Flowtrace

Из публичных источников

Выполняйте задачи с помощью ИИ как последовательность шагов, которую можно сохранять, повторно использовать и улучшать, а не как разовый чат.

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Run a task with AI as a flow of steps you keep, reuse, and refine, not a one-off chat.

AI-инструментКатегория: AI-инструментыOpen sourceданные проверены 16 окт. 2026 г.

Обзор

  • agent-skills
  • agentic-ai
  • ai
  • ai-agent
  • ai-agents
  • anthropic
  • claude
  • claude-code
  • claude-skills
  • cli
  • codex
  • cursor

Установка

Команды только показываются, маркетплейс их не выполняет. Сверяйтесь с официальной документацией.
  • Официальный сайтИз публичных источниковиз метаданных каталога
    morphmind.ai/ ↗
  • Сборка из исходниковИз публичных источниковиз метаданных каталога

    Сборка из исходников: проверенного рецепта сборки нет — следуйте инструкциям репозитория.

    github.com/AIScientists-Dev/Flowtrace ↗

Совместимость

«Неизвестно» значит, что доказательств не найдено, а не что продукт несовместим.
ПлатформаСтатусАрхитектураДоказательствоУверенность
WindowsНеизвестно———
macOSНеизвестно———
LinuxНеизвестно———
Web browserНеизвестно———
Server / self-hostedНеизвестно———
Container (OCI)Неизвестно———

Релизы

проверено 30 окт. 2026 г.
В источнике релизы не найдены.

Профиль качества

алгоритм quality-v1.0 · оценено 16 окт. 2026 г.
Оценка качества62
Оценка риска0
Уверенность 1.00
Оценка качества и оценка риска — разные показатели. Высокое качество не гарантирует безопасность.

Составляющие оценки

Поддержка · 2012
last activity 128 days ago
Документация · 1515
README 12966 chars, description present
Готовность к использованию · 150
install instructions: no; releases: no
Метаданные · 1010
4/4 of description, homepage, license, topics
Релизы · 102
0 release(s)
Точность категории · 107
classifier confidence 0.65
Популярность · 107
485 stars (log-dampened, 10k = max)
Ясность лицензии · 55
SPDX MIT
Сообщество · 55
issues enabled, 35 forks

Лицензия

MIT
Лицензия известнапо данным хостинга репозитория

Это статус политики каталога, а не юридическое заключение.

Источники

github.com/AIScientists-Dev/FlowtraceОсновной★ 485 звёздактивность 9 июн. 2026 г.Основной репозиторий · Уверенность 1.00

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README

Из AIScientists-Dev/Flowtrace · лицензия MIT · загружено 30 окт. 2026 г.

Flowtrace

Run your agent's work as steps you can follow, check, and reuse, instead of a stream of text that buries you and then disappears.

Works with the agent you already use: Claude Code, Codex, Cursor.

[GitHub stars] [MIT License] [Homepage] [Discord] [X]

What it does · Get started · Examples · Docs

English · 简体中文

⭐ If Flowtrace looks useful, star it (button's top-right) — it's how we decide what to keep building in the open.


Real work with an agent happens as a stream of text. You run a skill and it does the whole task in one pass, or you go back and forth in a chat that keeps growing. Either way it piles up faster than you can follow, and once it is done you are left with a wall of messages.

For a quick question that is fine. For a buy or sell call, a due diligence memo, a security gate, anything you would actually need to verify or run again, it is a problem:

  • It is too much to follow. The thread grows longer than you can hold, and you lose track of what was decided and why.
  • You cannot check it. A confident wrong answer looks exactly like a right one.
  • You cannot steer it. One bad assumption in the middle means redoing the whole thing and hoping the good parts survive.
  • It does not last. Every session is a cold start, and the good ones evaporate into scrollback.

Flowtrace runs that same work as a trace: a flow of steps the agent moves through one at a time, each leaving its output on disk. Here is one, a buy or sell decision that ends in a fixed-format, citable PDF:

What it does

Same skills, same agent. Running that work as a trace is what changes:

Transparent. The work is a flow of steps you take in at a glance, not a thread you scroll. Each step's output is a file you open, so the intermediate work is right there instead of buried in messages.

