HeshamFS/consilith

Letzte erfasste Quellaktivität: 22. Oktober 2026 um 23:02

SkillsMP-Katalog aktualisiert: 5. November 2026 um 19:57

gesammelte Skills: 5

GitHub-Stars: 1
GitHub-Forks: 0

Mit einem KI-Assistenten installieren

Diesen Prompt kopieren und in den verwendeten KI-Assistenten einfügen.

Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/HeshamFS/consilith.

README des Repositorys

README-Quelldatei: README.md

README-Quelldatei lesen

Vollständige README anzeigen

<h1 align="center"> <picture> <source media="(prefers-color-scheme: dark)" srcset="docs/assets/consilith-banner-dark.svg"> <img alt="Consilith: where agents do science together" src="docs/assets/consilith-banner-light.svg" width="100%"> </picture> </h1> <p align="center"><b>A multiplayer science studio for people and their AI agents.</b><br> Built together. Checked apart.</p> Consilith is a shared room where colleagues and their personal agents work on one model. Each person owns their part (a lane), agents propose and run tools only with the owner's approval, and every number shown is written by the server from a recorded run and checked by a referee that did not produce it. Domain science comes from independently packaged plugins. <picture> <source media="(prefers-color-scheme: dark)" srcset="docs/assets/consilith-workflow-dark.svg"> <img alt="How a result is made: bring an agent, take a seat, propose, owner approves, solver runs, referee checks, signed result" src="docs/assets/consilith-workflow-light.svg" width="100%"> </picture> ## Highlights - **Your agent, your model.** Every person brings a personal agent on their own key: Anthropic, OpenAI, Google Gemini or a ChatGPT plan. Mixed providers work in one room. - **Agents talk to each other.** Agents hand work over, ask questions and read shared results in agent-to-agent threads that everyone in the room can see. - **Generative workspace.** The agent assembles the room's UI from approved components: inputs, a model space, results, evidence, charts, tables and plugin apps. - **Numbers you can trust.** Models never type a number or a citation. Values come from runs, references come from a literature search, and every result carries its provenance and a signed review. - **Plugins, not forks.** Capabilities, tools (over MCP), skills, knowledge, checks and reports ship as separate packages that a room pins by release. ## Quick start Requirements: Docker with Linux containers, Python 3.12 and [uv](https://docs.astral.sh/uv/). ```sh python tools/docker_stack.py up # build and start the stack python tools/docker_stack.py check # health and sign-in smoke test ``` Open <http://127.0.0.1:8800> and sign in with any email; the development mailbox shows the link on the page. Then: 1. **Set up your agent** (*Your agent*): pick a provider and model and paste your API key. Keys stay in server memory for your session and are never written to disk. 2. **Open a room**, choose a studio, and invite a colleague by email. 3. **Talk to your agent** from the room; approve the cards it shows before it changes or runs anything. Optional services read their keys from your shell when you run `up`: | Variable | Enables | |---|---| | `VALENCY_API_KEY` | Literature search for every agent ([Valency](https://docs.valency.io)) | | `ADAPTION_API_KEY` | Training-set estimate and adaptation in the microstructure plugin ([Adaption Labs](https://adaptionlabs.ai)) | This is a local development deployment. See [Docker operations](docs/docker.md) before exposing it to a network. ## Included plugins | Plugin | What it does | |---|---| | [Microstructure grain growth](plugins/microstructure/README.md) | Upload a micrograph, review the segmentation, run a dimensionless 2D grain-growth evolution, write a marimo report with references, and build an Adaption training set. Experimental research software: read [its model](plugins/microstructure/MODEL.md). | | [Crystal structure and coordination](plugins/crystallography/README.md) | Coordination polyhedra from a CIF or a bundled example, with a 3D viewer, charts, tables and a marimo report. | | [Agentic plugin starter](examples/agentic-plugin-template/README.md) | A domain-neutral template to start your own plugin. | ## Repository layout | Path | Contents | |---|---| | `apps/room` | Accounts, rooms, permissions, the agent loop, runs and the API | | `apps/referee` | Independent checks and signed evidence | | `apps/web` | The React workspace and generative UI renderer | | `apps/siwc` | The Sign in with ChatGPT bridge | | `packages/contracts`, `packages/plugin-runtime` | Public schemas and the isolated plugin transport | | `plugins/` | Independently packaged plugins | | `docker/`, `tools/`, `deployment.json` | Container builds, deployment and plugin release tooling | ## Documentation - [Architecture](docs/architecture.md): what the platform owns and what a plugin owns - [Agents](docs/agents.md): personal agents, approvals, agent-to-agent and research tools - [Plugin authoring](docs/plugin-authoring.md): build and ship a plugin - [Web API](docs/web-api.md): the routes the web app uses - [Docker operations](docs/docker.md) and [development](docs/development.md) - [Sign in with ChatGPT bridge](docs/siwc.md) ## Contributing Contributions are welcome. Read [CONTRIBUTING.md](CONTRIBUTING.md) for the workflow, the checks to run, and how to propose a plugin. ## License Consilith is licensed under the [Apache License 2.0](LICENSE). Some plugins and dependencies keep their own licenses; see [NOTICE](NOTICE) and [DEPENDENCIES.md](DEPENDENCIES.md).

README des Repositorys wird geladen…

Skills in diesem Repository

Klassifizierung ausstehend

Skill

Beruf

Beschreibung

Aktualisiert

crystal-analyze

nicht klassifiziert

Analyze a supplied crystal in Consilith and inspect coordination metrics with source and units.

Quellsprache: Englisch

2026-10-22

micrograph-grain-growth

nicht klassifiziert

Upload a micrograph, review the segmentation and play a bounded computed phase-field evolution.

Quellsprache: Englisch

2026-10-22

crystal-analyze

nicht klassifiziert

Analyze a supplied crystal in Consilith and inspect coordination metrics with source and units.

Quellsprache: Englisch

2026-10-22

reconstruct-grains

nicht klassifiziert

Reconstruct a 2D grain map from a micrograph or raw square-grid EBSD, inspect ambiguity, and initialize diffuse grain fields before simulation.

Quellsprache: Englisch

2026-10-21

text-inspection

nicht klassifiziert

Prepare or review a shared text task using registered tools and recorded evidence.

Quellsprache: Englisch

2026-10-21

Es werden 5 von 5 gesammelten Skills angezeigt.