一键在 Manus 中运行任何 Skill

ae-proof-agent

Diligence-grade product and technical analysis for the ae.ltd proof-agent concept, including comparison against Cursor and Omnara, MVP and production architecture, red-team review, and build-vs-buy evaluation. Use when Codex needs to create or critique PRDs, tech specs, competitive diligence, leadership memos, or multi-agent evaluation packs for agent-runtime, demo-agent, or proof-agent products.

在 Manus 中运行

概览

安装命令

npx skills add https://github.com/aegntic/cldcde --skill ae-proof-agent

复制此命令并粘贴到 Claude Code 中以安装该技能

来源

aegntic/cldcde

星标10

分支2

更新时间2026年3月13日 17:46

文件资源管理器

24 个文件

SKILL.md

readonly

name	ae-proof-agent
description	Diligence-grade product and technical analysis for the ae.ltd proof-agent concept, including comparison against Cursor and Omnara, MVP and production architecture, red-team review, and build-vs-buy evaluation. Use when Codex needs to create or critique PRDs, tech specs, competitive diligence, leadership memos, or multi-agent evaluation packs for agent-runtime, demo-agent, or proof-agent products.

ae-proof-agent

Read references/RESEARCH-GUARDRAILS.md first.

Then use the bundle in this order:

Read references/COMPETITIVE-DILIGENCE.md.
Use references/PRD.md and references/TECHSPEC.md as the base spec.
Run the prompt chain in prompts/ when generating comparable multi-agent outputs.
Score outputs with templates/SCORECARD.md.
Assemble the final memo with templates/FINAL-REPORT-OUTLINE.md.

Rules:

Separate Verified, Inference, and Unknown.
Do not invent backend details, customer metrics, or infra choices.
Use exact dates for recent releases and product changes.
Prefer primary sources when browsing is required.
Optimize for decision quality, not volume.

Use the prompt chain like this:

prompts/01-DISCOVERY.md for a source-grounded brief
prompts/02-PRD.md for product requirements
prompts/03-TECHSPEC.md for implementation planning
prompts/04-REDTEAM.md for failure analysis
prompts/05-SYNTHESIS.md for the final leadership memo

同仓库更多 Skills

同仓库

ae-ltd-claude-template-switchboard

aegntic/cldcde

Use when creating or upgrading CLAUDE.md instructions and selecting the right template baseline for repo size, architecture, and team constraints. AE.LTD template decision workflow.

2026-03-1110

ae-ltd-context7-radar

aegntic/cldcde

Use when coding decisions depend on current library/framework APIs and you need version-accurate docs before implementation. AE.LTD workflow tuned for fast, verifiable doc grounding.

2026-03-1110

ae-ltd-mcp-foundry

aegntic/cldcde

Use when scaffolding or extending MCP servers, adding tools/resources/prompts, or hardening MCP tool schemas and handlers. AE.LTD workflow tuned for production-ready MCP delivery.

2026-03-1110

ae-ltd-mutation-gate

aegntic/cldcde

Use when unit tests look green but confidence is low and mutation testing is needed to expose weak assertions. AE.LTD workflow for targeted mutation runs and actionable test hardening.

2026-03-1110

ae-ltd-n8n-orbit

aegntic/cldcde

Use when converting plain-language automation goals into production-ready n8n workflow JSON with retries, error paths, and credential-safe placeholders. AE.LTD automation blueprint workflow.

2026-03-1110

ae-ltd-skill-builder

aegntic/cldcde

Create new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization. Use when building custom skills, generating skill templates, fixing naming issues, or understanding the Claude Skills specification.

2026-03-1110

来源

aegntic

aegntic/cldcde

打开 GitHub 仓库查看创作者相关仓库

安装命令

下载

在 Manus 中运行

适用职业SOC

软件开发工程师计算机与数学类职业15-1252L4

name	ae-proof-agent
description	Diligence-grade product and technical analysis for the ae.ltd proof-agent concept, including comparison against Cursor and Omnara, MVP and production architecture, red-team review, and build-vs-buy evaluation. Use when Codex needs to create or critique PRDs, tech specs, competitive diligence, leadership memos, or multi-agent evaluation packs for agent-runtime, demo-agent, or proof-agent products.

ae-proof-agent

Read references/RESEARCH-GUARDRAILS.md first.

Then use the bundle in this order:

Read references/COMPETITIVE-DILIGENCE.md.
Use references/PRD.md and references/TECHSPEC.md as the base spec.
Run the prompt chain in prompts/ when generating comparable multi-agent outputs.
Score outputs with templates/SCORECARD.md.
Assemble the final memo with templates/FINAL-REPORT-OUTLINE.md.

Rules:

Separate Verified, Inference, and Unknown.
Do not invent backend details, customer metrics, or infra choices.
Use exact dates for recent releases and product changes.
Prefer primary sources when browsing is required.
Optimize for decision quality, not volume.

Use the prompt chain like this:

prompts/01-DISCOVERY.md for a source-grounded brief
prompts/02-PRD.md for product requirements
prompts/03-TECHSPEC.md for implementation planning
prompts/04-REDTEAM.md for failure analysis
prompts/05-SYNTHESIS.md for the final leadership memo