/assumption-constraint
Which assumptions are most fragile? — Vulnerability ranking + impact
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill assumption-constraint --agent claude-codeHow it fires
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/assumption-constraint
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Which assumptions are most fragile? — Vulnerability ranking + impact
SKILL.md
assumption-constraint.SKILL.mdname: assumption-constraint
description: Which assumptions are most fragile? — Vulnerability ranking + impact
assessment of experiment assumptions
version: 1.0.0
category: experiment-execution
type: strategy
sops:
- assumption-challenging
- resource-quantification
tactics:
- sensitivity-ranking
dependencies:
sops:
- assumption-challenging
- resource-quantification
tactics:
- sensitivity-ranking
Strategy: Assumption Constraint
Methodology
Systematic assumption vulnerability analysis:
- **Extraction**: Surface all implicit and explicit assumptions
- **Scoring**: Quantify vulnerability (confidence × evidence / testability)
- **Impact assessment**: Blast radius × recovery cost
- **Prioritization**: Vulnerability × Impact = Priority
- **Validation planning**: Cheapest test that resolves uncertainty
Assumption categories: | Category | Examples | |----------|----------| | Technical | Method convergence, architecture suitability | | Data | Availability, quality, representativeness | | Resource | Sufficiency of compute, time, expertise | | Environmental | Tool stability, API access, policy | | Theoretical | Effect existence, measurability, magnitude |
Execution Flow
1. **Challenge Assumptions** → call `assumption-challenging` SOP
- Input: experiment plan, hypothesis
- Output: assumption inventory with validity assessment
2. **Quantify Validation Cost** → call `resource-quantification` SOP
- Input: validation experiments for top assumptions
- Output: cost to validate each assumption
3. **Rank Sensitivity** → invoke `sensitivity-ranking` tactic
- Determine which assumptions are most binding
4. **Report** → synthesize vulnerability assessment
- Top-5 fragile assumptions with validation paths
- Binding assumption constraint identification
Budget Gate
| Resource | Budget | Notes | |----------|--------|-------| | Subagent calls | ≤5 | 2 SOPs + synthesis | | Iterations | ≤2 | Re-rank if new assumptions surface | | Output size | ≤3000 tokens | Ranked table + validation plan |
<!-- BEGIN available-tables (generated) -->
Available Tactics
Optional, no fixed order; the final leaf is always a sop.
| Tactic | When to use | | --- | --- | | sensitivity-ranking | Rank constraints by sensitivity — which ones most impact the outcome if they shift |
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use | | --- | --- | | assumption-challenging | Challenge each assumption's validity — shared cross-repo SOP | | resource-quantification | Quantify resource demand vs supply vs gap for each resource category |
<!-- END available-tables (generated) -->
Read more
name: assumption-constraint description: Which assumptions are most fragile? — Vulnerability ranking + impact assessment of experiment assumptions version: 1.0.0 category: experiment-execution type: strategy sops: - assumption-challenging - resource-quantification tactics: - sensitivity-ranking dependencies: sops: - assumption-challenging - resource-quantification tactics: - sensitivity-ranking
Strategy: Assumption Constraint
Methodology
Systematic assumption vulnerability analysis:
- **Extraction**: Surface all implicit and explicit assumptions
- **Scoring**: Quantify vulnerability (confidence × evidence / testability)
- **Impact assessment**: Blast radius × recovery cost
- **Prioritization**: Vulnerability × Impact = Priority
- **Validation planning**: Cheapest test that resolves uncertainty
Assumption categories: | Category | Examples | |----------|----------| | Technical | Method convergence, architecture suitability | | Data | Availability, quality, representativeness | | Resource | Sufficiency of compute, time, expertise | | Environmental | Tool stability, API access, policy | | Theoretical | Effect existence, measurability, magnitude |
Execution Flow
1. **Challenge Assumptions** → call `assumption-challenging` SOP
- Input: experiment plan, hypothesis
- Output: assumption inventory with validity assessment
2. **Quantify Validation Cost** → call `resource-quantification` SOP
- Input: validation experiments for top assumptions
- Output: cost to validate each assumption
3. **Rank Sensitivity** → invoke `sensitivity-ranking` tactic
- Determine which assumptions are most binding
4. **Report** → synthesize vulnerability assessment
- Top-5 fragile assumptions with validation paths
- Binding assumption constraint identification
Budget Gate
| Resource | Budget | Notes | |----------|--------|-------| | Subagent calls | ≤5 | 2 SOPs + synthesis | | Iterations | ≤2 | Re-rank if new assumptions surface | | Output size | ≤3000 tokens | Ranked table + validation plan |
<!-- BEGIN available-tables (generated) -->
Available Tactics
Optional, no fixed order; the final leaf is always a sop.
| Tactic | When to use | | --- | --- | | sensitivity-ranking | Rank constraints by sensitivity — which ones most impact the outcome if they shift |
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use | | --- | --- | | assumption-challenging | Challenge each assumption's validity — shared cross-repo SOP | | resource-quantification | Quantify resource demand vs supply vs gap for each resource category |
<!-- END available-tables (generated) -->
The complete research orchestration system for AI-native science. What It Does Design Philosophy Architecture (v3.2.2) Quick Start Configuration Roadmap License DARE is not a tool that helps you do research. It is the researcher.
Repo: yogsoth-ai/de-anthropocentric-research-engine
Other skills on de-anthropocentric-research-engine.
- /formated-results
Closing skill for the research-executor, loaded as the last step of formated-specs. Summarize the design just produced into one research-result JSON fenced block in your reply. Do not execute the research.
Open skill - /formated-specs
Spec-slot skill for the research-executor. Emit the 4-layer DARE orchestration of the assigned topic as one research-graph JSON fenced block in your reply. Replaces the generic spec-writing step.
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Open skill - /ladder-quality-order
Loss-2 judge (codex role). Over one topic's 6 shuffled research-design samples, pairwise-rank by quality using the D1–D5 standard. Emit the pairwise log; the harness computes the order and the ladder verdicts. Judge quality difference, never against academic standards.
Open skill - /optimization-loop
The optimizer brain for the ladder-foundry pretraining loop. Runs the two-level nested batch loop, delegates gating to gate_eval, attributes a failing batch to one weight (attribute-first), and recovers from disk after compaction. Control flow is fully scripted; only the
Open skill - /acu-nugget-recall
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Open skill

