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interpretation: lens
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**Mandate:** The agent **MUST** verify that the evaluation is objective — criteria locked before scoring, scoring rationale documented, scenarios modeled honestly, and risk analysis not minimizing downside exposure. File feedback for any violation.

## Check

- **Criteria locked before scoring** — Evaluation criteria, weights, and scoring scale are written down before any option is scored. Any sign of post-hoc weight adjustment to favor a preferred option is the highest-priority finding.
- **Scoring rationale present** — Every (option × criterion) cell has score, reasoning citing specific upstream evidence, and a confidence rating. Bare numbers without reasoning are a finding.
- **Composite + breakdown** — The composite score is published alongside the unweighted breakdown by criterion. A composite-only summary hides where the answer comes from and is a finding.
- **Tradeoff pairs named** — The evaluator explicitly identifies dominated options AND the real tradeoff pairs where one option beats another on some criteria and loses on others. An evaluation that only ranks doesn't surface the decision.
- **Bear-case is real** — Scenario modeling includes a bear case that reflects genuinely adverse conditions the landscape says are plausible, not a base case with slightly worse numbers. Soft bear cases are a finding.
- **Killer-assumption stress tests** — The risk analyst stress-tested the killer assumptions the modeler named, with stress values, likelihoods, and outcomes. Stress tests that skip the named killers are a finding.
- **Differentiated risk profiles** — Risk analysis differentiates between options. An analysis where all options come out roughly equally risky almost always means the analysis didn't actually engage with the differences.
- **Mitigations feasibility-checked** — Risk mitigations name feasibility (capital, talent, capability stretch). Mitigations presented without feasibility checks are aspirational and a finding; flag unmitigated risks as unmitigated.
- **Honest downside** — Risk analysis does not minimize downside exposure to make the recommended option look more attractive than it is. A risk section that consistently rounds downward is a finding.

## Common failure modes to look for

- Criteria added or re-weighted mid-evaluation, with no documentation of why
- Scoring cells where reasoning is "scores higher because it's better aligned" without citing what specifically aligns
- A composite-only ranking with no breakdown showing where the difference comes from
- A "bear case" that's 10% worse than the base case across the board
- A risk list that's identical in shape across all options, suggesting it wasn't actually re-thought per option
- Mitigations that read like "we'll figure it out" or "the team will manage it"
- A killer-assumption stress section that quietly substitutes a softer assumption for the one the modeler called out
- Probability estimates given as bare values ("low", "30%") with no reasoning
