction Status If the repo has more than ~2 apps, confirm scope with the user before starting: which apps to instrument now, and at what depth.
-
Establish shared conventions once, up front — before touching any app. Decide on consistent attribute namespacing (e.g.
myapp.<domain>.<field>), event-name phrasing, and log levels, so logs from every language can be searched and correlated together. Record these so each per-app pass follows them. Note service boundaries that propagate trace headers (baggage / sentry-trace) — logs on both sides of such a call should share attribute names so a single trace reads coherently across languages. -
For each application in the inventory, complete the full pass below before moving to the next, updating its Status as you go (
not started → configured → instrumented → verified):a. Read the corresponding language-specific skill in skills and confirm Sentry logging is configured. b. Determine the app's logging abstraction (Monolog/PHP, slog/Go, Rails logger/Ruby, Pino or console/JS). If Sentry supports it, configure that integration; otherwise use Sentry's logging SDK directly. c. Identify a small number of high-value log messages, prioritizing runtime decisions, important algorithms, audit events, and context around recoverable failures. Follow Valuable log entries to instrument. d. Add structured logs following the shared conventions from Step 2 and the Instrumentation guidance. e. Verify: run the app's lint/type/test tooling if available, and confirm logs are emitted. If the toolchain isn't available locally, say so explicitly rather than implying it passed.
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.
- 7d ago First seen · 318 lines · 20 tokens per session scan A f0e923bc4886
sentry-instrument-logging is a skill published in the GitHub repository getsentry/sentry-for-ai (258 stars, last pushed 2d ago), licensed MIT. It adds 20 tokens to every session and 2,562 once invoked, about $0.0001 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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