How do I install the Openclaw Success Skill Publisher skill?

Run npx skillmds@latest add lord1egypt/openclaw-success-skill-publisher in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Openclaw Success Skill Publisher safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: makes network calls, reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Openclaw Success Skill Publisher?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Openclaw Success Skill Publisher free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Openclaw Success Skill Publisher?

Lord1Egypt (@lord1egypt) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Openclaw Success Skill Publisher by lord1egypt

Name: Openclaw Success Skill Publisher
Rating: 4.666666666666667 (3 reviews)
Author: Lord1Egypt

Openclaw Success Skill Publisher

Capture successful OpenClaw interactions and convert them into reusable skills with an optimized execution path summary, then publish to ClawHub and distribute bilingual sharing posts to Moltbook, Zhihu, Xiaohongshu, or other configured channels. Use when the user asks to productize a completed OpenClaw workflow into a reusable skill and push it to distribution platforms.

Lord1Egypt Updated Sep 8, 2026 2 repo stars

File contents

OpenClaw Success Skill Publisher

Convert a successful user-agent interaction into a production-ready skill and distribute it.

Security And Runtime

Require explicit user approval before any real external publish.
Treat missing publish credentials as draft-only mode.
Never leak secrets in generated summaries.
Use local output directory as source of truth for every publish payload.

Required Inputs

A success record JSON containing:
- title
- user_goal
- steps[]
- outcome.completed
Optional:
- deliverables[]
- context
- outcome.metrics
- language

Environment Variables

CLAWHUB_API_BASE (example: https://api.clawhub.ai)
CLAWHUB_API_TOKEN
MOLTBOOK_WEBHOOK_URL
ZHIHU_WEBHOOK_URL
XIAOHONGSHU_WEBHOOK_URL

In --dry-run, unset publish/share targets are skipped and local drafts are still generated. In real publish mode (without --dry-run), missing required env for a selected target should fail fast.

Workflow

Build distilled knowledge from a success case.

python3 scripts/pipeline.py \
  --input examples/success_case.json \
  --output outputs/run-001 \
  --dry-run

Review generated artifacts:

summary.md: what happened and why it worked
optimal_path.md: shortest high-confidence implementation path
generated_skill/SKILL.md: reusable skill definition
generated_skill/agents/openai.yaml: skill card metadata
share_payloads/*.md: platform-tailored bilingual posts

Publish after explicit approval.

python3 scripts/pipeline.py \
  --input examples/success_case.json \
  --output outputs/run-001 \
  --publish-clawhub \
  --share moltbook zhihu xiaohongshu

Rules

If outcome.completed is false, stop and request more evidence.
Prefer deterministic step extraction over freeform storytelling.
Rank step importance by observed success signal + dependency position + efficiency.
Generate both Chinese and English sharing copy.
In --dry-run, if publish/share endpoint is missing, persist payloads locally and continue.
In real publish mode, require env for selected targets and fail fast when missing.
Preserve reproducibility with placeholder env names and command templates only. Never embed real secret values in generated artifacts.

Output Contract

Always produce:

summary.md
optimal_path.md
generated_skill/
share_payloads/
publish_report.json

---name: openclaw-success-skill-publisherdescription: Capture successful OpenClaw interactions and convert them into reusable skills with an optimized execution path summary, then publish to ClawHub and distribute bilingual sharing posts to Moltbook, Zhihu, Xiaohongshu, or other configured channels. Use when the user asks to productize a completed OpenClaw workflow into a reusable skill and push it to distribution platforms.---# OpenClaw Success Skill PublisherConvert a successful user-agent interaction into a production-ready skill and distribute it.## Security And Runtime- Require explicit user approval before any real external publish.- Treat missing publish credentials as `draft-only` mode.- Never leak secrets in generated summaries.- Use local output directory as source of truth for every publish payload.## Required Inputs- A success record JSON containing: - `title` - `user_goal` - `steps[]` - `outcome.completed`- Optional: - `deliverables[]` - `context` - `outcome.metrics` - `language`## Environment Variables- `CLAWHUB_API_BASE` (example: `https://api.clawhub.ai`)- `CLAWHUB_API_TOKEN`- `MOLTBOOK_WEBHOOK_URL`- `ZHIHU_WEBHOOK_URL`- `XIAOHONGSHU_WEBHOOK_URL`In `--dry-run`, unset publish/share targets are skipped and local drafts are still generated.In real publish mode (without `--dry-run`), missing required env for a selected target should fail fast.## Workflow1. Build distilled knowledge from a success case.```bashpython3 scripts/pipeline.py \ --input examples/success_case.json \ --output outputs/run-001 \ --dry-run```2. Review generated artifacts:- `summary.md`: what happened and why it worked- `optimal_path.md`: shortest high-confidence implementation path- `generated_skill/SKILL.md`: reusable skill definition- `generated_skill/agents/openai.yaml`: skill card metadata- `share_payloads/*.md`: platform-tailored bilingual posts3. Publish after explicit approval.```bashpython3 scripts/pipeline.py \ --input examples/success_case.json \ --output outputs/run-001 \ --publish-clawhub \ --share moltbook zhihu xiaohongshu```## Rules- If `outcome.completed` is false, stop and request more evidence.- Prefer deterministic step extraction over freeform storytelling.- Rank step importance by observed success signal + dependency position + efficiency.- Generate both Chinese and English sharing copy.- In `--dry-run`, if publish/share endpoint is missing, persist payloads locally and continue.- In real publish mode, require env for selected targets and fail fast when missing.- Preserve reproducibility with placeholder env names and command templates only. Never embed real secret values in generated artifacts.## Output ContractAlways produce:- `summary.md`- `optimal_path.md`- `generated_skill/`- `share_payloads/`- `publish_report.json`

Frequently asked questions