Grounded. Every result points back to the files it came from, so you verify instead of trust.

Steerable. Fix one step and only what depends on it re-runs. The rest stays put.

Traceable. The whole run is files and git, so it does not vanish when you close the tab. Stop and resume anytime, hand it to a teammate, read the full history.

Reusable. A finished task becomes a trace you run again on new input. The method is reused, not rebuilt.

Evolving. The trace gets better the more it runs. When a step misses its bar, the next version switches to a method that clears it, and the version that passes is the one that sticks.

Structured reading. A trace exposes the work as a graph of files, not a linear transcript. The agent reads it by structure and on demand, loading a step's contract, inputs, and outputs only while working on it and following explicit dependencies rather than carrying the whole history. This bounds working context, reduces drift, and yields a representation people and agents can both inspect and extend.

You do not start from scratch. A skill, a long session, a plan, a finished run: run any of them as a trace and you get the same steps you can follow, check, and run again. Open any one to read it full size.

Not every task needs this. A quick one off, just chat. Flowtrace earns its place when the result matters enough to verify, or when you will run the task again.

Get started

The fast path is to hand the repo to an agent. Point a coding agent (Claude Code, Codex, Cursor) at this folder and say:

"Install Flowtrace and run the tailored-resume example."

It installs the CLI, builds a real trace at ~/traces/tailored-resume/, and opens the web view at http://localhost:3000, where the flow lights up step by step.

Two ways to get a trace:

  • Try a reference. Each example ships as a builder that creates a real trace folder and walks one full run.

    bash scripts/examples/tailored-resume/build.sh   # → ~/traces/tailored-resume/
    flowtrace serve                                  # → http://localhost:3000
    
  • Make your own. The make-trace skill turns any source (a SKILL.md, a runbook, a chat log, a finished task) into a trace. Copy skills/make-trace/ into the agent's skills directory and run /make-trace.

A run is steerable: stop at any step, change it, and the steps that depend on it re-run while the rest stay put.

git clone https://github.com/AIScientists-Dev/flowtrace.git
cd flowtrace
./scripts/install.sh        # builds + symlinks flowtrace to ~/.local/bin/

Update with git pull && ./scripts/install.sh. Override the symlink target with INSTALL_DIR=…. Building from source or contributing? See CONTRIBUTING.md.

Examples

Nine examples built from popular open-source skills, spanning different domains. Open any one for its flow and a one-command demo in the examples gallery:

Plus six more:

Documentation

A trace is one git repository. trace.json declares the steps, their dependencies, and the final deliverable. Each run lives under runs/<run_id>/:

<trace_root>/
├─ .git/                                    standard git repo, the audit trail
├─ trace.json                              the static plan (steps + deliverable)
├─ scripts/                                 shared code used by 2+ steps
├─ resources/                               shared static material (refs, papers, master data)
├─ steps/<step_id>/
│  ├─ STEP.md                               per-step contract + impl hints
│  ├─ scripts/                              step-local code
│  └─ resources/                            step-local material (figures, PDFs, fixtures)
└─ runs/<run_id>/
   ├─ state.json                            run status (sole source of truth)
   ├─ replies/NNNN.json                     append-only structured-output stream
   └─ <step_id>/                            run-time files (assets + scratch)

The same two-name convention (scripts/ for code that runs, resources/ for static material that doesn't) appears at both the trace root and inside each step. Anything reused across 2+ steps belongs at the trace root; single-step material stays inside the step folder. STEP.md references either with relative paths.

Every CLI write makes one git commit, scoped to exactly the paths it declares: state.json plus any --asset paths, or the new reply file plus its cited evidence paths. Scratch files stay untracked. The git history is the audit trail, and the UI can time-travel through it.

Steps pass data through files, not parameters: each step writes its output, and a downstream step reads it.

To learnRead
The idea, in depthPHILOSOPHY.md
Driving a trace as an agentdocs/trace/CLI.md
Making a traceskills/make-trace/SKILL.md, or run /make-trace
The format specSCHEMA.md and FIELDS.md
All examplesdocs/EXAMPLES.md

Community

If Flowtrace is useful to you, consider starring the repo. It helps others find it.


MIT. See LICENSE.

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