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Sred Work Summary

OrganizationPopular
getsentry
sred-work-summary

Go back through the previous year of work and create a Notion doc that groups relevant links into projects that can then be documented as SRED projects.

Overview

Publishergetsentry
Repositoryskills
Skill namesred-work-summary
Stars
1K
Forks
53
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by getsentry on GitHub. Read the source before you install it.

Installation

Install the Sred Work Summary 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/getsentry/skills/tree/main/skills/sred-work-summary
  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/getsentry/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/sred-work-summary .claude/skills/sred-work-summary
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sred Work Summary 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 Sred Work Summary 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 Sred Work Summary 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.

SRED Work Summary

Collect all the Github PRs, Notion docs and Linear tickets a person completed in a given year. Group the links from all of those into projects. Put everything into a private Notion document and return a link to that document.

Prerequisites

Before starting make sure that Github, Notion and Linear can be accessed. Notion and Linear should be connected using an MCP. Github can be connected with an MCP, but if you have access to the gh CLI tool, you can use that instead.

If any of these can't be accessed, prompt the user to grant access before proceeding.

Process

Step 1

bash
# Get the current year
date +%Y

The output of this command is the current year. The current year minus one is the previous year.

Step 2

Collect all of the required information from the user:

Github Username: What is the github username of the user?

Github Repositories: Which Github repositories should be searched for PRs?

The user can either specify a comma separated list, or provide a directory that contains repositories. In the second case use this command in the specified directory:

bash
# Find github repos
find . -maxdepth 2 -name ".git" -type d | sed 's/\/.git$//' | sort

Ensure:

  • All the repositories listed are in the getsentry Github organization.

The output of this is hereafter referred to as the "user repos".

Incidents: Ask if the user wants to include incident documents.

The answer is either yes or no. If the answer is no, that will exclude certain documents from the search later on.

Other Users: Ask if there are any other users who might have created Notion documents.

This should be a comma separated list of names. Remember this as the "other users".

Step 3

Create a private Notion document entitled "SRED Work Summary [current year]". This document will be referred to as the Work Summary.

If a document with this name already exists, notify the user to rename the existing document and stop executing.

Ensure:

  • If the Work Summary already exists, stop execution.

Step 4

The time window is Feb. 1 of the previous year until Jan. 31 of the current year Find all Github PRs created by the given github username in the time window for the user repos. If the user does not want to include incident documents, ignore any Github PRs with INC-X, inc-X in the title or description. Use either the Github MCP or the gh command to do this.

Find all the Notion documents the user created in the time window. If the user does not want to include incident documents, ignore any Notion Documents with INC-XXXX in the title. Use the Notion MCP to do this.

Find all the Linear tickets the user was assigned in the time window. If the user does not want to include incident documents, ignore any Linear tickets with INC-XXXX in the title. Use the Linear MCP to do this.

Ensure:

  • All the Github PRs were created or merged in the time window and was opened by the user.
  • All the Notion docs were created in the time window and were created by the user.
  • All the Linear tickets were opened or completed in the time window and were assigned to the user when they were completed.

Step 5

For each of the Github PRs, Notion documents and Linear tickets found in Step 4, put a link into the private document created in Step 3.

Ensure:

  • There is a link for all the Github PRs in the Work Summary
  • There is a link for all the Notion docs in the Work Summary
  • There is a link for all the Linear tickets in the Work Summary
  • DO NOT truncate the lists of links. DO NOT use shorteners like "...and 75 more". Make sure that the full set of all Github PRs, Notion documents and Linear tickets is visible in the document.

Step 6

Use your own intelligence to group all the Github, Notion and Linear ticket links in the Work Summary document into projects. The format of this document is shown below.

markdown
# Projects

## [Project Name]
*Summary*: [X] PRs, [X] Notion docs, [X] Linear tickets

### Pull Requests [X]
*[repository name]
[Links to all the PRs]
- [link] - [Merge date]

### Notion Docs [X]
[Links to all the Notion docs]
- [link] - [Creation date]

### Linear Tickets [X]
- [link] - [Creation date]

For Github PRs, use both the title of the PR and the description of the PR for grouping. For Notion documents, use the full document for grouping. For Linear tickets use the title of the ticket and the description of the ticket.

Ensure:

  • All the links in the file are assigned to a project.
  • The file follows the format specified above.
  • DO NOT truncate the lists of links. DO NOT use shorteners like "...and 75 more". Make sure that the full set of all Github PRs, Notion documents and Linear tickets is visible in the document.

Step 7

Search for notion documents created by the "other users". Take any that are relevant to the projects in the Work Summary and add links to those Notion documents into the Work Summary in the appropriate project.

Step 8

Return a link to the Work Summary Notion doc to the user.

Ensure:

  • The actual Notion document link is in the final output.

Resources

This is an example Working Summary document for the year 2025: https://www.notion.so/sentry/Work-Summary-Feb-2025-Jan-2026-3068b10e4b5d81d3a40cfa6ad3fe1078?source=copy_link

Frequently asked questions

What does the Sred Work Summary AI skill do?

Go back through the previous year of work and create a Notion doc that groups relevant links into projects that can then be documented as SRED projects.

Why use Sred Work Summary on TypingMind?

Because you install it once and use it with any model. Sred Work Summary 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 Sred Work Summary in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/getsentry/skills/tree/main/skills/sred-work-summary. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Sred Work Summary?

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 Sred Work Summary?

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

Is the Sred Work Summary AI skill free?

Yes. It is published on GitHub by getsentry 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.

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