forge

Dispatch the Capability Forge to detect workforce gaps, scout for existing implementations, or author new skills/MCPs/plugins. Use this skill when the user asks "what capability are we missing", "build a skill for X", "check MCP Registry for Y", "what skills should we add", "extend the workforce", or when a retrospective mentions a recurring capability gap.

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仓库: TheAdaply/re-forge
最近来源活动: 2026年4月13日 15:04
检测到的 SKILL.md 语言: 英语
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分支: 0

安装方式

默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。

用 Codex 或 Claude 帮你安装复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。

直接命令不会经过审查 Prompt；运行前请先检查来源。

npx skills add https://github.com/TheAdaply/re-forge --skill forge

命令会保持在同一行。复制前请横向滚动并检查完整内容。

想先保存到本地？可下载 SkillsMP 当前能够提供的文件。

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决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。

SKILL.md

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causal-inference

Correlation-to-causation discipline for any "does X cause Y", "what is the effect of X", or "should we do X" question. Use when a decision rests on a causal claim drawn from observational data, an A/B test, an event study, or a regression with controls — before reporting any effect as causal. Enforces draw-the-DAG-first, identification-before-estimation, the design hierarchy (RCT > natural experiment > diff-in-diff > IV > controls), A/B-test pitfalls, and unmeasured-confounder sensitivity analysis.

2026-06-11

nnsight

Provides guidance for interpreting and manipulating neural network internals using nnsight with optional NDIF remote execution. Use when needing to run interpretability experiments on massive models (70B+) without local GPU resources, or when working with any PyTorch architecture.

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spec-driven

Use this skill for long-horizon agentic coding where a feature spans many turns and the agent drifts: it freezes a re-readable contract before code. Writes EARS-style requirements -> design -> task breakdown -> verification evidence, one feature directory per feature, with status gates and grep-able traceability IDs. Triggers on 'spec this out', 'write a spec', 'spec-driven', 'requirements then design', or planning a multi-session build.

2026-06-04

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name	forge
description	Dispatch the Capability Forge to detect workforce gaps, scout for existing implementations, or author new skills/MCPs/plugins. Use this skill when the user asks "what capability are we missing", "build a skill for X", "check MCP Registry for Y", "what skills should we add", "extend the workforce", or when a retrospective mentions a recurring capability gap.

Capability Forge dispatch

You are invoking the Capability Forge (forge-lead, H1 architecture).

What to do

Read ~/.claude/agent-memory/forge-lead/MEMORY.md — authored skills catalog + process lessons.
Read ~/.claude/agents/forge-lead.md — adopt this as your behavioral contract.
If the user specifies a gap, skip to step 5. Otherwise:
Run /forge:gap — inventory the workforce and detect gaps. Read the gap skill at ~/.claude/forge/skills/gap/SKILL.md and execute its method.
Run /forge:scout — query MCP Registry + anthropics/skills + marketplaces for existing implementations. Read ~/.claude/forge/skills/scout/SKILL.md.
Decision: INSTALL existing / ADOPT existing / AUTHOR new / DEFER to research.
If AUTHOR: run /forge:draft → /forge:test → /forge:promote pipeline.
If DEFER: write research-request drop-file and stop.

Hard rules

Never author what already exists — check registry + marketplaces first
Never promote without passing /forge:test (≥3 eval cases, ≥0.8 pass rate)
Every authored skill gets an ACE-style MEMORY.md bullet with helpful/harmful counters
Research-request handoff is user-mediated (no automated polling)

forge

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Capability Forge dispatch

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Hard rules

Capability Forge dispatch

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