Install
openclaw skills install @deciqai/anchoringActivate when: user says 'what's a fair price / starting number / ballpark'; counterparty just opened with a number; user is about to negotiate salary, valuation, or deal terms; user is making a forecast and a number has already been floated; user asks about 'first offer', 'framing effect', or 'being anchored'. Do NOT activate when: the number in question is a verifiable data point (audited financials, confirmed comparable) and is genuinely informative; or the decision is so trivial that the economic impact of anchoring is negligible.
openclaw skills install @deciqai/anchoringWhen people estimate an unknown quantity they start from a reference point — an anchor — and adjust. The adjustment is almost always insufficient, so the final answer stays closer to the anchor than it should. This pattern holds even when the anchor is explicitly random and subjects are told to ignore it (Tversky & Kahneman 1974). It survives expertise, explicit warnings, and financial incentives for accuracy.
Strategically: almost every consequential negotiation, valuation, or forecast begins with an anchor. The first number said or written — asking price, salary band, prior-round valuation, revenue projection — anchors everything that follows.
Composes with: pricing-strategy · expected-value-and-kelly · probabilistic-thinking · signaling-games
Apply when:
When NOT to use:
In Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.
Run the Anchoring Analysis. Detect anchors, judge their informational content, decide deliberately.
Anchor: [number] | Source: [who/how] | Status: [offer/comparable/casual/expectation]
Informational content: [genuinely informative / partial / pure anchor] — Evidence: […] Counter-evidence: […]
Anchor-free counterfactual: [my number without the anchor] | Gap vs. current "natural" answer: […]
Opposite-anchor test: [what would justify the other extreme] → range implication: […]
Decision: [proposer: bold-but-defensible opening] / [respondent: name/reset/work-with + specific number]
Risk anchor still operating: […] (how I'll know if I've been pulled too far)
→ Method in Action: Tversky & Kahneman's Wheel of Fortune, 1974
→ Primary sources: references/sources.md
[D] = designed upfront | [O] = observed in real use. [O] entries are more valuable.
| Fake move | Reality |
|---|---|
| [D] "I'm an expert — I'm not anchored" | Northcraft & Neale 1987 (real-estate agents) and Englich et al. 2006 (judges) show expertise is not protective. |
| [D] "I know the anchor is random, so it won't affect me" | The 1974 wheel told subjects it was random. Effect operated anyway. Knowing is the start of defense, not the conclusion. |
| [D] "I'll consider the anchor and then make my own judgment" | Every anchored subject believed this. Defense is generate-your-number-first, then look at the anchor. |
| [D] "Going first shows my cards — I'll let them open" | Galinsky & Mussweiler 2001: bold first offers produce better outcomes. Letting them open loses money on average. |
| [D] "Our forecast is bottom-up, not anchored" | If it started from last year's number or referenced the board's expectation, it is anchored. |
| [D] Setting an anchor outside the bounds of plausibility | Absurd anchors lose power and damage the negotiation. Bold = maximum within the plausibility range. |
| → 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.