sentry-instrumentation: Instructions file for Codex

AGENTS.md

sentry-instrumentation AGENTS.md is an instructions file for Codex, OpenCode from tortastudios/sentry-instrumentation. It costs 1,038 tokens per session, scanned A, original, MIT.

Instructions for teaching coding agents to add Sentry monitoring to applications. Sentry is a service for collecting errors, measurements, and traces that show how software runs; the guidance includes metrics and AI-agent tracing patterns.

In plain words
What is it for?
Adding counters, gauges, distributions, timing and failure measurements, plus tracing for AI-agent conversations in Python and other languages.
Why use it?
It gives agents tested implementation patterns and explains where the instructions belong for different coding-agent tools.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: reads .claude/ paths; mentions Claude Code; mentions AGENTS.md.

This is tortastudios/sentry-instrumentation's own configuration. It tells Codex and OpenCode how to work on sentry-instrumentation itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything sentry-instrumentation configures →

Reuse

Borrowing it

Nothing to install: this file belongs to tortastudios/sentry-instrumentation. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/tortastudios/sentry-instrumentation/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/tortastudios/sentry-instrumentation

Made for: Codex, OpenCode.

Wrote 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.

agentmods badge for sentry-instrumentation AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/tortastudios/sentry-instrumentation/agents-md.svg)](https://agentmods.dev/instructions/tortastudios/sentry-instrumentation/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/tortastudios/sentry-instrumentation/agents-md"><img src="https://agentmods.dev/badge/instructions/tortastudios/sentry-instrumentation/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 1,038 This file is loaded in full into every session.
When invoked 1,038 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.01038 $0.01038
Opus 5 $0.00519 $0.00519
Sonnet 5 $0.00208 $0.00208
Haiku 4.5 $0.00104 $0.00104

Measured 6d ago against content hash ced0403d24e6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

sentry-instrumentation AGENTS.md 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 6d 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.

AGENTS.md · 101 lines

How it starts

The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agents guide — sentry-instrumentation

What this repo is

sentry-instrumentation is an Anthropic-format skill: a set of rules, references, and drop-in code patterns that teach AI coding agents how to add Sentry instrumentation the right way — both metrics (counter / gauge / distribution, duration, failure, resource) and tracing (the gen_ai.* spans for AI agent conversations). The canonical reference ships in Python under examples/python/, but the patterns are language-neutral and port to TypeScript, Go, Ruby, etc. The skill is production-tested at Torta Studios.

This is not an application. There is nothing to run from this repo — it is installed into consumer projects so that an AI agent working in those projects reads its rules.

This repo has no "skill registry"

There is no cross-agent "skill registry file" standard. Each supported agent discovers skills its own way:

Agent Discovery file
Claude Code SKILL.md YAML frontmatter under ~/.claude/skills/ or .claude/skills/
Claude.ai (web) SKILL.md YAML frontmatter uploaded via Settings → Skills
Codex AGENTS.md at project root
Cursor .cursor/rules/*.mdc
Aider CONVENTIONS.md (or any file passed via --read)
Continue .continuerules
Windsurf .windsurfrules

The install shape for each agent lives under adapters/<agent>.md. The matrix is in adapters/README.md.

If you're a Codex agent asked to install this skill

One command, from inside the cloned skill repo:

scripts/install.sh --agent=codex --project=/path/to/consumer/project

That appends the Skill-enable block below into the consumer project's AGENTS.md, bracketed by marker comments so re-runs update in place.

If you prefer to do it by hand, copy the block below into the consumer project's AGENTS.md, and adjust the paths to point at the cloned skill on disk.

Skill-enable block (copy into consumer AGENTS.md)

<!-- BEGIN sentry-instrumentation -->
## Sentry instrumentation

This project uses the `sentry-instrumentation` skill. When writing code
that emits a Sentry metric, measures duration, counts failures, wraps a
workflow step, adds a retry or fallback path, or instruments an AI agent
/ LLM call / tool call / conversation:

1. Read `<path-to-skill>/SKILL.md`.
2. Follow its decision rules and surface patterns.
3. For deeper rules (tagging, cost model, lifecycle, AI agent
   conversations), open the relevant file under
   `<path-to-skill>/references/`.
4. Use `<path-to-skill>/examples/python/` as the canonical drop-in
   reference.

Never hand-roll emissions — use the surface patterns (middleware,
decorator, base class). Never pass a raw string to an emit helper. For
AI agents, use `gen_ai.*` spans and set `gen_ai.conversation.id` per
turn — keep the conversation id and message bodies on span attributes,
never on a metric tag.
<!-- END sentry-instrumentation -->

Read the full file on GitHub · 101 lines

Changes

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.

  1. 6d ago First seen · 101 lines · 1,038 tokens per session scan A ced0403d24e6

Subscribe to this mod's changes

sentry-instrumentation AGENTS.md is an instructions file published in the GitHub repository tortastudios/sentry-instrumentation (24 stars, last pushed 2mo ago), licensed MIT. It adds 1,038 tokens to every session, about $0.0052 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.

Related

Other instructions, from other repositories

vscode buildNext.instructions.md

Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).

microsoft/vscode · 6,785 tokens

codex AGENTS.md

AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.

openai/codex · 5,182 tokens

vscode oss-third-party-notices.instructions.md

Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).

microsoft/vscode · 5,001 tokens

spec-kit AGENTS.md

AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.

github/spec-kit · 7,104 tokens

next.js AGENTS.md

AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.

vercel/next.js · 7,296 tokens

langchain AGENTS.md

AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.

langchain-ai/langchain · 4,469 tokens