mcpbeat Sign in

Telemetry Skill for Codex

Add and verify lightweight macOS runtime telemetry. Use when wiring Logger events or inspecting logs for windows, sidebars, menus, and actions.

1k tokens
context cost
the whole folder, loaded on every use
2
files
instructions only
0
copies elsewhere
how many repositories repackaged it
4915
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/openai/plugins --skill telemetry

What comes with it

343 bytes besides the instruction
agents/openai.yaml

The instruction itself

7 sections, as written by the author

Telemetry

Quick Start

Use this skill to add lightweight app instrumentation that helps debug behavior

without turning the codebase into a logging landfill. Prefer Apple's unified

logging APIs and verify the events after a build/run loop.

Core Guidelines

  • Prefer Logger from the OSLog framework for structured app logs.
  • Give each feature a clear subsystem/category pair so runtime filtering stays easy.
  • Log meaningful user and app lifecycle events: window opening, sidebar selection changes, menu commands, menu bar extra actions, sync/load milestones, and unexpected fallback paths.
  • Keep info logs concise and stable. Use debug logs for noisy state details.
  • Do not log secrets, auth tokens, personal data, or raw document contents.
  • Add signposts only when measuring timing or performance spans; do not overinstrument by default.

Minimal Logger Pattern

import OSLog

private let logger = Logger(
  subsystem: Bundle.main.bundleIdentifier ?? "SampleApp",
  category: "Sidebar"
)

@MainActor
func selectItem(_ item: SidebarItem) {
  logger.info("Selected sidebar item: \(item.id, privacy: .public)")
  selection = item.id
}

Use feature-specific categories like Windowing, Commands, MenuBar, Sidebar,

Sync, or Import so logs can be filtered quickly.

Workflow

  • Identify the behavior that needs observability.
  • Window open/close
  • Sidebar or inspector selection changes
  • Menu or keyboard command actions
  • Menu bar extra actions
  • Background load/sync/import events
  • Error and recovery paths
  • Add the smallest useful instrumentation.
  • Create one Logger per feature area or type.
  • Log action boundaries and key state transitions.
  • Prefer one high-signal line per user action over noisy value dumps.
  • Build and run the app.
  • Use build-run-debug for the build/run loop.
  • If script/build_and_run.sh exists, prefer ./script/build_and_run.sh --telemetry for live telemetry checks or ./script/build_and_run.sh --logs for broader process logs.
  • Exercise the UI or command path that should emit telemetry.
  • Read runtime logs and verify the event fired.
  • Use Console.app with a process/subsystem filter when that is the fastest manual check.
  • Use log stream --style compact --predicate 'process == "AppName"' for live terminal verification.
  • Prefer tighter predicates when you know the subsystem/category:

log stream --style compact --predicate 'subsystem == "com.example.app" && category == "Sidebar"'

  • Tighten or remove instrumentation.
  • If the event fires, keep only the logs that remain useful for future debugging.
  • If it does not fire, move the log closer to the suspected control path and rerun.

Verification Checklist

  • The app builds after telemetry changes.
  • The relevant action emits exactly one clear log line or a small bounded sequence.
  • The log can be filtered by process, subsystem, or category.
  • No sensitive payloads are written to unified logs.
  • Noisy temporary debug logs are removed or demoted before finishing.

Guardrails

  • Do not use print as the primary app telemetry mechanism for macOS app code.
  • Do not leave a dense trail of permanent debug logs around every state mutation.
  • Do not claim an event is wired correctly until you have a concrete verification path through Console, log stream, or captured process output.
  • If the debugging task is mostly about crash/backtrace analysis rather than action telemetry, switch to build-run-debug.

Other skills for the same job

different authors, same section of the catalogue
Protocolsio Integration
by christophacham
×4

Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.

16k tokens
Tailored Resume Generator
by frostant
×4

Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances

3k tokens
Excalidraw Diagram Generator
by github
vendor ×3

Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.

36k tokens scripts
Executing Plans
by ZhanlinCui
×3

Use when you have a written implementation plan to execute in a separate session with review checkpoints

542 tokens
Anndata
by christophacham
×3

Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.

16k tokens
Benchling Integration
by christophacham
×3

Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.

14k tokens
Biopython
by christophacham
×3

Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.

24k tokens
Cellxgene Census
by christophacham
×3

Query the CELLxGENE Census (61M+ cells) programmatically. Use when you need expression data across tissues, diseases, or cell types from the largest curated single-cell atlas. Best for population-scale queries, reference atlas comparisons. For analyzing your own data use scanpy or scvi-tools.

8k tokens

How to use it

Copy the folder

Take openai/telemetry from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.