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Agent skill

Weiping Lab

by appleweiping in appleweiping/WEIPING_LAB

Plan, design, develop, test, release, maintain, monitor, and iterate Weiping Lab honestly.

MITAuto-check: notes

Install Weiping Lab

skills CLI
$ npx skills add appleweiping/WEIPING_LAB --skill weiping-lab -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install appleweiping/WEIPING_LAB weiping-lab --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/appleweiping/WEIPING_LAB.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.codex/skills/weiping-lab .claude/skills/weiping-lab && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
weiping-lab
GitHub stars
119
Token cost
~1.2k tokens
SKILL.md length
563 words
Files
1
Skills in repo
1
Repo updated
First seen
Licence
MIT

At a glance

Plan, design, develop, test, release, maintain, monitor, and iterate Weiping Lab honestly.

  • Works in 8 steps: Plan → Design → Develop → …
  • SKILL.md covers 1. Plan, 2. Design, 3. Develop and 4. Test, plus 4 more sections
  • Calls python, npm and git; reaches registry.npmjs.org

What it does

Weiping Lab is an agent skill from appleweiping/WEIPING_LAB. Plan, design, develop, test, release, maintain, monitor, and iterate Weiping Lab honestly.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Autonomous research system: phenomenon-driven discovery, kill-first ideation, anti-toy enforcement, evidence-gated pipeline. The licence is MIT.

Example prompts

  • “/weiping-lab”

Requirements

  • Python 3

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Plan
  2. Design
  3. Develop
  4. Test
  5. Release
  6. Maintain
  7. Monitor
  8. Upgrade Iterate

What it can do on your machine

Read from SKILL.md and the folder at commit e26588e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python
    • npm
    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • registry.npmjs.org

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Weiping Lab loads about 1.2k tokens when it runs. Until then it costs about 26 tokens; SKILL.md has 563 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~26
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:25
    rtifact formats are acceptable; private `.env` files, local DBs, caches, generated reports, and active services are not.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from appleweiping/WEIPING_LAB at commit e26588e, republished under its MIT licence (© appleweiping). 563 words, ~1,199 tokens.

Download SKILL.mdSave it as .claude/skills/weiping-lab/SKILL.md (or your agent's skills folder).
name
weiping-lab
description
Plan, design, develop, test, release, maintain, monitor, and iterate Weiping Lab honestly.

Weiping Lab Project Skill

Use this skill for any non-trivial change to Weiping Lab. The goal is an honest research workbench: public-safe config, explicit evidence gates, reproducible workspace state, and no hidden dependency on retired collaboration systems.

1. Plan

  • Read AGENTS.md, README.md, CLAUDE.md, pyproject.toml, lab/core/config.py, and lab/runtime.py.
  • Run git status --short --branch and do not disturb unrelated user changes.
  • Define one version-sized outcome. Avoid tiny isolated tweaks unless the user explicitly asks for one.
  • Identify any relation to WEIPING_WIKI, WEIPING_COUNCIL, AGENT_RESOURCE, AGENTIC_SCIENCE, or deepseek-cli; use current files as evidence, not memory alone. Treat historical vipin-* references as compatibility aliases only.

2. Design

  • Keep runtime configuration env-driven. Never add tracked private keys, endpoints, account names, or secret-shaped placeholders.
  • Keep active memory routed through agentmemory. Local fallback may be an outbox under the configured workspace only; do not restore retired Agent Hub mailboxes or old markdown session dumps.
  • Preserve the research gate sequence: phenomenon, kill-first, refine, experiment plan, bridge, results, paper write, review, citation audit, claim audit.
  • Preserve docs/RESULT_CONTRACT.md: result files are untrusted, evidence labels are computed locally, and empirical claims require persisted links to paper_result block IDs.
  • Make every new check observable through CLI, API, tests, or release scan.
  • Keep cross-project links low-coupling: route maps, optional context variables, validation commands, and artifact formats are acceptable; private .env files, local DBs, caches, generated reports, and active services are not.

3. Develop

  • Prefer scoped edits in lab/, api/, cli/, ui/, tests/, scripts/, and docs.
  • Use apply_patch for manual edits.
  • If lab/workspace/ source files are touched, verify they are not gitignored.
  • Redact provider errors and persisted diagnostics before writing logs or outbox records.
  • Use atomic replacement for durable JSON checkpoints. Never treat a partial result set, a producer-supplied label, or a partial model rubric as a passing gate.
  • Bind READY state to the exact plan, paper, and result artifact hashes; any later mutation must downgrade the checkpoint and force deterministic evidence validation again.

4. Test

Run the strongest practical local gate:

bash
python -m pytest -q
python -m pip check
python -m pip_audit
python scripts/release_scan.py
npm --prefix ui run lint
npm --prefix ui run build
npm --prefix ui audit --audit-level=low --registry=https://registry.npmjs.org

When dependencies are missing, install only the narrow needed dev dependency into a D-drive project-local environment or clearly report the blocker.

