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Decision Option Review

When several real options compete, intuition compares them on shifting, unstated criteria that nobody can inspect. This skill makes the comparison explicit: list the options, define and weight the criteria that actually matter, score each option, surface the tradeoffs, and recommend. The output is a criteria-weighted option matrix. It is a lightweight multi-criteria review, not academic MCDA, and it deliberately shows the tradeoffs rather than hiding behind a single total: weighted scores can manufacture false precision, so soft scores are flagged and the recommendation states what would flip it.

  • Choosing among several real, distinct options.
  • Objectives conflict and the tradeoffs are currently implicit.
  • The decision needs to be explained or defended to others.
  • Trivial or obvious choices, or one-way doors needing deeper analysis than a matrix.
  • To generate options (use an ideation skill); this compares options that already exist.
  • When the criteria genuinely cannot be articulated.
  • As a way to make a single weighted total settle a close call (false precision).

When asked to review options, follow these steps:

  1. List the options being compared (the real, distinct ones).
  2. Define the criteria that actually matter for this decision, and weight them (high / medium / low is enough). State why each criterion is in.
  3. Score each option against each criterion. Use a small scale and say what a high score means. Flag any score you are not confident in.
  4. Surface the tradeoffs. For each leading option, state plainly what it gives up. Note factors that resist scoring rather than dropping them.
  5. Recommend one option, with a confidence note and the conditions under which the recommendation would flip.
  6. Emit the matrix per references/TEMPLATE.md.

Use the template in references/TEMPLATE.md. The deliverable is the matrix plus the tradeoffs and a recommendation, not prose and not a bare total.

Before finalizing, verify:

  • Criteria and weights are explicit, with a reason each is included.
  • Soft or low-confidence scores are flagged, not presented as exact.
  • The tradeoffs each leading option makes are stated.
  • Factors that resist quantification are noted, not dropped.
  • The recommendation states what would flip it.
  • The output is the matrix artifact, not a single total treated as the answer.

Tier P (flagged). Structured multi-criteria comparison is a long-standing, government-endorsed decision aid (UK Government MCDA guidance), which stresses it should support judgment, not replace it. Making criteria and weights explicit improves transparency, but a weighted total does not produce a correct decision, and over-trusting the arithmetic (false precision) is a known failure. Evidence is transferred from human practice, not AI-validated. Full grading: evidence/dossier.md.

See references/EXAMPLE.md for a completed option matrix.

A full worked run (the shared Northwind scenario)

Criteria-Weighted Option Matrix - Worked Example

Section titled “Criteria-Weighted Option Matrix - Worked Example”

A completed run of think-decision-option-review, on the shared Northwind scenario. This is the quality bar a generated matrix should meet.

Northwind is a B2B SaaS. After reframing the goal to “generate qualified pipeline with the least irreversible commitment” and expanding options with SCAMPER, this skill compares the shortlisted growth options.


  • Which growth approach to commit to for the Q3 target.
  • A: Build a self-serve free tier.
  • B: Fix the paid-trial funnel (onboarding + conversion).
  • C: Outbound plus free pilots for qualified prospects.
Criterion (weight, why)A: Free tierB: Fix funnelC: Outbound + pilots
Likely impact on qualified pipeline by Q3 (H - it is the goal)3 - high if conversion holds (unproven)3 - directly lifts existing demand4 - targets qualified accounts
Reversibility (H - avoid one-way doors)1 - hard to unwind publicly5 - fully reversible4 - low commitment
Cost / unit-economics risk (H)2 - infra + support + cannibalization5 - low3 - sales time
Time to first signal (M)2 - weeks to build5 - days4 - days
Strategic upside if it works (M)5 - durable self-serve motion2 - incremental3 - repeatable but sales-heavy

Score scale 1-5; 5 = best on that criterion. Flagged soft scores: A’s impact (3) is unproven (depends on unmeasured ICP conversion); all of A’s scores carry that uncertainty.

