/boundary-probing
Map parameter space, generate extreme values, test at boundaries, detect
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill boundary-probing --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/boundary-probing
Context preview
The summary Claude sees to decide when to auto-load this skill.
Map parameter space, generate extreme values, test at boundaries, detect
SKILL.md
boundary-probing.SKILL.mdname: boundary-probing
description: Map parameter space, generate extreme values, test at boundaries, detect
breakpoints, synthesize validity envelope.
type: tactic
strategies:
- boundary-enumeration
- validity-envelope-mapping
- critical-case-design
dependencies:
sops:
- breakpoint-detection
- extreme-value-generation
- parameter-space-mapping
- stress-test-validity-envelope-construction
Boundary Probing
Orchestration Steps
1. Receive claim and parameter context from strategy 2. Dispatch `parameter-space-mapping` to identify all dimensions 3. For each dimension, dispatch `extreme-value-generation`:
- Minimum, maximum, zero, negative, overflow
- Type boundaries (empty, null, singleton, infinite)
4. Dispatch `breakpoint-detection` at each extreme value 5. Record pass/fail for each probe point 6. Dispatch `validity-envelope-construction` to synthesize boundaries
Subagents
- parameter-space-mapping
- extreme-value-generation
- breakpoint-detection
- validity-envelope-construction
Termination Conditions
- All dimensions probed at all boundary values (complete)
- Breakpoint found in critical dimension (early report)
- Budget exhausted (report partial envelope)
- Dimension count exceeds budget (prioritize by sensitivity)
<!-- BEGIN available-tables (generated) -->
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use | | --- | --- | | breakpoint-detection | Test a claim at extreme parameter values and detect the precise point where it breaks down. | | extreme-value-generation | Generate boundary and extreme test values for a given parameter dimension to stress-test claims. | | parameter-space-mapping | Identify all parameter dimensions along which a claim's validity might vary. | | stress-test-validity-envelope-construction | Synthesize breakpoints across dimensions into a coherent validity envelope for a claim. |
<!-- END available-tables (generated) -->
Read more
name: boundary-probing description: Map parameter space, generate extreme values, test at boundaries, detect breakpoints, synthesize validity envelope. type: tactic strategies: - boundary-enumeration - validity-envelope-mapping - critical-case-design dependencies: sops: - breakpoint-detection - extreme-value-generation - parameter-space-mapping - stress-test-validity-envelope-construction
Boundary Probing
Orchestration Steps
1. Receive claim and parameter context from strategy 2. Dispatch `parameter-space-mapping` to identify all dimensions 3. For each dimension, dispatch `extreme-value-generation`:
- Minimum, maximum, zero, negative, overflow
- Type boundaries (empty, null, singleton, infinite)
4. Dispatch `breakpoint-detection` at each extreme value 5. Record pass/fail for each probe point 6. Dispatch `validity-envelope-construction` to synthesize boundaries
Subagents
- parameter-space-mapping
- extreme-value-generation
- breakpoint-detection
- validity-envelope-construction
Termination Conditions
- All dimensions probed at all boundary values (complete)
- Breakpoint found in critical dimension (early report)
- Budget exhausted (report partial envelope)
- Dimension count exceeds budget (prioritize by sensitivity)
<!-- BEGIN available-tables (generated) -->
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use | | --- | --- | | breakpoint-detection | Test a claim at extreme parameter values and detect the precise point where it breaks down. | | extreme-value-generation | Generate boundary and extreme test values for a given parameter dimension to stress-test claims. | | parameter-space-mapping | Identify all parameter dimensions along which a claim's validity might vary. | | stress-test-validity-envelope-construction | Synthesize breakpoints across dimensions into a coherent validity envelope for a claim. |
<!-- 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.
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

