steel-manning
$
npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/steel-manningVerifies convergence decisions through adversarial challenge methods
- Tests decision resilience against strongest counter-arguments
- Uses Devil's Advocacy, Pre-mortem, Red Teaming, and Dialectical Inquiry
- Routes strategies based on signals like resurrection or criteria interrogation
- Delivers stress-tested decisions with documented counter-arguments
SKILL.md
.github/skills/steel-manningView on GitHub ↗
--- name: steel-manning description: Steel-Manning Campaign — adversarial verification of convergence decisions through resurrection advocacy, winner stress-testing, criteria interrogation, and multi-perspective attack using Devil's Advocacy, Pre-mortem, Red Teaming, Dialectical Inquiry methods. execution: campaign used-by: convergence --- # Steel-Manning Adversarial verification of convergence decisions. This campaign subjects winners, criteria, and rejected alternatives to rigorous challenge — ensuring that final decisions survive the strongest possible counter-arguments rather than merely the weakest objections. The campaign deploys four complementary attack vectors: resurrecting rejected candidates to test whether elimination was justified, stress-testing winners to find hidden weaknesses, interrogating the criteria framework itself, and simulating stakeholder objections for political feasibility. ## Strategy Routing | Signal | Strategy | |--------|----------| | resurrect rejected candidates / give losers a fair hearing | resurrection-advocacy | | stress-test the winner / find weaknesses in top pick | winner-stress-testing | | challenge the criteria themselves / meta-level questioning | criteria-interrogation | | simulate stakeholder objections / political feasibility | stakeholder-objection-simulation | | construct strongest counter-argument / dialectical challenge | counter-thesis-construction | ## Manifest ### Strategies | Strategy | Method Lineage | |----------|---------------| | resurrection-advocacy | Devil's Advocacy, Dialectical Inquiry, Adversarial Collaboration (Kahneman) | | winner-stress-testing | Pre-mortem (Klein), Red Teaming, Failure Mode Analysis | | criteria-interrogation | Assumption-based Planning, Critical Systems Heuristics, Boundary Critique | | stakeholder-objection-simulation | Role-play, Stakeholder Analysis, Political Feasibility | | counter-thesis-construction | Dialectical Inquiry, Thesis-Antithesis-Synthesis, Adversarial Debate | ### Tactics | Tactic | SOPs Used | |--------|-----------| | adversarial-debate-protocol | advocate-construction, critic-attack, judge-verdict | | assumption-excavation | assumption-extraction, assumption-challenge, conclusion-sensitivity | | multi-perspective-attack | perspective-assignment, perspective-attack, steel-manning-synthesis | ### SOPs | SOP | Input | Output | Shareable | |-----|-------|--------|-----------| | advocate-construction | rejected_candidate, context | strongest_case_for_resurrection | validation | | critic-attack | winner, advocate_case | attack_arguments[], severity_ratings | validation | | judge-verdict | advocate_case, critic_attacks | verdict, reasoning, conditions | validation | | assumption-extraction | decision, evidence | assumptions[], confidence_levels | — | | assumption-challenge | assumption | challenge_argument, alternative, impact_if_wrong | — | | conclusion-sensitivity | assumptions[], challenges[] | sensitivity_map, critical_assumptions[] | — | | perspective-assignment | decision, stakeholders | perspective_briefs[] | — | | perspective-attack | decision, perspective_brief | attacks[], constructive_alternatives[] | — | | steel-manning-synthesis | all_attacks, all_verdicts | final_verdict, surviving_concerns, modifications | — | ## Budget Table (M Tier) | Metric | Minimum | |--------|---------| | Attack perspectives | >= 3 distinct angles | | Debate rounds | >= 2 per contested decision | | Assumptions challenged | >= 5 per winner | | Final verdict | Explicit ACCEPT / REJECT / REVISE with evidence | ## MCP Tools - `mcp__wiki-vault__vault_search` — retrieve prior decisions and context - `mcp__wiki-vault__vault_query_graph` — trace dependency chains for impact analysis - `mcp__wiki-vault__vault_add_edge` — record challenge relationships ## Context Management The campaign maintains a **Challenge Ledger** tracking: - Which decisions have been challenged - Attack vectors applied to each - Verdicts rendered and their conditions - Surviving concerns requiring monitoring State is passed between strategies via the ledger. Each strategy updates it upon completion.
More from yogsoth-ai/de-anthropocentric-research-engine
- abductive-hypothesis-generationStrategy: 面对异常的最佳解释推理
- ablation-brainstormRemove components one by one, observe system changes to reveal hidden dependencies and generate ideas from structural gaps.
- ablation-component-mappingMap system architecture to ablatable units for ablation studies
- ablation-designDesign ablation studies to isolate component contributions in ML systems
- ablation-executionRemove components one by one from a system, record the response/impact of each removal.
- abp-vulnerability-classificationClassify assumptions on 2 axes — load-bearing (how much conclusion depends on it) × vulnerable (how likely to be false). Focuses attention on High-Load × High-Vulnerable quadrant.
- abstraction-extractionExtract abstract principles from concrete domain cases. Strips domain-specific details to reveal transferable mechanisms.
- abstraction-ladderPerform bisociation at multiple abstraction levels
- abstraction-ladderingMove between concrete and abstract framings — 3 levels up (Why?) and 3 levels down (How?) to find the most productive research level.
- abstraction-to-designAbstract biological principle to design principle. Bridge from biology to engineering.