learn-profile
Interview the learner and write .alvar/LEARNER.md so one teacher can fit one mind — pace, voice, solid ground, and how they want…
Fact-check a teaching claim against sources so the learner can trust the single interface. Use when the user runs /learn-verify or /skill:learn-verify, or says fact-check, verify this, is this true, source this, don't hallucinate, or when a teach/plan step needs a claim checked
$ npx -y skills add vasanthsreeram/alvarmethod --skill learn-verify --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/learn-verifyContext preview
The summary Claude sees to decide when to auto-load this skill.
Fact-check a teaching claim against sources so the learner can trust the single interface. Use when the user runs /learn-verify or /skill:learn-verify, or says fact-check, verify this, is this true, source this, don't hallucinate, or when a teach/plan step needs a claim checked
name: learn-verify description: > Fact-check a teaching claim against sources so the learner can trust the single interface. Use when the user runs /learn-verify or /skill:learn-verify, or says fact-check, verify this, is this true, source this, don't hallucinate, or when a teach/plan step needs a claim checked before it is taught as fact. license: MIT metadata: author: vasanthsreeram version: "1.0" source: "Eero Alvar — How I Use AI to Learn Things https://youtu.be/kzcI5F4tGiU"
Trust is engineered. Check the claim before it is taught as fact.
Skip a full search only when you can derive the statement in-session and the learner does not need an external citation. Still say that it was derived, not sourced.
1. Write the claim in one falsifiable sentence. 2. Fetch or search primary-ish sources (paper, textbook, official docs, standard reference). Do not cite a URL you did not open. 3. Quote or paraphrase the supporting line. Note edition / year if it matters. 4. Mark disagreements. Prefer the source the field actually uses. 5. Return a verdict.
## Claim … ## Verdict confirmed | qualified | contradicted | unknown ## Sources - <title> — <url or citation> — <what it says> ## Teach as <one sentence the teacher may now say, with any hedge>
`qualified` = true under stated assumptions (dimension, characteristic, gauge, version).
`unknown` = do not teach it as fact. Say you could not verify.
One-to-one AI teaching skills (Alvar method) for Codex, Claude Code, Grok, Pi, and OpenCode
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