Show full SKILL.md (215 more words)Show less

5. Release

  • Bump lab/runtime.py and pyproject.toml together.
  • Update README.md, CLAUDE.md, .env.example, and the release scan when behavior changes.
  • Ensure python scripts/release_scan.py rejects stale versions, retired infrastructure, mirror registries, private endpoints, and secret-like placeholders.
  • Commit and push only after tests and reviewer gates pass.

6. Maintain

  • Keep README.md honest about implemented behavior.
  • Keep CLAUDE.md as an operational adapter, not a competing policy document.
  • Keep AGENTS.md as the top-level operating adapter for this repo and align it with README, CLAUDE, and this skill.
  • Maintain the handoff contract for workspace/*/session.json, workspace/ideas/<idea_id>/idea.json, plan.json, paper.json, EXPERIMENT_PLAN.md, EXPERIMENT_TRACKER.md, experiments/results/*.json, and redacted agentmemory-outbox.jsonl.
  • Keep the repository result contract and bridge-generated result template synchronized with the loader and its regression tests.
  • Remove compatibility shims only when callers are updated; otherwise make shims explicit no-ops.

7. Monitor

  • vlab status --json and GET /api/status are the public runtime probes.
  • Monitor workspace count, model key source, agentmemory endpoint host, and disabled legacy fallbacks.
  • Do not expose raw API keys, bearer tokens, full provider URLs containing credentials, or private filesystem paths beyond configured workspace diagnostics.

8. Upgrade Iterate

  • Study concrete source files from active open-source research-agent projects before major architecture claims.
  • Use reviewer partners after the implementation batch is complete. Require PASS_10 before release.
  • Feed reviewer findings back into code, docs, and tests, then rerun the gates.

© appleweiping, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .codex/skills/weiping-lab of appleweiping/WEIPING_LAB.

Open the folder on GitHubat commit e26588e

Compare with similar skills

Weiping Lab next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Weiping Lab compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Weiping Lab this skillappleweiping/WEIPING_LAB119—~1.2kAutomated safety check: NotesMIT
MCP Developmentcoollabsio/coolify63k1 repos~949Automated safety check: PassMIT
Wiki Maintaineropenclaw/openclaw392k1 repos~462Automated safety check: PassMIT
Game Developmentsickn33/agentic-awesome-skills47k1 repos~1.3kAutomated safety check: PassMIT
Twenty App Entity Developmenttwentyhq/twenty58k—~1.8kAutomated safety check: PassCustom licence
Developmentccusage/ccusage19k—~433Automated safety check: PassCustom licence

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Questions about Weiping Lab

What does Weiping Lab do?

Plan, design, develop, test, release, maintain, monitor, and iterate Weiping Lab honestly. Weiping Lab is an agent skill from appleweiping/WEIPING_LAB. Plan, design, develop, test, release, maintain, monitor, and iterate Weiping Lab honestly.

How do I install Weiping Lab in Claude Code?

Run `npx skills add appleweiping/WEIPING_LAB --skill weiping-lab -a claude-code`. Or copy the skill folder (.codex/skills/weiping-lab in appleweiping/WEIPING_LAB) into .claude/skills/weiping-lab in your project. Claude Code loads it when a task matches its description.

How do I install Weiping Lab in Codex?

Run `npx skills add appleweiping/WEIPING_LAB --skill weiping-lab -a codex`. Or copy the skill folder (.codex/skills/weiping-lab in appleweiping/WEIPING_LAB) into .agents/skills/weiping-lab in your project. Codex loads it when a task matches its description.

Can I use Weiping Lab in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add appleweiping/WEIPING_LAB --skill weiping-lab -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/weiping-lab, .gemini/skills/weiping-lab, .github/skills/weiping-lab and .opencode/skills/weiping-lab in your project.

What does Weiping Lab need to run?

Going by SKILL.md and its folder, Weiping Lab needs the command-line tools its instructions call (python, npm and git). Our summary lists: Python 3.

Does Weiping Lab access the network?

SKILL.md names 1 domain. In commands or code: registry.npmjs.org; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Weiping Lab safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Weiping Lab use?

Weiping Lab is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Weiping Lab use?

About 1.2k tokens (SKILL.md is roughly 4.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Weiping Lab?

Skills that share tags, products or a category with Weiping Lab: MCP Development (coollabsio/coolify, 63k stars), Wiki Maintainer (openclaw/openclaw, 392k stars), Game Development (sickn33/agentic-awesome-skills, 47k stars) and Twenty App Entity Development (twentyhq/twenty, 58k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Weiping Lab?

appleweiping (a GitHub user) maintains it in appleweiping/WEIPING_LAB, which has 119 GitHub stars. The repository was last updated on August 28, 2026.

Source: appleweiping/WEIPING_LAB on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.