TypingMindTypingMindThe best frontend for AI
System Execution Report logo

System Execution Report

Community
coleam00
system-execution-report

Generates a structured implementation report reflecting on a just-completed feature — what was done, divergences, challenges. Use right after finishing an implementation, as the input to a system review.

Overview

Publishercoleam00
Repositoryskills
Skill namesystem-execution-report
Stars
678
Forks
184
Bundled files
Instructions only
LicenseMIT
Links
Skill sourceRepository
  • 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 coleam00 on GitHub. Read the source before you install it.

Installation

Install the System Execution 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/coleam00/skills/tree/main/.claude/skills/system-execution-report
  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/coleam00/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/.claude/skills/system-execution-report .claude/skills/system-execution-report
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable System Execution 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 System Execution 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 System Execution 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.

Execution Report

Review and deeply analyze the implementation you just completed.

Context

You have just finished implementing a feature. Before moving on, reflect on:

  • What you implemented
  • How it aligns with the plan
  • What challenges you encountered
  • What diverged and why

Generate Report

Save to: .claude/execution-reports/[feature-name].md

Meta Information

  • Plan file: [path to plan that guided this implementation]
  • Files added: [list with paths]
  • Files modified: [list with paths]
  • Lines changed: +X -Y

Validation Results

  • Syntax & Linting: ✓/✗ [details if failed]
  • Type Checking: ✓/✗ [details if failed]
  • Unit Tests: ✓/✗ [X passed, Y failed]
  • Integration Tests: ✓/✗ [X passed, Y failed]

What Went Well

List specific things that worked smoothly:

  • [concrete examples]

Challenges Encountered

List specific difficulties:

  • [what was difficult and why]

Divergences from Plan

For each divergence, document:

[Divergence Title]

  • Planned: [what the plan specified]
  • Actual: [what was implemented instead]
  • Reason: [why this divergence occurred]
  • Type: [Better approach found | Plan assumption wrong | Security concern | Performance issue | Other]

Skipped Items

List anything from the plan that was not implemented:

  • [what was skipped]
  • Reason: [why it was skipped]

Recommendations

Based on this implementation, what should change for next time?

  • Plan skill improvements: [suggestions]
  • Execute skill improvements: [suggestions]
  • CLAUDE.md additions: [suggestions]

Frequently asked questions

What does the System Execution Report AI skill do?

Generates a structured implementation report reflecting on a just-completed feature — what was done, divergences, challenges. Use right after finishing an implementation, as the input to a system review.

Why use System Execution Report on TypingMind?

Because you install it once and use it with any model. System Execution 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 System Execution Report in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/coleam00/skills/tree/main/.claude/skills/system-execution-report. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use System Execution 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 System Execution Report?

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

Is the System Execution Report AI skill free?

Yes. It is published on GitHub by coleam00 under the MIT 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.

Related AI Skills

View all
affaan-m logo

Test Collaboration

affaan-m
CommunityPopular

Inventory and govern a project's test assets. Connect requirements, business rules, risks, bugs, and cross-boundary contracts to stable TEST-IDs and executable evidence in the repository's existing…

41.4K
277.3K
2 files
View
affaan-m logo

Competitive Report Structure

affaan-m
CommunityPopular

Use after benchmark-methodology has produced scored competitor profile cards. Assembles findings into a decision-grade report: landscape map, competitor profiles, benchmarking matrix, white-space…

40.4K
270.2K
1 files
View
affaan-m logo

Dmux Workflows

affaan-m
CommunityPopular

Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across Claude Code, Codex, OpenCode, and other harnesses. Use when running multiple agent…

40.4K
270.2K
1 files
View
affaan-m logo

Documentation Lookup

affaan-m
CommunityPopular

Use up-to-date library and framework docs via Context7 MCP instead of training data. Activates for setup questions, API references, code examples, or when the user names a framework (e.g. React,…

40.4K
270.2K
1 files
View

Set up your own AI workspace now

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