Agent skill

Release Telemetry

by fastrepl in fastrepl/anarlog

Review Anarlog product analytics and error reporting for releases, preserving consent and verifying shipped attribution, ingestion, and symbols for affected paths.

MITAuto-check passedData & Analytics

Install Release Telemetry

skills CLI
$ npx skills add fastrepl/anarlog --skill release-telemetry -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install fastrepl/anarlog release-telemetry --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/fastrepl/anarlog.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/release-telemetry .claude/skills/release-telemetry && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
release-telemetry
GitHub stars
9.5k
Token cost
~850 tokens
SKILL.md length
364 words
Files
1
Skills in repo
32
Repo updated
First seen
Licence
MIT

At a glance

Review Anarlog product analytics and error reporting for releases, preserving consent and verifying shipped attribution, ingestion, and symbols for affected paths.

  • Works in 5 steps: Trace changed journeys through… → Keep product analytics consent separate… → Run affected component tests using… → …
  • Tasks that involve Product analytics
  • SKILL.md covers Implementation map and Review and verification
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Release Telemetry is an agent skill from fastrepl/anarlog. Review Anarlog product analytics and error reporting for releases, preserving consent and verifying shipped attribution, ingestion, and symbols for affected paths.

Its SKILL.md is about 850 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Data & Analytics, covering Product analytics. The repository describes itself as: Open source Granola AI Alternative. The licence is MIT.

When your agent uses it

  • Tasks that involve Product analytics

Example prompts

  • “/release-telemetry”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Trace changed journeys through event/error production, consent/channel gates,
  2. Keep product analytics consent separate from crash-reporting consent. Preserve
  3. Run affected component tests using current CI commands, including opt-out,
  4. Verify affected PostHog ingestion and Sentry ingestion/symbolication against the
  5. Keep mocks, successful transport, destination ingestion, and symbolication as

What it can do on your machine

Read from SKILL.md and the folder at commit 385e117. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Release Telemetry loads about 850 tokens when it runs. Until then it costs about 45 tokens; SKILL.md has 364 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~45
When it runs · the whole SKILL.md, loaded when a task matches
~850

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from fastrepl/anarlog at commit 385e117, republished under its MIT licence (© fastrepl). 364 words, ~850 tokens.

Download SKILL.mdSave it as .claude/skills/release-telemetry/SKILL.md (or your agent's skills folder).
name
release-telemetry
description
Review Anarlog product analytics and error reporting for releases, preserving consent and verifying shipped attribution, ingestion, and symbols for affected paths.
metadata.internal
true

Release Telemetry

Review every release; implement and verify affected paths and known gaps. Inherit scope and session authorization from Release a New Version. Do not turn a release review into an unrelated telemetry migration.

Implementation map

  • Desktop product events: apps/desktop/src/analytics.ts, plugins/analytics/, and crates/analytics/.
  • Desktop errors and consent: apps/desktop/src-tauri/src/lib.rs, plugins/tracing/, and current privacy/settings wiring.
  • Website: apps/web/src/providers/posthog.tsx, analytics/privacy helpers under apps/web/src/lib/, and apps/web/src/telemetry.ts for browser tracing.
  • Hosted services: apps/api/src/main.rs, affected API/proxy instrumentation, and apps/stripe/ when billing changes.
  • Requested mobile releases: apps/mobile/src/lib/analytics.ts and the current mobile error-reporting/bootstrap path. Do not infer desktop coverage applies.
  • Native symbols and web source maps: desktop_cd.yaml, web_cd.yaml, and their actions. Inspect the actual platform steps and destinations before checking uploads.

