/ask-intentionality
Deep WHY probing inspired by i* Intentionality modeling. Understand the
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill ask-intentionality --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
/ask-intentionality
Context preview
The summary Claude sees to decide when to auto-load this skill.
Deep WHY probing inspired by i* Intentionality modeling. Understand the
SKILL.md
ask-intentionality.SKILL.mdname: ask-intentionality
description: Deep WHY probing inspired by i* Intentionality modeling. Understand the
user's motivation, success definition, risk tolerance, innovation preference, independence
preference, time urgency, and learning willingness. The most important SOP in actor-profiling
— understanding WHY drives everything downstream.
execution: dialogue
Ask Intentionality
Deep WHY probing (i* Intentionality). Understanding motivation shapes every downstream decision.
Execution
Dialogue — inline, no subagent.
What to Ask About
- If user has a stated goal: Why this specific goal? What's driving it?
- Motivation depth: graduation requirement / pure interest / career advancement / impact / combination
- Success definition: What does "done well" look like to you?
- Risk tolerance: safe incremental improvement vs. high-risk high-reward breakthrough
- Innovation preference: improve existing methods vs. create entirely new approaches
- Independence preference: complete solo vs. depend on collaborators
- Time urgency: deadline-driven vs. long-term accumulation
- Learning willingness: use familiar tools/domains vs. learn new ones
Key Behaviors
- User may decline to answer (privacy). Accept gracefully. Note that downstream work becomes broader and may require more iteration.
- This SOP can be re-invoked by the tactic whenever new WHY questions emerge.
- Don't ask all dimensions at once — probe naturally based on conversation flow.
Output
Intentionality section of ActorProfile.
Read more
name: ask-intentionality description: Deep WHY probing inspired by i* Intentionality modeling. Understand the user's motivation, success definition, risk tolerance, innovation preference, independence preference, time urgency, and learning willingness. The most important SOP in actor-profiling — understanding WHY drives everything downstream. execution: dialogue
Ask Intentionality
Deep WHY probing (i* Intentionality). Understanding motivation shapes every downstream decision.
Execution
Dialogue — inline, no subagent.
What to Ask About
- If user has a stated goal: Why this specific goal? What's driving it?
- Motivation depth: graduation requirement / pure interest / career advancement / impact / combination
- Success definition: What does "done well" look like to you?
- Risk tolerance: safe incremental improvement vs. high-risk high-reward breakthrough
- Innovation preference: improve existing methods vs. create entirely new approaches
- Independence preference: complete solo vs. depend on collaborators
- Time urgency: deadline-driven vs. long-term accumulation
- Learning willingness: use familiar tools/domains vs. learn new ones
Key Behaviors
- User may decline to answer (privacy). Accept gracefully. Note that downstream work becomes broader and may require more iteration.
- This SOP can be re-invoked by the tactic whenever new WHY questions emerge.
- Don't ask all dimensions at once — probe naturally based on conversation flow.
Output
Intentionality section of ActorProfile.
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

