A specialized upstream profiling skill that builds high-fidelity, reusable persona profiles to eliminate generic AI responses and improve downstream agent collaboration.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install dae-persona-context-injector
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install dae-persona-context-injector using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is DaE Persona Context Injector?
DaE Persona Context Injector is a sophisticated upstream profiling tool designed for the agentic era. Unlike standard chat interfaces that dive straight into execution, DaE focuses exclusively on building a robust PersonaProfile that captures the operator's unique context, constraints, and decision-making style. This ensures that any subsequent Openclaw Skills or agents you interact with have a deep, structured understanding of who they are working for, leading to highly tailored and relevant outputs.
By acting as a front-loaded context injector, DaE challenges vague self-descriptions and forces a rigorous examination of trade-offs and goals. It transforms the AI interaction from a generic exchange into a specialized partnership, making it an essential component for power users who require stable, context-aware downstream collaboration across diverse AI workflows.
DaE Persona Context Injector Use Cases
- Reducing generic, "hallmark-style" answers from downstream AI agents.
- Creating a persistent, reusable profile file for consistent AI collaboration across different sessions.
- Conducting structured elicitation and intake before high-stakes planning or technical execution.
- Capturing complex operator dynamics, including hidden constraints, internal tensions, and specific decision-making styles.
How DaE Persona Context Injector Works
- Opening Contract: The skill establishes a formal cognitive intake framework, outlining privacy boundaries and the goal of creating a reusable asset.
- Phase 1 (Baseline Intake): Captures high-level context and foundational operator data.
- Phase 2 (Issue Deep Dive): Performs a structured analysis of the most critical current challenges facing the operator.
- Phase 3 (Whole-Profile Sweep): Conducts a comprehensive review to identify gaps, verify consistency, and challenge assumptions.
- Phase 4 (Final Synthesis): Generates a multi-layered PersonaProfile, including human-readable summaries and machine-readable data for other Openclaw Skills.
DaE Persona Context Injector Setup
To install the DaE Persona Context Injector using the Openclaw Skills CLI, run the following command:
npx skills add https://github.com/sirsws/dae-persona-context-injector --skill dae-persona-context-injector
Ensure you have your environment configured to read the required reference files located in the references/ directory of the package.
DaE Persona Context Injector Data Schema & Taxonomy
The skill generates a structured PersonaProfile with metadata-rich fields. Each entry is validated against specific evidence and confidence metrics.
| Field | Description | Taxonomy |
|---|---|---|
| Background & Capabilities | Core history and skill sets | Confirmed, Inferred |
| Constraints & Resources | Operational boundaries and assets | Confirmed, UserWithheld |
| Drives & Goals | Primary motivations and targets | Confirmed, Inferred |
| Tensions & Challenges | Internal conflicts and external obstacles | Insufficient, Confirmed |
| DecisionStyle | How the operator evaluates trade-offs | Inferred, Confirmed |
All judgments include an evidence string, a confidence score, and a status label (Confirmed, Inferred, UserWithheld, or Insufficient).
DaE Persona Context Injector Advanced Features
- Adversarial Elicitation: Actively challenges vague answers and tests claimed values against actual historical trade-offs.
- Partial Profile Support: Gracefully handles early exits by marking withheld or insufficient data points rather than guessing.
- Downstream Injection: Designed specifically to feed into other Openclaw Skills to provide immediate, high-fidelity context without re-prompting.
- Machine-Readable Exports: Optional JSON output for seamless integration into automated multi-agent systems and custom LLM pipelines.
SKILL.md
Loading
Related Openclaw Skills
Loop Engine Governance
A policy enforcement layer for Openclaw Skills that routes agent decisions through human-in-the-loop approvals and runtime guards.
FreeRide
FreeRide automates the selection and configuration of high-quality free AI models from OpenRouter for the OpenClaw ecosystem.
Academic Engineering Literature Survey
A high-precision AI research agent that automates systematic engineering literature surveys and daily technical reading using formal academic methodologies.
RunningHub
A professional cloud platform for running ComfyUI workflows to generate AI images and videos via a robust API.
Skill Discovery & Installation
A specialized skill designed to browse, discover, and instantly install new capabilities from the open agent skills ecosystem.
blucli (blu)
A high-performance command line interface for discovering, controlling, and grouping Bluesound and NAD audio players.
Featured*
