What makes Synomega Skill notable?

1.3K downloads. Trust evidence available

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agentCLAWHUBUnverified

Synomega Skill

Retrosynthesis, reaction prediction, and synthesizability for organic molecules, using the synomega Python package (pip install synomega) — runs locally, works out of the box. Six capabilities: single-step retrosynthesis (product → reactants, candidate disconnections), single-step forward reaction prediction / reaction outcome (reactants → product), multi-step route planning down to purchasable building blocks, a continuous synthesizability / makeability score (SynScore), reaction-plausibility screening, and multi-component evolution (growing a forward synthesis network from a set of reactants, e.g. one-pot / multicomponent chemistry). Use this whenever the user gives a molecule (as SMILES or a resolvable name) and asks how to make / synthesize it, whether it can be made or how hard, how to rank molecules by ease of synthesis, what reactants give a target, what product a set of reactants gives, a reaction outcome, or how a reactant mixture evolves — i.e. for retrosynthesis, synthesis planning, cheminformatics, and reaction-prediction tasks. Safety judgments for hazardous, controlled, or otherwise dual-use compounds are deferred to the host's safety policy (see "Safety boundary / dual-use" below).

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.3k

Updated

Oct 10, 2026

Version

1.8.1

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.3K downloads reported by the source. Last updated 10/10/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 10, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 10, 2026
Adoption signal: 1.3K downloadsadoption · observed Oct 10, 2026
Latest release: 1.8.1release · observed Aug 29, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s170n9q9jf63zng4je4m7vaafh84dkwy:synomega

Install using `clawhub skill install s170n9q9jf63zng4je4m7vaafh84dkwy:synomega` in an isolated environment before connecting it to live workloads.
No published capability contract is available yet, so validate auth and request/response behavior manually.
Review the upstream CLAWHUB listing at https://clawhub.ai/zbc0315/synomega before using production credentials.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-zbc0315-synomega/snapshot"

Documentation

CLAWHUB

147,338 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: synomega
description: >-
  Retrosynthesis, reaction prediction, and synthesizability for organic molecules,
  using the synomega Python package (pip install synomega) — runs locally, works
  out of the box. Six capabilities: single-step retrosynthesis (product → reactants,
  candidate disconnections), single-step forward reaction prediction / reaction
  outcome (reactants → product), multi-step route planning down to purchasable
  building blocks, a continuous synthesizability / makeability score (SynScore),
  reaction-plausibility screening, and multi-component evolution (growing a forward
  synthesis network from a set of reactants, e.g. one-pot / multicomponent
  chemistry). Use this whenever the user gives a molecule (as SMILES or a resolvable
  name) and asks how to make / synthesize it, whether it can be made or how hard,
  how to rank molecules by ease of synthesis, what reactants give a target, what
  product a set of reactants gives, a reaction outcome, or how a reactant mixture
  evolves — i.e. for retrosynthesis, synthesis planning, cheminformatics, and
  reaction-prediction tasks. Safety judgments for hazardous, controlled, or
  otherwise dual-use compounds are deferred to the host's safety policy (see
  "Safety boundary / dual-use" below).
---

# SynOmega

SynOmega is a **Python package** ([PyPI](https://pypi.org/project/synomega/),
[docs](https://zbc0315.github.io/synomega/)) for organic small-molecule reactions.
It exposes **six capabilities** behind one install:

| # | Capability | Direction | Helper command |
|---|---|---|---|
| 1 | **Single-step retrosynthesis** | product → reactants | `single-step` |
| 2 | **Single-step forward prediction** | reactants → product | `forward` |
| 3 | **Multi-step route planning** | target → route to purchasable stock | `plan` |
| 4 | **Synthesizability score (SynScore)** | target → 0–1 makeability | `score` |
| 5 | **Reaction-plausibility screening** | filter single-step candidates | env toggle |
| 6 | **Multi-component evolution** | reactant set → forward synthesis network | `evolve` |

It runs entirely locally. **It works out of the box** — the pretrained models and
building-block stock download automatically on first use, so there is nothing to
train or configure.

> ⚠️ **Network + disk notice (first use downloads a few hundred MB).** The first
> call automatically reaches out to a **remote mirror** (USTC GitLab and/or GitHub)
> and downloads the model(s) and stock — **a few hundred MB** — into
> `~/.cache/synomega`. Nothing else phones home, but this first fetch does.
> Controls: pre-fetch with `synomega download`; change the cache dir with
> `SYNOMEGA_CACHE`; pick a mirror with `SYNOMEGA_MIRROR` (`ustc` or `github`). In
> **air-gapped, bandwidth-limited, privacy-sensitive, or reproducibility-critical**
> environments, pre-fetch (or point at a local model/stock) and treat the download
> as an explicit opt-in rather than a surprise.

