anarlog is a local-first AI meeting notetaker that captures device audio, transcribes meetings, and stores notes, transcripts, and recordings on the user's computer. It is for people who want meeting notes without adding a bot to calls or sending conversation data to an external cloud. The catalogue entries provide agent integrations and workflows for the application.
Borrowing it
Nothing to install: this file belongs to fastrepl/anarlog. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/fastrepl/anarlog/main/.agents/skills/anarlog-workflow/SKILL.mdgit clone --depth 1 https://github.com/fastrepl/anarlogWrote 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/fastrepl/anarlog/anarlog-workflow)<a href="https://agentmods.dev/skills/fastrepl/anarlog/anarlog-workflow"><img src="https://agentmods.dev/badge/skills/fastrepl/anarlog/anarlog-workflow/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/fastrepl/anarlog/anarlog-workflow"><img src="https://agentmods.dev/badge/skills/fastrepl/anarlog/anarlog-workflow.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00069 | $0.01156 |
| Opus 5.5 | $0.00028 | $0.00462 |
| Sonnet 5.5 | $0.00014 | $0.00231 |
| Haiku 4.5 | $0.00007 | $0.00116 |
Grade A, and why
anarlog-workflow 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 21d 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 — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Anarlog workflow
Apply to Anarlog repository or Anarlog desktop, web, mobile, and API work. Apply the same workflow in other checkouts and worktrees.
Use Linear for work tracking and facts worth remembering. Keep implementation and verification details in commits, PRs, and CI.
Write everything you log or edit in English, even when the conversation is in another language: Linear issues, comments, and documents; Slack updates; commits, PRs, and review replies; code comments and docs. Only replies to the user in the conversation follow the user's language, and localized product content such as translation catalogs keeps its target language.
Do not read, create, edit, or comment in Notion for Anarlog work. Anarlog does not use Notion; keep its decisions and durable context in Linear.
- Team: Anarlog (
ANLG). - Workspace: fastrepl-inc.
- Agent lessons.
Start work immediately
- Default to execution. When the user requests a change, reports a bug, or scopes work, start investigating and implementing immediately and carry it through to completion. Document only when the criteria below are met; documentation is not a prerequisite or the deliverable.
- Only use a discussion-first workflow when the user explicitly asks for brainstorming, exploration of ideas, or planning without implementation. Answer informational questions directly.
- Search Linear issues, documents, and comments for the topic, IDs (
ANLG-123), and nearby decisions alongside execution. Read matching issues/docs and the team's Agent lessons early enough to inform relevant implementation decisions. Do not make this pass a prerequisite for starting useful work. - Reuse an existing issue when one fits. Create one for work that needs tracking, such as a feature, substantial behavior change, or unresolved bug; do not create an issue just to log a small completed edit. Use the right team and existing project. Update status when it changes without adding a routine progress comment.
- If Linear is unavailable, continue authorized work and report a recording gap only when there is useful context to preserve. Existing approval requirements for external actions and shared history still apply.
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.
- 21d ago Changed · +2 lines 106d0b233e5e
- 27d ago Changed · +2 lines 74e9bf32ad1f
- 1mo ago Changed · +11 lines · -1 tokens per session 020db408ba76
- 1mo ago First seen · 39 lines · 70 tokens per session scan A 6eddc7b58610
anarlog-workflow is a skill published in the GitHub repository fastrepl/anarlog (9,621 stars, last pushed yesterday), licensed MIT. It adds 69 tokens to every session and 1,156 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-13.
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