Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add eric861129/SKILLS_All-in-one --skill elicitationgit clone --depth 1 https://github.com/eric861129/SKILLS_All-in-oneWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/eric861129/skills_all-in-one/elicitation)<a href="https://agentmods.dev/skills/eric861129/skills_all-in-one/elicitation"><img src="https://agentmods.dev/badge/skills/eric861129/skills_all-in-one/elicitation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/eric861129/skills_all-in-one/elicitation"><img src="https://agentmods.dev/badge/skills/eric861129/skills_all-in-one/elicitation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00130 | $0.03994 |
| Opus 5 | $0.00065 | $0.01997 |
| Sonnet 5 | $0.00026 | $0.00799 |
| Haiku 4.5 | $0.00013 | $0.00399 |
Grade A, and why
elicitation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- elicitation — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 476 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Elicitation
Psychological profiling through natural conversation.
Goal
When reviewing or creating content related to psychological elicitation—whether conversation scripts, interview questions, user research flows, or any code that implements these techniques—your goal is to achieve a 10/10 score.
Score all work on a 0-10 scale based on adherence to the principles and techniques in this skill. Provide your assessment as X/10 with specific feedback on what's working and what needs improvement to reach 10/10.
A 10/10 means the work:
- Embodies the core principle (depth through patience, not probing)
- Uses appropriate techniques from the research traditions
- Avoids all anti-patterns
- Creates conditions for authentic self-disclosure
Iterate until you reach 10/10.
Core Principle
Depth comes from patience, not probing.
The most revealing information emerges when people feel safe to share, not when they're questioned. Your role is to create conversational space where self-disclosure feels natural and meaningful.
Key insight: People want to tell their stories. They rarely get the chance.
Three Research Traditions
This skill synthesizes three complementary approaches:
1. Autobiographical Memory Research
How memories shape identity. Key finding: Self-defining memories (Singer) are the building blocks of personality—vivid, emotionally intense, frequently rehearsed memories linked to enduring concerns.
2. Narrative Identity Theory
How people construct life stories. Key finding: The narrative themes people use (redemption vs. contamination, agency vs. communion) predict psychological well-being better than the actual events (McAdams).
3. Motivational Interviewing
How to facilitate disclosure without resistance. Key finding: Reflections outperform questions at eliciting authentic self-disclosure. Aim for 2:1 reflection-to-question ratio (Miller & Rollnick).
Self-Defining Memories
Jefferson Singer identified five criteria that make a memory "self-defining":
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 476 lines · 130 tokens per session scan A e0223cfdffeb
elicitation is a skill published in the GitHub repository eric861129/SKILLS_All-in-one (52 stars, last pushed 4mo ago), licensed MIT. It adds 130 tokens to every session and 3,994 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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