agentleFS
baney75baney75/myelinate/skills/verify/SKILL.md

verify

Skill4 starsChanged 2 days agoMITView on GitHub

Use when someone asks to check a lesson, answer key, or learning material for accuracy, currency, and alignment. Not software code review or tests.

We split this skill into the rules it gives an agent

8 rules. 0 are common, 7 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 168 edited versions we read keep these.

  • 7

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Ask "could this have changed?" for each consequential claim.

    line 26
  2. Distinctive:

    Prefer the newest *authoritative* source (current guideline, current edition, current docs), not the newest blog.

    line 27
  3. Distinctive:

    Recompute: every calculation, unit, sign, significant figure, model output (run code).

    line 35
  4. Distinctive:

    Alignment: every in-scope objective covered.

    line 38
  5. Distinctive:

    Use an independent reviewer, a fresh subagent with no stake in the draft (or a second model when available).

    line 43
  6. Distinctive:

    Re-review: after substantive fixes (only changed parts).

    line 49
  7. Distinctive:

    Don't duplicate effort: one reviewer per artifact per round.

    line 51
  8. Very specific:

    Use templates/verification-report.md.

    line 55

“Common” is measured: kept by at least 6 in 10 of the 168 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Verify

Teaching something wrong is worse than not teaching it: a confidently learned error is hard to remove and costs points on the exam or worse in a clinic. This skill is a deliberate attempt to break the material before the learner does. A check that could not have failed is not verification.

Paths like references/…, templates/… and examples/… are relative to this skill's folder, which carries its own copy of every file it names. Other Myelinate skills are siblings (../tutor/SKILL.md) and are installed as their own skills too. If a file is missing from your copy, fetch it from https://raw.githubusercontent.com/baney75/myelinate/main/ plus its path in the repository (references/…, skills/<name>/SKILL.md); if you can't fetch, work from this file and the router's core rules.

1. When to run it

Always, before delivery:

  • Labs, study packs, answer keys, practice exams, flashcard decks over ~20 cards
  • Anything graded, clinical/medical, legal, financial, safety-related
  • Time-sensitive content: guidelines, drug info, reference ranges, technology versions, laws, statistics, "current" anything, recent discoveries, taxonomy and nomenclature revisions, exam formats (MCAT/USMLE changes)
  • Numeric models and simulations
  • Claims where the course and the field may disagree

Light version (self-check, §3 steps 1 to 4) for ordinary chat explanations of stable material. Full adversarial review (§4) for the list above.

2. Time awareness

Know today's date and treat it as a variable:

  • Ask "could this have changed?" for each consequential claim. If yes, search for the current version and record the date/version checked.
  • Prefer the newest authoritative source (current guideline, current edition, current docs), not the newest blog. Recent ≠ reliable; old foundational work is fine for stable facts.
  • Flag claims in the learner's materials that are outdated (e.g., reclassified taxonomy, revised guidelines). Teach the course version for the exam and the current version, labeled.
  • Exam proximity raises the bar: the closer the exam, the more any error costs. With little time left, verify the highest-weight items first.

3. The verification pass

  1. Claim inventory: list every consequential claim, number, definition, mechanism step, answer and distractor-key.
  2. Source each: course material (slide/page) for scope and convention; authoritative reference for fact. Read the actual source, not a snippet. Mark: supported / course-only / unsupported / contradicted.
  3. Recompute: every calculation, unit, sign, significant figure, model output (run code). Re-derive every answer key independently before looking at the stated answer.
  4. Match strength: "associated with" stays associated; "can" doesn't become "always"; one example isn't a rule.
  5. Item audit: each question has exactly one defensible answer; distractors are wrong for a named reason; stem isn't ambiguous; no answer leaks (stem cues, longest-option bias, grammatical cues, alt text, filenames).
  6. Alignment: every in-scope objective covered; nothing out of scope presented as tested.
  7. Media: labels correct, licenses recorded, masked labels fully masked.

4. Adversarial review (the important part)

Use an independent reviewer, a fresh subagent with no stake in the draft (or a second model when available). Give it the material, the sources, the course scope and today's date, and instruct it to find errors, not to approve:

You are an adversarial reviewer for teaching material for [audience/course], exam on [date]. Today is [date]. Find every factual error, outdated claim, miscalculation, ambiguous or double-keyed question, misleading simplification, scope violation, and answer leak. For each finding give: location, the problem, evidence (source + quote or calculation), severity (blocks-learning / misleading / minor), and the fix. Check time-sensitive claims against current authoritative sources. Do not praise. If you find nothing in a section, say what you checked.

Then:

  • Triage each finding yourself against the source; reviewers can be wrong too. Confirmed → fix. Disputed → resolve with a primary source or present both views to the learner, labeled.
  • Re-review after substantive fixes (only changed parts).
  • For very high stakes (clinical content, final-exam answer keys, published labs), run two independent reviewers and compare.
  • Don't duplicate effort: one reviewer per artifact per round; don't rerun unchanged checks.

5. Report

Use templates/verification-report.md. State: date, what was checked and how, findings and fixes, what remains unverified, and what's approximate. Use precise words: drafted, self-checked, adversarially reviewed, tested (ran it), deployed (live), confirmed live. Never "verified" alone without saying by what.

Anti-patterns

Reviewing your own draft and calling it adversarial · approving because sources "look reputable" · checking only that code runs · trusting a reviewer's finding without checking it · searching once and declaring "current" · silently teaching the course's outdated claim · burying uncertainty.

Download now (ZIP)

  • Other versions188 projects use a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 188

    1. react/react★ 252ksame name
    2. facebook/react★ 252ksame name
    3. garrytan/gstack★ 139ksame name
    4. oven-sh/bun★ 96ksame name
    5. anthropics/financial-services★ 41ksame name
    6. anthropics/financial-services-plugins★ 41ksame name
    7. Yeachan-Heo/oh-my-claude-sisyphus★ 40ksame name
    8. Yeachan-Heo/oh-my-claudecode★ 40ksame name
    9. anthropics/claude-quickstarts★ 19ksame name
    10. NVIDIA-NeMo/Speech★ 19ksame name

    178 more not listed

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

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  • In this repository19 other files it gives its agents.

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