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scenario-planning
What might the future look like — construct multiple future scenarios, assess research approach robustness under different assumptions
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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What might the future look like — construct multiple future scenarios, assess research approach robustness under different assumptions
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Strategy: Attack an isomorphism claim by demanding an explicit structure-preserving map and trying to break it. Targets any multi-language claim of the form 'X ≅ Y ≅ … across N mathematical languages'. Forces the claim to either earn the word 'isomorphism' or be demoted to 'analogy'. Methods: category theory (functor/natural-iso criteria), model theory, Lakatos monster-barring.
Strategy: Dialectic engine retuned for truth-seeking, not survival. A defender steelmans a claim into its MOST falsifiable form, a critic attacks to refute it, a judge classifies the exchange into BROKEN/CORROBORATED/UNFALSIFIABLE — the judge does NOT pick a winner or score persuasiveness. Methods: Irving debate (repurposed), Toulmin argumentation, Mayo severe testing.
Strategy: Run BEFORE building any validator (sandbox/simulation/benchmark). Builds a non-circularity matrix of theory-claim × validator-assumption to detect when a validator would 'confirm' a theory only because it was built on the theory's own premises. A circular validator's PASS carries zero evidential weight. Methods: Cartwright nomological machines, Winsberg sanctioning-of-simulations, tautology detection.
Strategy: Attack a beautiful unified result on the suspicion that its beauty is the bug. Distinguishes EARNED simplicity (forbids/predicts/subsumes) from DECORATIVE simplicity (re-describes/relabels/accommodates). Directly serves the Occam aesthetic by making it a falsifiable bar, not a vibe. Methods: Sober parsimony-as-evidence, MDL, Meehl risky prediction, accommodation-vs-prediction.
Campaign: Truth-seeking adversarial validation for scientific research artifacts (NOT publication defense). Core question: Where have we fooled ourselves, and is each load-bearing claim even falsifiable? Win-condition is INVERTED from survival/resilience to active refutation. Methods: Popper falsificationism, Lakatos Proofs and Refutations, Mayo severe testing, Platt strong inference.
Strategy: Attack the evidential weight of an 'independent convergence' claim. When N reasoning paths all reach the same conclusion, the confidence boost is real only if the paths were actually independent. Measures shared-prior / shared-blindspot contamination and corrects the over-counted confidence. Methods: Bayesian agreement-as-evidence, correlated-error analysis, jury theorem assumptions.
| name | scenario-planning |
| description | What might the future look like — construct multiple future scenarios, assess research approach robustness under different assumptions |
| version | 1.0.0 |
| category | experiment-execution |
| type | campaign |
| strategies | ["morphological-scenario","narrative-scenario","stress-scenario","competitive-scenario","temporal-scenario"] |
| dependencies | {"strategies":["competitive-scenario","morphological-scenario","narrative-scenario","stress-scenario","temporal-scenario"],"sops":["context-checkpoint","context-init","experiment-execution-paper-overview","experiment-execution-paper-research","experiment-execution-paper-search","experiment-execution-quality-gate-check","experiment-execution-saturation-detection","experiment-execution-web-research","experiment-execution-web-search","scenario-synthesis"]} |
Before launching this campaign, verify:
If any gate fails, STOP and resolve before proceeding.
Construct a portfolio of plausible future scenarios spanning the uncertainty space, then assess how robust our research approach is under each scenario. The output is a robustness index plus contingency triggers that tell us when to pivot.
| Strategy | Question | When to Use |
|---|---|---|
| morphological-scenario | What are all possible combinations? | Systematic enumeration of all factor combinations needed |
| narrative-scenario | What is the story of each future? | Rich qualitative understanding of scenario dynamics needed |
| stress-scenario | What is the worst case? | Risk assessment and failure preparedness needed |
| competitive-scenario | What will competitors do? | Competitive landscape awareness needed |
| temporal-scenario | How does it evolve over time? | Technology evolution and timing decisions needed |
| Component | Token Budget | Subagent Calls |
|---|---|---|
| Driver identification | 8K | 1 |
| Parameter enumeration | 10K | 1 |
| Consistency filtering | 15K | 2 |
| Narrative construction | 12K per scenario | 1 per scenario |
| Impact assessment | 10K per scenario | 1 per scenario |
| Robustness scoring | 8K | 1 |
| Synthesis | 12K | 1 |
| Total (5 scenarios) | ~130K | ~15 |
A successful campaign produces at minimum:
研究过程经 context-management 落盘,与最终报告分属不同文件:
scenario-planning,
建立本 campaign 的过程 context 文件。init 幂等——同 Phase 重入返回原文件。scenario-planning-report 文件落盘(见该 SOP)。Optional, no fixed order; the final leaf is always a sop.
| Strategy | When to use |
|---|---|
| competitive-scenario | What will competitors do? — Competitive method progress prediction and time window analysis |
| morphological-scenario | What are all possible combinations? — Zwicky Box construction with CCA consistency filtering for systematic scenario enumeration |
| narrative-scenario | What is the story of each future? — Shell method narrative construction for rich qualitative scenario understanding |
| stress-scenario | What is the worst case? — Extreme condition construction and failure mode enumeration for risk preparedness |
| temporal-scenario | How does it evolve over time? — Short/medium/long-term timeline projection with technology maturity curves |
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| context-checkpoint | Append research process and results to the current Phase's context file. Each append MUST contain >=500 lines of markdown covering both process and results. Use this skill at plan-designated checkpoint points — typically after each strategy completes or at key decision nodes within a research Phase. |
| context-init | Create a new context file for a research Phase. Called once at Phase start to initialize the file that subsequent context-checkpoint calls will append to. Use this skill whenever a new research Phase begins and a fresh context file is needed. |
| experiment-execution-paper-overview | Import SOP: paper landscape scan (from literature-engine skill) |
| experiment-execution-paper-research | Import SOP: paper full-text reading (from literature-engine skill) |
| experiment-execution-paper-search | Import SOP: paper AI summary reading (from literature-engine skill) |
| experiment-execution-quality-gate-check | Shared SOP: verify quality gate criteria are met before proceeding |
| experiment-execution-saturation-detection | Shared SOP: detect information saturation — know when to stop searching/analyzing |
| experiment-execution-web-research | Import SOP: deep full-page content analysis (from web-browsing skill) |
| experiment-execution-web-search | Import SOP: quick web scan discovery (from web-browsing skill) |
| scenario-synthesis | Comprehensive scenario analysis report synthesizing all scenario work |