Install
openclaw skills install @deciqai/halo-effectActivate when: user is conducting a performance review or hiring interview; someone says 'she's great across the board' or 'everything they do is excellent'; user is evaluating a vendor, CEO, or investment and all attributes look uniformly positive or negative; user is reading business books or analyst reports and wants to assess whether the lessons generalize; user suspects their overall impression of a person or brand is distorting specific judgments. Do NOT activate when: the global impression is itself the legitimate judgment (e.g., overall product satisfaction driving a purchase); attribute-by-attribute analysis would cause decision paralysis.
openclaw skills install @deciqai/halo-effectA single positive or negative impression biases judgments of all unrelated attributes. A "great" CEO is assumed to have great strategy, vision, and execution; a beloved brand's features are rated higher than equivalent features from less-loved brands. Documented by Thorndike (1920), formalized by Nisbett & Wilson (1977), applied to business analysis by Rosenzweig (2007) — who showed business books overclaim because their descriptions follow company performance, not underlying reality.
Composes with fundamental-attribution-error, narrative-fallacy, confirmation-bias, hindsight-bias, survivorship-bias.
Not when: the global impression is itself the relevant judgment; attribute-by-attribute analysis would produce decision paralysis.
In Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.
[WAIT — do not advance until user responds]
[WAIT — do not advance until user responds]
[WAIT — do not advance until user responds]
Target | Attributes being rated | Decision | Current global impression
All attributes rated similarly? | Rating disproportionate to attribute-specific evidence? | Global impression precede the rating?
Per attribute: specific evidence | contrarian view | would blind test change anything?
Rubric + independent evaluators + blind where possible | Is this target a true outlier vs. base rates? | Base action on real-evidence attributes only
# Halo Effect Analysis: <evaluation>
Target: | Attributes: | Decision: | Global impression:
Halo test: all attributes similar Y/N | disproportionate to evidence Y/N | impression precedes rating Y/N
Decoupling — Attr A: evidence / contrarian / blind test | Attr B: ...
Structured eval: rubric | independent evaluators | blinding plan
Adjusted decision: real-evidence attrs | halo-inflated attrs | action
→ Method in Action: Thorndike 1920 + Nisbett-Wilson 1977 + Rosenzweig 2007 Business Application
| Domain | Halo move | Halo-corrected move |
|---|---|---|
| Performance review | "She's great across the board" | Rate each competency against rubric with anchors |
| Hiring interview | "He's a strong all-around candidate" | Structured interview with role-specific rubrics |
| Investment / CEO | "Great company, visionary leader" | Specific evidence per attribute; track decisions vs. outcomes |
| Business book | "These companies all have strong cultures" | Recognize as halo-inflated; check generalization |
| Brand / self-assessment | "We love Apple's everything" / "I'm doing great" | Blind comparison or specific metrics by area |
→ Primary sources: references/sources.md
[D] = designed upfront | [O] = observed in real use. [O] entries are more valuable.
| Fake move | Reality |
|---|---|
| [D] "Successful people just have multiple strengths" | Systematic cross-attribute correlations exceed independent assessment. It's halo. |
| [D] "I can see who's competent in an interview" | Unstructured interviews have weak predictive validity. Trust the rubric. |
| [D] "Their culture clearly drives results" | Post-hoc description of a successful company. May not generalize. |
| [D] "I'm not biased; I rate each attribute on its merits" | Nisbett & Wilson: people don't realize when global impression biases specific ratings. |
| [D] "Everyone says she's an A-player" | Consensus is amplifier, not corrective. Check the underlying evidence. |
| [D] "Business books distill what makes companies great" | Halo-contaminated descriptions of currently-favored companies. Hypotheses only. |
| → Add [O] entries here after each real use — paste the actual failure pattern | What went wrong and why |
Part of deciqAI Knowledge Skills — open-source thinking skills that make rigor executable for AI agents. Built by deciqAI · https://deciqai.com · Contributions welcome — see the template at the repo root.