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assumptions

Extract a thesis's load-bearing assumptions and scan for internal contradictions — the falsifiable claims the bull case requires, what would falsify each, and where the thesis's own Risks / Bear Case / research already argue against it. Use when user says "assumptions", "what must be true", "load-bearing assumptions", or "does [TICKER] contradict itself".

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SKILL.md (original)

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Follow CLAUDE.md Writing Standards strictly. Lead with the assumption and what falsifies it, no hedge words, tables over prose.

Extract the load-bearing assumptions of one thesis — the falsifiable claims that must hold for the bull case to work — and flag where the thesis already contradicts itself. The output is the atom the vault-contradictions workflow fans out to find where one thesis's bull premise is another thesis's bear premise.

Arguments

$ARGUMENTS = a ticker or thesis name. If empty, ask which thesis.

Read-only

This skill REPORTS analysis; it does not modify vault files. To persist, the user asks explicitly.

Mental Models gate (MANDATORY — CLAUDE.md)

Read [[Mental Models/Generalist - Overview]] + matching Industry -/Lens - files. Apply the READING PROTOCOL: each assumption is a hypothesis to test, and agreement across the thesis's own sections is a trigger to disconfirm, not to trust — hunt the single falsifying datapoint.

Method (single source of truth — the vault-contradictions workflow reads this section)

  1. Read the thesis in full — Summary, Key Non-consensus Insights, Bull Case, Bear Case, Risks, Outstanding Questions, Conviction Triggers — plus its Related Research. Read _graph.md once for cluster peers.
  2. Enumerate the load-bearing assumptions: the specific, falsifiable claims the bull case requires (e.g. "HBM pricing holds through 2026", "CoWoS stays capacity-constrained", "Company X keeps design-win Y"). Each must be a claim that could be shown false, not a vibe.
  3. For each assumption record: what falsifies it (the concrete datapoint / event), whether it is stated or implicit, and its criticality (thesis breaks / weakens / cosmetic).
  4. Internal-contradiction scan: for each assumption, check whether the thesis's OWN ## Bear Case / ## Risks / ## Outstanding Questions or a linked research note already argues against it. A high-conviction thesis whose bull assumption is contradicted by its own risk section is the strongest single-name red flag.
  5. Portability tag (for the workflow): mark assumptions that are really claims about the industry (not just this company) — e.g. "memory oversupply arrives in 2H26" — since those are the ones that can clash with another thesis that assumes the opposite.

Output (solo run)

An assumptions ledger — columns: Assumption | Falsifier | Stated? | Criticality | Internally contradicted? (where) — then a one-line verdict on whether stated conviction is supported by the surviving assumptions. No filler.

Workflow reuse

vault-contradictions (.claude/workflows/vault-contradictions.js) fans this ## Method out across every thesis, then finds cross-thesis clashes (thesis A's bull assumption = thesis B's bear assumption) and adversarially verifies each is a real contradiction, not a framing difference. Keep ## Method the single source of truth.

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