Review and verification

  1. Trace changed journeys through event/error production, consent/channel gates, sanitization, transport, and destination. Cover success, failure, cancellation, retries, and recovery where affected. Reuse existing instrumentation with evidence; implement required missing coverage before candidate freeze or record an explicit deferral and impact.
  2. Keep product analytics consent separate from crash-reporting consent. Preserve opt-out, private-route/global-privacy gates, redaction, deduplication, and bounded asynchronous delivery. Never include note/transcript content, credentials, keys, or raw private identifiers as diagnostic fixtures. Telemetry failure must not block recording, saving, or recovery.
  3. Run affected component tests using current CI commands, including opt-out, sanitization, retry and collector-failure cases. Verify APP_VERSION, channel, environment and serving revision reach events from the actual packaged or deployed runtime. Developer SDK initialization is not shipped evidence.
  4. Verify affected PostHog ingestion and Sentry ingestion/symbolication against the shipped release and each deployed service revision. Use existing authorized test accounts and harmless synthetic diagnostics where supported; do not crash the user's working app or change their consent to obtain evidence. For disabled channels, verify no emission. Inspect matching native debug IDs/source maps; upload success alone does not prove a captured stack is symbolicated.
  5. Keep mocks, successful transport, destination ingestion, and symbolication as distinct evidence. Empty queries do not prove no events occurred. If credentials or suitable runtime evidence are unavailable, report that specific unchecked result; do not claim success or silently add a new release dispatch.
Show full SKILL.md (19 more words)Show less

Return coverage/update or reuse decisions, source/runtime versions, consent and privacy checks, destination evidence, and pending gaps to the coordinator.

© fastrepl, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/release-telemetry of fastrepl/anarlog.

Open the folder on GitHubat commit 385e117

Compare with similar skills

Release Telemetry next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Release Telemetry compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Release Telemetry this skillfastrepl/anarlog9.5k—~850Automated safety check: PassMIT
PostHog CLI Queriesdebugtheworldbot/keyStats1.5k—~1.2kAutomated safety check: PassMIT
Retentioneering Contributingretentioneering/retentioneering-tools920—~1.8kAutomated safety check: PassApache-2.0
Retentioneering Product Analyticsretentioneering/retentioneering-tools920—~1.6kAutomated safety check: PassApache-2.0
Retention Analysisliangdabiao/claude-data-analysis-ultra-main2901 repos~1.3kAutomated safety check: NotesNone
Feature Analytics Instrumentation Plannermistralai/mistral-vibe5.1k—~2.2kAutomated safety check: PassApache-2.0

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Questions about Release Telemetry

What does Release Telemetry do?

Review Anarlog product analytics and error reporting for releases, preserving consent and verifying shipped attribution, ingestion, and symbols for affected paths. Release Telemetry is an agent skill from fastrepl/anarlog. Review Anarlog product analytics and error reporting for releases, preserving consent and verifying shipped attribution, ingestion, and symbols for affected paths.

When should I use Release Telemetry?

Release Telemetry fits situations like: tasks that involve Product analytics.

How do I install Release Telemetry in Claude Code?

Run `npx skills add fastrepl/anarlog --skill release-telemetry -a claude-code`. Or copy the skill folder (.agents/skills/release-telemetry in fastrepl/anarlog) into .claude/skills/release-telemetry in your project. Claude Code loads it when a task matches its description.

How do I install Release Telemetry in Codex?

Run `npx skills add fastrepl/anarlog --skill release-telemetry -a codex`. Or copy the skill folder (.agents/skills/release-telemetry in fastrepl/anarlog) into .agents/skills/release-telemetry in your project. Codex loads it when a task matches its description.

Can I use Release Telemetry in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add fastrepl/anarlog --skill release-telemetry -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/release-telemetry, .gemini/skills/release-telemetry, .github/skills/release-telemetry and .opencode/skills/release-telemetry in your project.

What does Release Telemetry need to run?

SKILL.md names no scripts, command-line tools or credentials: Release Telemetry is instructions for the agent only.

Does Release Telemetry access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Release Telemetry safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Release Telemetry use?

Release Telemetry is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Release Telemetry use?

About 850 tokens (SKILL.md is roughly 3.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Release Telemetry?

Skills that share tags, products or a category with Release Telemetry: PostHog CLI Queries (debugtheworldbot/keyStats, 1.5k stars), Retentioneering Contributing (retentioneering/retentioneering-tools, 920 stars), Retentioneering Product Analytics (retentioneering/retentioneering-tools, 920 stars) and Retention Analysis (liangdabiao/claude-data-analysis-ultra-main, 290 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Release Telemetry?

fastrepl (a GitHub organization) maintains it in fastrepl/anarlog, which has 9,452 GitHub stars. The repository holds 32 skills in this directory. The repository was last updated on October 8, 2026.

Source: fastrepl/anarlog on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.