← LeaderboardThe Skill Leaderboard

thinking-via-negativa

Use when the reflex is to add a feature, layer, or process. Prefer removing harmful or nonessential elements first, with an irreversibility guard before deletion.

Published by tjboudreaux ↗tjboudreaux/cc-thinking-skills

Try your first task

thinking-via-negativa

Start a fresh conversation. Replace the highlighted placeholders.

Use thinking-via-negativa to Assess [desired outcome] by identifying evidence-backed, reversible removal candidates before proposing the minimum necessary addition; preserve load-bearing controls and provide an action and verification plan.

Required inputs

  • [desired outcome]

User-approved starter prompt based on a pinned source version; check current skill requirements before running. Task evidence ↗

SKILL.md

name: thinking-via-negativadescription: Use when the reflex is to add a feature, layer, or process. Prefer removing harmful or nonessential elements first, with an irreversibility guard before deletion.disable-model-invocation: true

Via Negativa

Improve by subtraction before addition. Prefer removing harm, waste, and nonessential complexity; add only when a demonstrated need remains after removal candidates are exhausted.

When to Use

  • About to add a feature, abstraction, dependency, process, or control to fix a problem.
  • Simplifying a system or workflow where complexity is the tax.
  • Prioritizing by deciding what not to keep, build, or maintain.
  • Performance or reliability work where eliminating a bad path beats bolting on mitigation.

When NOT to Use

  • Load-bearing controls: auth, validation, tests, rate limits, retries, safety checks — presume necessary until proven dead.
  • A demonstrated requirement that cannot be met by removal or simplification.
  • Aesthetic minimalism without evidence of non-use or net harm.
  • Irreversible deletion without a rollback path when impact is unknown.

Procedure

  1. Pause the add reflex. State the goal and the proposed addition in one line.
  2. Ask the subtraction question first. List what could be removed or stopped to achieve the same goal with less surface area.
  3. Catalog candidates with evidence. Prefer unused, redundant, high-cost/low-value, or harmful elements. Require usage, call-graph, metrics, or experiment evidence — not taste.
  4. Apply the irreversibility guard. Classify reversible vs hard-to-restore; identify dependents; refuse deleting unproven mystery guards. Plan staged removal or flag when risk is non-trivial.
  5. Remove the safest high-value candidate first. Subtract, monitor, and verify absence of needed behavior before the next removal.
  6. Add only if the goal still fails. If subtraction cannot meet the need, add the minimum change and record why removal was insufficient.
  7. Stop when the goal is met by absence, or remaining candidates fail the irreversibility/evidence bar and a minimal addition is justified.

Stop condition: Goal achieved via removal, or residual need documented after evidence-backed subtraction failed.

Output

Goal: <desired outcome>
Proposed add (if any): <thing>
Removal candidates: <element — evidence — risk — reversible?>
Action: remove <X> | staged remove <X> | add minimal <Y> because <why removal failed>
Verification plan: <how absence/success is checked>
Do-not-touch: <load-bearing items preserved>

Verification

  • Falsify if something was deleted without non-use/harm evidence, or a safety control was removed as "complexity."
  • Falsify if an addition shipped without a prior subtraction pass on the same goal.
  • Over-application guard: do not delete for line-count or purity when the element is load-bearing or the need is demonstrated.