Actor Profiling

SkillDev tools

Understand who the user is — background, resources, constraints, and

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Actor Profiling skill

What this skill tells your AI

The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/actor-profiling/SKILL.md and read by ahel’s review.

Build a comprehensive model of the user as a research actor — who they are, what they have, what constrains them, and why they're doing this.

Available SOPs

SOPPurposeExecution
explore-resumeBackground, skills, projects, publications, research experiencedialogue (once only)
clarify-resourcesCompute, timeline, collaboration, data, environmentdialogue
ask-constraintsVenue targets, methodology preferences, avoidance areas, advisor requirementsdialogue
ask-intentionalityDeep WHY probing — motivation, risk tolerance, innovation preference, etc.dialogue

Methodology Guidance

The goal is to construct an ActorProfile with enough information to inform field exploration and goal decomposition. How you get there is your decision.

Typical flow:

  1. explore-resume first (one-time, never re-run)
  2. clarify-resourcesask-constraintsask-intentionality

But you may:

  • Return to ask-intentionality at any point when you discover a deeper WHY to probe
  • Interleave clarify-resources when intentionality probing reveals resource-related gaps
  • Skip or abbreviate SOPs when the user's initial message already provides the information

End condition: You judge that you have enough information to construct a meaningful ActorProfile. In cold-start scenarios, "enough" may mean just establishing boundaries (what the user won't do) rather than specifics.

Cold-Start Special Case

When the user doesn't know what they want or can do, the ActorProfile captures boundaries rather than commitments:

  • "User has experience in NLP and GNN, won't jump to physics/chemistry"
  • "Timeline is flexible, no hard deadline"
  • "Motivated by interest, not graduation pressure"

This is sufficient — later tactics will help narrow within these boundaries.

Output (Tactic-Level Aggregation)

After running the SOPs you deem necessary, synthesize an ActorProfile:

ActorProfile {
  background: { skills, projects, publications, researchExp }
  resources: { compute, timeline, collaboration, data, environment }
  constraints: { venue, methodology, avoidance, advisor }
  intentionality: {
    motivation, successDefinition,
    riskTolerance, innovationPreference,
    independencePreference, timeUrgency, learningWillingness
  }
  boundary: "..."  // what the user definitely won't do
}

This is a conceptual schema, not a JSON requirement. Express it in whatever format serves the downstream context best.

Available SOPs

Optional, no fixed order; the final leaf is always a sop.

SOPWhen to use
ask-constraintsUnderstand hard boundaries on the user's research — target venues, methodology preferences, areas to avoid, advisor/team requirements. Not limited to ML/AI — works for any research domain.
ask-intentionalityDeep 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.
clarify-resourcesUnderstand what resources the user has available for research — compute, timeline, collaboration, data access, experimental environment. Every item accepts 'TBD' as a valid answer.
explore-resumeUnderstand the user's background comprehensively — technical stack, project experience, research experience, publications, research directions. Allows user to express interest beyond their resume. Execute once only, never re-run.

Signals

GitHub stars
469
Forks
37
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
actor-profiling
Source
github.com/yogsoth-ai/de-anthropocentric-research-engine