Catch Report logo

Catch Report

Organization
sno-ai
catch-report

Report how many problems the two brains found: mutual review (the other model checks the work, from the peer-review records) and self-check (an agent finds its own error in its own conversation, judged by that agent's own model), side by side. Use when the owner asks whether the second agent or the reviews are worth it, or wants the week's review results.

Overview

Publishersno-ai
Repositorysno-station-skills
Skill namecatch-report
Stars
604
Forks
415
Bundled files
3
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by sno-ai on GitHub. Read the source before you install it.

Installation

Install the Catch Report AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/sno-ai/sno-station-skills/tree/main/skills/H-reporting-and-visibility/catch-report/skill
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/sno-ai/sno-station-skills.git /tmp/sno-station-skills
mkdir -p .claude/skills
cp -r /tmp/sno-station-skills/skills/H-reporting-and-visibility/catch-report/skill .claude/skills/catch-report
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Catch Report in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Catch Report on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Catch Report is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

catch-report

The product claim is two brains: one does the work, another checks it. sno catch-report puts numbers on that claim from records already on this machine. It changes nothing.

  • Mutual review is every review the peer-review skill recorded: a different model read the work and reported problems. sno catch-report run prints those numbers.
  • Self-check is an agent finding its own error inside one conversation. sno catch-report self reads the agents' own conversations (~/.claude/projects, ~/.codex/sessions), picks the moments where an agent reacted to a failing command or test, or admitted a mistake, and asks that agent's own model (claude judges claude conversations, codex judges codex conversations) whether the agent found the error itself or was told. It then prints the two side by side.

Prerequisites: bash 4+, GNU date, find and grep, and jq. self also needs the claude and/or codex command line, logged in.

Use

  1. To show the user what the two brains caught, run sno catch-report brief --since 7d (or 12h, 30m, 30d, or a date). It measures both and prints one page: a headline with the problems the second model caught and the moments in which the agents caught their own mistakes (kept apart, never added together), the second brain's numbers with its biggest catches quoted by title, the agents' own catches in their own words, and how to read the numbers. Tell the user first that the self-check part sends short excerpts of their conversations to their own claude or codex (100 by default, about four minutes, it costs tokens); --limit N changes that, and --agent claude or --agent codex narrows it. --agent cursor reads Cursor's conversations (~/.cursor/projects/*/agent-transcripts) instead and has cursor-agent judge them; Cursor transcripts hold no tool output, so only its spoken admissions count there, and no per-message times, so a Cursor conversation updated in the period counts with its whole history.
  2. Hand the page to the user as printed, headline first, in English: do not translate it or re-word it. Keep every number and the plausible range exactly as printed, keep the quotes, and keep the "How to read this" notes. Do not round up, do not add a claim the page does not make, and do not say the findings are "real problems" or whose work was wrong: the records hold no author and most findings are undecided. You may add one sentence on what stands out.
  3. When the page says the self-check could not be measured, say that; do not report a zero. The self-check count is an estimate from a sample when there are more moments than --limit, and only sees errors an agent said out loud within ten steps of a failure or in a known admission phrase (English and Chinese); quiet fixes are not seen.
  4. For the details behind a number: sno catch-report run prints the review records (reviews started, finished, refused and never finished; per reviewer model the high and medium findings and fix-now; verdicts; the five reviews with the most fix-now; findings the owner has ruled on), and sno catch-report self --list prints each self-check moment with the model's verdict. Both take --stats FILE and --findings FILE for records kept elsewhere. The records are ~/.local/state/codex-review-stats.jsonl and ~/.local/state/codex-reviews/findings.jsonl.
  5. To make the ruled column mean something, rule on findings with review-findings.sh set <id> accepted|rejected|superseded (the peer-review skill); this command never rules on anything.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Catch Report AI skill do?

Report how many problems the two brains found: mutual review (the other model checks the work, from the peer-review records) and self-check (an agent finds its own error in its own conversation, judged by that agent's own model), side by side. Use when the owner asks whether the second agent or the reviews are worth it, or wants the week's review results.

Why use Catch Report on TypingMind?

Because you install it once and use it with any model. Catch Report is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Catch Report in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/sno-ai/sno-station-skills/tree/main/skills/H-reporting-and-visibility/catch-report/skill. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Catch Report?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Catch Report?

As many as you like. As long as a model supports skills, you can use Catch Report with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Catch Report AI skill free?

Yes. It is published on GitHub by sno-ai under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