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/learn-verify

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

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From plugin
alvarmethod
1635 skills
Install
$ npx -y skills add vasanthsreeram/alvarmethod --skill learn-verify --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/learn-verify

Context 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

SKILL.md

learn-verify.SKILL.md
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"

Learn verify

Trust is engineered. Check the claim before it is taught as fact.

When to run

  • Empirical, historical, bibliographic, or API/tool claims
  • Named theorems, identities, or "standard facts" you cannot reconstruct
  • Anything you were about to present with unearned certainty

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.

Method

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.

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.

Rules

  • No invented papers, quotes, or page numbers.
  • One claim per run. Batch only if they are the same fact in different words.
  • Write the verdict into the session file if a teach session is open.
Read more
Ships withalvarmethod

One-to-one AI teaching skills (Alvar method) for Codex, Claude Code, Grok, Pi, and OpenCode

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MIT
License
2mo ago
Last commit
2mo ago
Created
2d ago
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Repo: vasanthsreeram/alvarmethod

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