  • Option A gives up reversibility and cost-safety for a large but unproven upside.
  • Option B gives up strategic upside for speed, safety, and reversibility.
  • Option C balances both but consumes sales capacity.
  • Board optics: a visible “free tier” launch may satisfy the board narratively even if it underperforms. Real but not a sound basis for the decision.
  • Morale / momentum of shipping something bold.
  • Recommended: B now (fix the funnel) as the cheapest, most reversible move that also tests whether packaging was ever the real problem; run C in parallel. Treat A as a deferred bet gated on the conversion pilot.
  • Would flip if: the funnel is already healthy (then B has little headroom and A/C rise), or the conversion pilot shows strong ICP free-to-paid economics (then A’s upside becomes worth the irreversibility).

Note: the value is that the explicit weights (reversibility and cost-risk both high) demote the option with the biggest raw upside. A single total would have hidden that A wins only on the criteria we deliberately down-weighted. Test the recommendation with What Would Have to Be True, then premortem the chosen plan.

What the research does and does not show, with graded sources

Single source of truth for the decision-option-review skill. The SKILL.md, sidecar, and evals derive from this.

Skillthinking-framework-skills.decision-option-review (installable name think-decision-option-review)
Familydecision-and-option-evaluation
Evidence tierP (flag: false-precision risk)
ConfidenceHigh that explicit criteria beat gut comparison; the numbers can mislead if over-trusted
Statusdraft (authored 2026-05-31 from the discovery corpus)

1. The mechanism (what actually does the work)

Section titled “1. The mechanism (what actually does the work)”

When several real options compete, intuition compares them on shifting, unstated criteria and the comparison cannot be inspected. This skill makes it explicit: list the options, define the criteria that actually matter and weight them, score each option against each criterion, and surface the tradeoffs, then recommend. The work is done by forcing the criteria and weights into the open (where they can be argued) and by making the tradeoffs visible rather than buried in a hunch. It is a lightweight multi-criteria review, not academic MCDA.

The honest caveat is built into the mechanism: numeric scores can manufacture false precision. The skill must show the tradeoffs and flag where a score is soft, not present a single total as if it settled the matter.

  • Multi-criteria decision analysis (MCDA). The UK Government’s MCDA guidance frames it as a way to choose rationally among options when objectives conflict, and stresses that it should support decision makers, not replace judgment.

No trademark. Named descriptively.

3. What the evidence shows, and what it does NOT show

Section titled “3. What the evidence shows, and what it does NOT show”

Supported: structured multi-criteria comparison is a long-standing, government-endorsed decision aid; making criteria and weights explicit improves the defensibility and transparency of a choice.

NOT shown: there is no evidence that a weighted score produces a correct decision, and over-trusting the arithmetic is a known failure (false precision; criteria and weights chosen to justify a favorite). Grade P with a flag; the value is the explicit tradeoffs, not the total.

Evidence is from human decision practice, not AI-augmented use. Transferred, not AI-validated. The AI value: a model can be asked to lay out criteria, weights, and tradeoffs explicitly and consistently, producing an inspectable matrix a human can challenge - far better than a hidden “I recommend X.”

Works best when: several real, distinct options compete; objectives conflict; the decision needs to be explained or defended; the tradeoffs are currently implicit.

Fails or misleads when (poor-fit / anti-patterns):

  • False precision - presenting a single weighted total as if it settled a close call (the central failure mode).
  • Criteria or weights chosen to justify an option already picked.
  • Ignoring factors that resist quantification (treating “unscoreable” as “unimportant”).
  • Trivial or obvious choices; or one-way doors that need deeper analysis than a matrix.
  • Generating options (use an ideation skill) - this compares options that already exist.

A criteria-weighted option matrix: options as columns (or rows), weighted criteria, a score per cell, the explicit tradeoffs each leading option makes, and a recommendation with a confidence note and the conditions under which it would flip. Soft scores are flagged.

  1. UK Government, MCDA guidance (multi-criteria decision analysis as a support for, not a replacement of, judgment).

Verification status: the UK MCDA guidance and the “support not replace judgment” framing are well-attested. Do not present weighted totals as proof of the right choice.

Thinking Framework Skills v0.3.0 · 38 frameworks