## Install

```bash
pip install "synomega[gnn]>=0.

README.md

# SynOmega Skill

An agent **Skill** for [SynOmega](https://github.com/zbc0315/synomega) — the
retrosynthesis and reaction-prediction toolkit on PyPI
([docs](https://zbc0315.github.io/synomega/)). It teaches Claude Code, OpenClaw and
other coding agents to use the `synomega` Python package across its **six
capabilities**: single-step retrosynthesis (product → reactants), single-step
forward prediction (reactants → product), multi-step route planning, a continuous
**synthesizability score** (SynScore), reaction-plausibility screening, and
multi-component evolution (growing a forward synthesis network from a set of
reactants).

The skill runs synomega **locally** — `pip install synomega` plus a trained model
and a building-block file. It does not depend on any hosted service.

## Install

**OpenClaw / ClawHub**

```bash
clawhub install synomega
```

**Claude Code (manual)**

```bash
mkdir -p ~/.claude/skills/synomega
curl -fsSL https://raw.githubusercontent.com/zbc0315/synomega-skill/main/SKILL.md \
  -o ~/.claude/skills/synomega/SKILL.md
curl -fsSL https://raw.githubusercontent.com/zbc0315/synomega-skill/main/scripts/synomega_run.py \
  -o ~/.claude/skills/synomega/synomega_run.py
```

## Prerequisites

```bash
pip install "synomega[gnn]"        # the package (neural backend)
```

That's it — **it works out of the box**. The default pretrained model and
building-block stock download automatically on first use (into
`~/.cache/synomega`); run `synomega download` to pre-fetch them. Downloads come
from the nearest mirror (USTC GitLab in China, or GitHub), auto-selected by
latency. To use your own checkpoint/stock instead, set `SYNOMEGA_MODEL` /
`SYNOMEGA_STOCK`.

## Use

Ask your agent things like:

- "Can *paracetamol* be synthesized? How hard?"
- "Propose a synthesis route for `CC(=O)Nc1ccccc1O`."
- "What reactants could give this molecule in one step?"
- "What product do acetic acid and benzylamine give?"
- "Evolve a forward network from acetophenone + formaldehyde + dimethylamine."

Or call the bundled helper directly (one JSON-printing command per capability):

```bash
python scripts/synomega_run.py single-step  "CC(=O)Nc1ccccc1O" --top-k 10     # product -> reactants
python scripts/synomega_run.py forward      "CC(=O)O.NCc1ccccc1" --top-k 5    # reactants -> product
python scripts/synomega_run.py plan         "CC(=O)Nc1ccccc1O" --max-depth 5  # multi-step route
python scripts/synomega_run.py score        "CC(=O)Nc1ccccc1O" --max-steps 5  # synthesizability (SynScore)
python scripts/synomega_run.py evolve       "CC(=O)c1ccccc1.C=O.CNC" --max-depth 3 --score-threshold 0.01
```

`plan` and `score` take `--exclude-target` (treat the target as not purchasable
even if it is a catalogue molecule, so it is not trivially "solved" in zero steps).
Reaction-plausibility screening is an env toggle: `SYNOMEGA_PLAUSIBILITY=1`. See
`SKILL.md` for the full option list and output shapes.

## Contents

| File | Purpose |
|---|---|
| `SKILL.md` | the skill definiti

_meta.json

{
  "ownerId": "kn77a46vsrdfh54z4vx4x71gad83cwcw",
  "slug": "synomega",
  "version": "1.8.1",
  "publishedAt": 1788009062675
}

skill-card.md

## Description:

SynOmega Skill helps agents use the local synomega Python package for retrosynthesis, reaction prediction, multi-step synthesis planning, synthesizability scoring, plausibility screening, and multi-component reaction evolution for organic molecules.

This skill is ready for commercial/non-commercial use.

## Publisher:

[zbc0315](https://clawhub.ai/user/zbc0315)

### License/Terms of Use:

MIT

## Use Case:

Developers, chemists, and cheminformatics practitioners use this skill to ask an agent for synthesis planning, reaction outcome prediction, route scoring, and local command guidance around organic small molecules. It is intended for benign chemistry workflows and defers hazardous or controlled-compound decisions to the host safety policy.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Manual installation commands in the artifact can fetch executable code from mutable remote URLs without integrity checks.

Mitigation: Use the ClawHub install path; if installing manually, pin a reviewed commit and verify the provided file hashes before use.

Risk: The Python dependency and first-use model or stock downloads can affect privacy-sensitive, bandwidth-limited, air-gapped, or reproducibility-critical environments.

Mitigation: Run the dependency in a dedicated environment, pin requirements, and pre-fetch or mirror model assets before deployment.

Risk: Retrosynthesis and route-planning outputs can be dual-use for hazardous, controlled, or otherwise high-risk compounds.

Mitigation: Apply the host safety policy before giving operational synthesis guidance and require additional review for high-risk targets.

## Reference(s):

- [SynOmega documentation](https://zbc0315.github.io/synomega/)
- [SynOmega package on PyPI](https://pypi.org/project/synomega/)
- [Synomega Skill on ClawHub](https://clawhub.ai/zbc0315/skills/synomega)

## Skill Output:

**Output Type(s):** [text, markdown, code, shell commands, configuration, guidance]

**Output Format:** [Markdown guidance with shell command snippets and JSON-producing helper commands]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [The bundled helper script prints JSON for retrosynthesis, forward prediction, planning, scoring, and multi-component evolution operations.]

## Skill Version(s):

1.8.1 (source: ClawHub release evidence)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

LICENSE

MIT License

Copyright (c) 2026 zbc0315

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

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