/boundary-condition-specification
SOP: Specify the boundary conditions under which a hypothesis holds
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill boundary-condition-specification --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
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/boundary-condition-specification
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The summary Claude sees to decide when to auto-load this skill.
SOP: Specify the boundary conditions under which a hypothesis holds
SKILL.md
boundary-condition-specification.SKILL.mdname: boundary-condition-specification
description: 'SOP: Specify the boundary conditions under which a hypothesis holds'
version: 1.0.0
category: hypothesis-formation
type: sop
campaign: hypothesis-formulation
input: Hypothesis draft (with statement + variables + mechanism)
output: Boundary condition list (temporal/spatial/population/conditional/exclusions)
dependencies:
skills:
- subagent-spawning
Boundary Condition Specification
Systematically identify the preconditions required for a hypothesis to hold, preventing overgeneralization.
HARD-GATE
<HARD-GATE> Preconditions (all must hold before starting): 1. At least 1 hypothesis draft is available (with statement and mechanism) 2. The hypothesis involves identifiable entities, time, or context
Not satisfied → stop and return error: hypothesis draft incomplete, cannot determine boundary conditions. </HARD-GATE>
Pipeline
1. Precondition check: verify completeness of the hypothesis draft 2. Temporal boundary: in what time period/historical era does the hypothesis hold? Is there a time sensitivity? 3. Spatial boundary: within what geographic/cultural/organizational scope does the hypothesis hold? 4. Population boundary: to what kind of subjects does the hypothesis apply (populations, species, system types)? 5. Conditional boundary: what preconditions are required for the hypothesis to hold (technical, institutional, environmental)? 6. Exclusion conditions: explicitly list the situations where the hypothesis does not apply 7. Output structured boundary condition list
Output Format
{
"hypothesis_id": "H1 (or hypothesis statement snippet)",
"boundary_conditions": {
"temporal": "Time period or duration constraints",
"spatial": "Geographic, cultural, or organizational scope",
"population": "Subject type, sample characteristics",
"conditional": ["Prerequisite condition 1", "Prerequisite condition 2"],
"exclusions": ["Situation where hypothesis does NOT apply"]
},
"generalizability": "narrow | moderate | broad",
"notes": "Any additional caveats"
}Each hypothesis draft yields 1 boundary condition object. </output>
Read more
name: boundary-condition-specification description: 'SOP: Specify the boundary conditions under which a hypothesis holds' version: 1.0.0 category: hypothesis-formation type: sop campaign: hypothesis-formulation input: Hypothesis draft (with statement + variables + mechanism) output: Boundary condition list (temporal/spatial/population/conditional/exclusions) dependencies: skills: - subagent-spawning
Boundary Condition Specification
Systematically identify the preconditions required for a hypothesis to hold, preventing overgeneralization.
HARD-GATE
<HARD-GATE> Preconditions (all must hold before starting): 1. At least 1 hypothesis draft is available (with statement and mechanism) 2. The hypothesis involves identifiable entities, time, or context
Not satisfied → stop and return error: hypothesis draft incomplete, cannot determine boundary conditions. </HARD-GATE>
Pipeline
1. Precondition check: verify completeness of the hypothesis draft 2. Temporal boundary: in what time period/historical era does the hypothesis hold? Is there a time sensitivity? 3. Spatial boundary: within what geographic/cultural/organizational scope does the hypothesis hold? 4. Population boundary: to what kind of subjects does the hypothesis apply (populations, species, system types)? 5. Conditional boundary: what preconditions are required for the hypothesis to hold (technical, institutional, environmental)? 6. Exclusion conditions: explicitly list the situations where the hypothesis does not apply 7. Output structured boundary condition list
Output Format
{
"hypothesis_id": "H1 (or hypothesis statement snippet)",
"boundary_conditions": {
"temporal": "Time period or duration constraints",
"spatial": "Geographic, cultural, or organizational scope",
"population": "Subject type, sample characteristics",
"conditional": ["Prerequisite condition 1", "Prerequisite condition 2"],
"exclusions": ["Situation where hypothesis does NOT apply"]
},
"generalizability": "narrow | moderate | broad",
"notes": "Any additional caveats"
}Each hypothesis draft yields 1 boundary condition object. </output>
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.
Open skill - /injection-fidelity
Loss-1 judge (codex role). Given one sample's de-identified dialogue and its PolicyCard, decide axis-by-axis whether the user-simulator enacted the card's per-axis pressure. Judge enactment of the card, never whether the research is good.
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
Tactic: Extract atomic units from one paper and score how much of a caller-supplied summary covers. Use for ACU-style binary or Nugget-style ternary recall checks; cannot run without a target summary.
Open skill

