meeting-notes-transcription-fixer

meeting-notes-transcription-fixer is a skill for Claude Code, Codex from regen-coordination/org-os-template. It costs 75 tokens per session (1,630 once invoked), scanned A, original, MIT.

A tool for checking and repairing meeting notes and transcripts in an organization’s shared workspace. It fixes missing metadata, broken project links, and recurring mistakes in names and acronyms.

In plain words
What is it for?
Use it to audit meeting backlogs, repair note structure, correct transcription errors, and prepare notes for further processing.
Why use it?
It removes manual cleanup from raw or older meeting files before they are processed or searched. Organization-specific terms can be corrected using a local list.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Use it to audit meeting backlogs, repair note structure, correct transcription errors, and prepare notes for further processing.

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Install with agentmods
npx agentmods add skills/regen-coordination/org-os-template/meeting-notes-transcription-fixer
Install

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.

Any agent
npx skills add regen-coordination/org-os-template --skill meeting-notes-transcription-fixer
Clone the repo
git clone --depth 1 https://github.com/regen-coordination/org-os-template

Made for: Claude Code, Codex.

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 meeting-notes-transcription-fixer

README.md
[![agentmods](https://agentmods.dev/badge/skills/regen-coordination/org-os-template/meeting-notes-transcription-fixer/github.svg)](https://agentmods.dev/skills/regen-coordination/org-os-template/meeting-notes-transcription-fixer)
Your own site
<a href="https://agentmods.dev/skills/regen-coordination/org-os-template/meeting-notes-transcription-fixer"><img src="https://agentmods.dev/badge/skills/regen-coordination/org-os-template/meeting-notes-transcription-fixer/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.

agentmods 80×15 button for meeting-notes-transcription-fixer

Your own site · 80×15
<a href="https://agentmods.dev/skills/regen-coordination/org-os-template/meeting-notes-transcription-fixer"><img src="https://agentmods.dev/badge/skills/regen-coordination/org-os-template/meeting-notes-transcription-fixer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,630 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00075 $0.01630
Opus 5 $0.00037 $0.00815
Sonnet 5 $0.00015 $0.00326
Haiku 4.5 $0.00007 $0.00163

Measured 9d ago against content hash e79d98ae507d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

meeting-notes-transcription-fixer 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 9d ago.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/audit_meeting_notes.py, scripts/build_fix_queue.py, scripts/fix_meeting_frontmatter.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/meeting-notes-transcription-fixer/SKILL.md · 156 lines

How it starts

The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Meeting Notes Transcription Fixer

Standardize legacy and recent meeting files in an org-os instance without destroying transcript authenticity.

Each instance can maintain its own terminology dictionary (e.g., data/transcription-fixes.yaml listing recurring transcription errors like COI→KOI, Luis→Luizfernando, Zargon→Zargham, etc.). The skill consumes this dictionary at runtime.

When to Use

  • Before meeting-processor, when raw notes contain transcription errors (typos in proper nouns, acronyms misheard by the transcription tool, names of org-specific concepts/people)
  • Auditing the meeting backlog in packages/operations/meetings/ for missing frontmatter / project links / sections
  • Batch normalization of historical meeting files

Customization required before first use in a new instance: The Python scripts under scripts/ (fix_meeting_terminology.py, audit_meeting_notes.py, build_fix_queue.py, fix_meeting_frontmatter.py) ship with example dictionaries from the originating instance (ReFi DAO OS) — proper nouns, acronyms, project mappings. Before running them in your instance, edit fix_meeting_terminology.py (TERMINOLOGY_FIXES tuple) and fix_meeting_frontmatter.py (PROJECT_MAPPING dict) to reflect the recurring transcription errors and project names in your meeting corpus. Future work (tracked as meeting-notes-transcription-fixer-externalize-dict): move dictionaries to per-instance data/transcription-fixes.yaml so the scripts become fully generic.

When NOT to Use

  • One-off, clean meeting transcripts → go straight to meeting-processor
  • Processing notes that aren't yet in packages/operations/meetings/ (use this AFTER meeting-processor has filed them, or run on the source vault location first)

Core Rules

  • Preserve meaning; never invent attendees, decisions, or action items.
  • Preserve transcript authenticity; fix only obvious transcription errors.
  • Run safe/reversible operations first (audit + metadata dry-run).
  • Keep conflict/hash-suffixed files out of automatic writes unless explicitly requested.

Read the full file on GitHub · 156 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 9d ago First seen · 156 lines · 75 tokens per session scan A e79d98ae507d

Subscribe to this mod's changes

meeting-notes-transcription-fixer is a skill published in the GitHub repository regen-coordination/org-os-template (5 stars, last pushed 6d ago), licensed MIT. It adds 75 tokens to every session and 1,630 once invoked, about $0.0004 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 2026-09-03.

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