Mechanism Research Skill
Investigates how a phenomenon arises, tests causal claims online, and reports the best-supported mechanism with its limits.
- Repository
- lijigang/ljg-skills
- Stars
- 7,607
- Licence
- MIT
- Files
- 3 files
What it does
When installed, the agent approaches a puzzling phenomenon by first checking whether the observation is accurate, then tracing the step-by-step process that could produce it, and comparing rival explanations. It is instructed to search the web and read sources to test these explanations, then deliver its current best mechanism judgement, how strong the evidence is, what new evidence would change its mind, and the conditions under which the explanation applies. It is a structured reasoning method rather than a data tool; the files describe it as read-only by default and say it should not create notes, reports or memory files unless asked.
Great for
- People trying to understand why something happens, such as why AI productivity gains do not show up in income
- Researchers or students who want a checklist for testing a causal explanation against sources
- Anyone checking a viral claim that a technique 'does not work' by clarifying the metric, period and group involved
Skip it if
- Simple definitions or plain summaries, which the skill itself says it should not handle (the cost is unnecessary effort, not harm)
- Questions with one clear answer, where the structured four-step framework adds nothing
- Situations needing guaranteed factual accuracy: the output is a reasoned judgement based on web searches that may be incomplete or wrong, so claims should be checked against the cited sources before being relied on
Try asking
- “/ljg-mechanism Why did AI make content creation easier but not increase creators' income?”
- “找机制：为什么远程团队的会议越来越多但决策没有变快？”
- “Walk me through the mechanism framework on why open-source projects still get answers without a central coordinator.”
- “联网验证这个解释：网上说某种学习方法没有效果，请核对指标和适用人群。”
Install in 3 steps
- 1
Download the skill
The ZIP contains the 3 original files, the MIT licence and an attribution note.
ljg-mechanism.zip - 2
Add it to your agent
Claude Code (all projects)
mkdir -p ~/.claude/skills && unzip ljg-mechanism.zip -d ~/.claude/skills/Claude Code / Agent SDK (this project only)
mkdir -p .claude/skills && unzip ljg-mechanism.zip -d .claude/skills/Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.
- 3
Ask for the task
No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.
Get better results
- State the phenomenon precisely, including the time period, group and metric you care about, so the skill can check the observation first.
- Ask for a full walkthrough if you want to see the four stages (anomaly, process, rival explanations, conditional transfer) spelled out.
- Verify the links it provides next to key causal claims, since the skill itself separates what a source shows from the agent's inference.
What's inside
- agents/openai.yaml
- SKILL.md
- Workflows/DiscoverMechanism.md
Redistributed unmodified from lijigang/ljg-skills under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.