hashintel/labs/assumptions

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Create and maintain an Assumption Ledger — a persistent record of assumptions, their confidence, and validation status. Use when starting a new slice, resuming work in a new context window, or when implicit assumptions risk causing drift. Tracks requirements, architecture, and implementation assumptions.

Install

npx vskill@latest install hashintel/labs/assumptions

SKILL.md

Assumption Ledger

Maintain a project-wide Assumption Ledger — durable memory of what was assumed, how sure we were, and how it was proved or disproved. Supports fresh context per slice without losing epistemic continuity.

Input

Mode + context: $ARGUMENTS

Modes:

  • create — initialize a new ledger
  • update — add/update assumptions from a card, spike verdict, or slice result
  • review — summarize current ledger and recommend what to validate next

Ledger location

Default: docs/assumptions.md. If it exists, update — don't duplicate.

Ledger schema

Each entry MUST include:

  • ID: A-### (stable identifier)
  • Statement: one sentence, falsifiable if possible
  • Type: Requirement | Architecture | Implementation
  • Confidence: 0-100%
  • Status: Proposed | Validated | Invalidated | Obsolete
  • Introduced by: (card / spike / slice / commit)
  • Validated by: (test name, command, spike evidence) — required for Validated/Invalidated
  • Last reviewed: YYYY-MM-DD

Graduation Protocol

Assumptions track uncertainty and confidence. They are not permanent authority. When assumptions stabilize, promote them to their canonical home:

  • Capsule promotion: durable semantic law or glossary boundary →

docs/capsule.md or docs/capsule-<feature>.md

  • Roadmap/decision promotion: strategic initiative choice with

reversibility/rationale → docs/roadmap.md (and/or decisions log)

  • Milestone promotion: temporary phase sequencing or deferment →

docs/milestone.md

  • Contract promotion: enforceable invariant now ready for code-level checks

→ /pragma:contract + tests

When promoted, keep the assumption entry for history and add a "Promoted to" reference with path/anchor.

Procedure

Mode: create

Create docs/assumptions.md with sections: Active (Proposed), Validated, Invalidated/Obsolete, Open Questions. Seed with 3-10 initial assumptions if obvious from capsule/card.

Mode: update
  1. Extract assumptions from context ("ASSUMPTION:" lines in cards, spike verdicts, slice summaries)
  2. Match against existing entries → update confidence/status/evidence. New → assign ID, add under Active.
  3. Confidence < 70% → mark High Risk, recommend clarification or /pragma:spike
  4. Disproved by spike/test → move to Invalidated, note "Replaced by A-###" if superseded
  5. For any stabilized assumption, apply the graduation protocol and add

cross-reference links to the promoted artifact

Mode: review
  1. List Active (Proposed) sorted by: lowest confidence first, highest impact first
  2. Recommend: /pragma:spike for unknowns, /pragma:card+/pragma:slice for E2E-validatable assumptions, /pragma:characterize for behavior already in code
  3. Identify stale assumptions (not reviewed recently, weak evidence)
  4. Identify promotable assumptions and their target authority document

Constraints

  • No vague assumptions. "Should be scalable" → rewrite as falsifiable statement.
  • Validated/Invalidated requires evidence. Cite test, command output, or spike verdict.
  • Do not delete history. Invalidated assumptions stay recorded.
  • Assumptions are not features. The ledger records knowledge state, not work.
  • Do not treat assumptions as semantic authority. Durable definitions and

laws must be promoted to capsule.

Output

  1. The updated docs/assumptions.md diff summary
  2. The top 3 highest-risk active assumptions
  3. Promotion summary (assumptions promoted, with destination artifacts)
  4. The recommended next step (often /pragma:spike or /pragma:card)
  5. Lifecycle: State: governance, Next: /pragma:consult (or the explicitly recommended next step), Loop: /pragma:consult (default unless user explicitly continues directly)

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
35
Repository forks
14
7-day trend score
18

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 23 May 2026, 5 months ago.

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