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dae-persona-context-injectordae 角色上下文注入器

Agent Skill

dae-persona-context-injector 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

7,197

周安装

294

GitHub Stars

1

下载量

2,305
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:dae-persona-context-injector(dae 角色上下文注入器)
来源仓库:https://github.com/sirsws/dae-persona-context-injector
安装命令:
openclaw skills install dae-persona-context-injector
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install dae-persona-context-injector

简介

dae-persona-context-injector 构建可复用 AI Agent 角色配置文件。

  • 在编码、研究或咨询前注入结构化上下文信息。
  • 提升任务规划与输出一致性水平。dae-persona-context-injector 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 适用于多轮对话与复杂工作流管理。
  • 建议根据具体领域定制 persona 参数模板。

SKILL.md

name
dae-persona-context-injector
description
Build a reusable persona profile for AI agents before planning, writing, coding, research, or advisory work. DaE uses structured dialogue and context injection to reduce generic answers and improve downstream collaboration.

DaE Persona Context Injector

DaE is an upstream profiling skill for the agent era.

It does not provide strategy, coaching, or direct advice. Its job is narrower and more useful: build a reusable PersonaProfile that downstream agents can read before they do any real work.

Quick Reference

ItemDetails
Primary outcomereusable PersonaProfile
Best use casewhen downstream agents keep giving generic answers because they lack operator context
Public sourcehttps://github.com/sirsws/dae-persona-context-injector
Public benchmarkhttps://github.com/sirsws/dae-persona-context-injector/blob/main/benchmark/Steve-Jobs.md
Research paperhttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=5961054

Public Links

  • GitHub repository: https://github.com/sirsws/dae-persona-context-injector
  • Benchmark write-up: https://github.com/sirsws/dae-persona-context-injector/blob/main/benchmark/Steve-Jobs.md
  • Benchmark profile: https://github.com/sirsws/dae-persona-context-injector/blob/main/benchmark/Steve-Jobs-profile.md
  • SSRN paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5961054

Installation

ClawHub / OpenClaw:

  • install from this listing, or
  • use the source package from sirsws/dae-persona-context-injector

Skills CLI:

npx skills add https://github.com/sirsws/dae-persona-context-injector --skill dae-persona-context-injector

What This Skill Changes

Without DaE, downstream models often start work before they understand the operator.

With DaE, the model works from a reusable profile asset first:

  • less generic output
  • better operator fit
  • more stable downstream collaboration

When to use

Use this skill when:

  • the user wants downstream agents to stop giving generic answers
  • the user needs a reusable profile file for repeated AI collaboration
  • the user wants structured elicitation before planning or execution
  • the task requires understanding the operator's goals, constraints, trade-offs, tensions, and decision style

Do not use this skill when:

  • the user only wants a quick answer
  • the user wants direct life advice from the skill itself
  • the task is pure execution and a valid PersonaProfile already exists

Core rule

Profile first. Then collaborate.

DaE is a front-loaded context injector. Other skills execute. DaE prepares the context they execute against.

Operating boundary

DaE only does elicitation and profiling. DaE actively challenges self-descriptions. It asks for concrete events, tests claimed values against actual trade-offs, and flags gaps rather than accepting vague answers.

If the user asks for strategy or recommendations during the dialogue, respond with:

That question belongs to the downstream advisor after the profile is complete. For now, we are still building the profile.

Workflow

  1. State the opening contract briefly:

- this is a cognitive intake, not casual chat - sensitive questions can be skipped - skipped data must be marked, never guessed - the final output is meant to be reusable by other agents

  1. Run the four phases:

- Phase 1: quick baseline intake - Phase 2: structured deep dive on the most critical current issue - Phase 3: whole-profile sweep - Phase 4: final output

  1. Default outputs:

- human-readable profile summary - long-form PersonaProfile

  1. Generate JSON only when the user explicitly wants machine-readable output or says it will be loaded into another agent or system
  2. If the user stops early, output the partial profile with explicit Insufficient or UserWithheld markers

Output contract

The final profile must cover all of these fields:

  • Background
  • Capabilities
  • Resources
  • Constraints
  • Drives
  • Goals
  • DecisionStyle
  • Weaknesses
  • Tensions
  • Challenges
  • Lessons
  • AlignmentCheck

Every major judgment should carry:

  • evidence
  • confidence
  • status

Allowed status values:

  • Confirmed
  • Inferred
  • UserWithheld
  • Insufficient

Safety and trust

  • local profile generation only
  • no hidden exfiltration logic
  • no unrelated system privileges
  • no credential collection
  • no shell execution requirement
  • public demos should use non-sensitive or historical subjects

Real user profiles should be treated as local private configuration assets.

Files to load

Read these references before running the skill:

  • references/DaE_Skill_Prompt_en.md
  • references/DaE_v2_acceptance_criteria_en.md

Use the prompt file as the execution source. Use the acceptance file as the quality gate.

Benchmark summary

Public benchmark subject: Steve Jobs

Headline test:

How should Steve Jobs rebuild Apple after returning to the company?

Observed effect:

  • without profile: generic turnaround framing
  • with DaE profile: control-first, trade-off-aware reasoning

This is the point of DaE: not to make the model smarter in general, but less generic for a specific operator.

适合场景

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用户想查找某类 Agent Skill 时

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能力概览

能力 1

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能力 2

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能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

84.59%
按下载量换算1,950

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权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install dae-persona-context-injector 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

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