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cf-integrations

价格未确认★ 28 GitHub Stars目录更新于 · 2026年9月12日agent-skill

概览

Render a live integration status dashboard for ContentForge — configured vs available MCP connectors grouped by category, coverage totals, and the top 3 quick-win connectors to add next, all taken from scripts/connector-status.py output. Triggers on \"/contentforge:cf-integrations\", \"what integrations are connected\", \"show connector status\", \"why can't a skill reach my CMS\", \"which connectors should I set up next\". Reads .mcp.json and environment variables only — no network calls, no agent; it reports status but does not configure anything. Pairs with /contentforge:cf-connect for guided setup and /contentforge:cf-add-integration for services outside the registry.

展开完整说明

以下为来源文档，不是本网站的操作指令。执行命令前请先核实权限。

/contentforge:cf-integrations — Integration Status Dashboard

Show the complete integration status for your ContentForge installation — configured vs available connectors, grouped by category, with workflow impact analysis and quick-win recommendations.

The ground truth about connectors

ContentForge ships with an empty .mcp.json ("mcpServers": {}) by design (v3.9.0 Cowork-safety decision). On a fresh install, expect 0 connectors configured (or 1-2 if the platform injects its own integrations). Nothing is pre-wired.

Every number in the dashboard must come from the live script output. Never render counts, percentages, or connected/available labels that are not present in the JSON returned by scripts/connector-status.py. Do not copy numbers from the example in this file.

When to Use

Use /contentforge:cf-integrations when:

You just installed ContentForge and want to see what's connected
You're troubleshooting why a skill can't reach an external service
You want to know which connectors to add next for maximum workflow coverage
You need a quick overview before onboarding a new team member
You're planning which integrations to set up for a new project

What This Command Does

Scan All Connectors — Run the status script; it checks the connector registry against your .mcp.json and environment variables
Build Status Dashboard — Group results by category with clear configured/available distinction
Calculate Coverage — Report exactly the totals the script returns
Recommend Quick Wins — Highlight the top 3 not-yet-configured connectors by workflow impact
Surface Category Gaps — Identify categories with zero coverage
Provide Next Steps — For each recommendation, point to /contentforge:cf-connect <name>

Required Inputs

Optional:

Category filter — Show only a specific category (e.g., --category=seo)
Show filter — connected, available, or all (default: all)

What Happens

Step 1: Connector Status Check

python scripts/connector-status.py --action status

This checks:

.mcp.json for HTTP connector entries the user has added
Environment variables for npx connectors (WordPress, Google Sheets, Semrush, DeepL, etc.)
Returns JSON with configured/available status per connector, grouped by category, plus summary totals

Step 2: Format Dashboard by Category

Render the script JSON as a category-grouped dashboard. Each category shows the category name and description, connectors marked [connected] or [available], transport type, and the skills each connector unlocks — all taken from the JSON.

SYNTHETIC EXAMPLE — fabricated for illustration. Always render your actual script output, never this block:

===========================================================
  ContentForge Integration Dashboard
  Connected: 1 of 22 (5%)
===========================================================

  KNOWLEDGE BASE — requirements, brand docs, reference material
  -----------------------------------------------------------
  [available]  Notion (HTTP) — content requirements, brand docs, editorial calendars
  [available]  Confluence (npx) — team wikis, brand guidelines

  CMS — content management and publishing
  -----------------------------------------------------------
  [connected]  Webflow (HTTP) — added by user to .mcp.json
  [available]  WordPress (npx) — needs WORDPRESS_SITE_URL, WORDPRESS_AUTH_TOKEN

  ... (remaining categories from script output)
===========================================================

A fresh install typically shows 0-2 connected. That is normal and expected — connectors are opt-in.

Step 3: Highlight Quick Wins

From the connectors the script reports as not configured, recommend the top 3 by workflow impact:

Notion — powers the most skills (content intake, brand docs, briefs, audits)
Google Sheets — batch requirement intake, analytics tracking
CMS (Webflow or WordPress) — end-to-end publish workflow
Design (Canva or Figma) — featured images and social graphics
SEO (Ahrefs) — real keyword data for briefs and audits

For each quick win, show: what it unlocks (from script JSON), setup route (/contentforge:cf-connect <name>), and effort (HTTP = one .mcp.json entry + OAuth on first use; npx = env vars + entry, Claude Code only).

Step 4: Show Coverage Summary

Render the script's summary block verbatim (total, connected, available, coverage percent) plus which categories have zero configured connectors.

Step 5: Provide Next Steps

  1. Connect your top quick win:      /contentforge:cf-connect <name>
  2. Setup guide for any connector:   /contentforge:cf-connect <name>
  3. Custom service not in registry:  /contentforge:cf-add-integration
  4. Full connector reference:        CONNECTORS.md and .mcp.json.connectors-reference

Transport Types

Transport	Setup Effort	Environment	Authentication
HTTP	Low — one `.mcp.json` entry (user-added)	Cowork + Claude Code	OAuth prompt on first use
npx	Moderate — env vars + `.mcp.json` entry	Claude Code only	API keys via environment variables

HTTP connectors work in both Cowork and Claude Code once the user adds them to .mcp.json (or connects them at the platform level in Cowork Settings → Integrations). npx connectors require local Node.js and work in Claude Code only. Use /contentforge:cf-connect <name> for step-by-step setup of either type.

Troubleshooting

"0 connectors connected" on a fresh install

This is the expected shipped state — .mcp.json starts empty. Use /contentforge:cf-connect <name> to add your first connector.

Dashboard shows an HTTP connector as "available" after you added it

The key name in .mcp.json must match the registry name exactly (e.g., notion, not Notion or notion-mcp)
Confirm .mcp.json is in the plugin root and contains valid JSON with a mcpServers object
Restart the session after editing .mcp.json

npx connector shows "not connected" even though env vars are set

Variables must be set in the shell session that launched Claude Code
Verify with echo $VARIABLE_NAME (should not be empty); on Windows restart the terminal after setting

Dashboard takes a long time

The script reads .mcp.json and environment variables only — no network calls. If slow, check for filesystem issues.

Agent Used

None. This skill is entirely script-driven using scripts/connector-status.py.

/contentforge:cf-connect — Guided setup for a specific connector
/contentforge:cf-add-integration — Connect services not in the registry
/contentforge:create-content — Main content production pipeline
/contentforge:batch-process — Sequential, checkpointed batch processing

Script: python scripts/connector-status.py --action status Network Required: No (reads local config only)

查看来源 ↗

文件元数据

name: cf-integrations
description: "Render a live integration status dashboard for ContentForge — configured vs available MCP connectors grouped by category, coverage totals, and the top 3 quick-win connectors to add next, all taken from scripts/connector-status.py output. Triggers on \"/contentforge:cf-integrations\", \"what integrations are connected\", \"show connector status\", \"why can't a skill reach my CMS\", \"which connectors should I set up next\". Reads .mcp.json and environment variables only — no network calls, no agent; it reports status but does not configure anything. Pairs with /contentforge:cf-connect for guided setup and /contentforge:cf-add-integration for services outside the registry."
effort: low
argument-hint: "[--category <name>]"

查看原始文本

---
name: cf-integrations
description: "Render a live integration status dashboard for ContentForge — configured vs available MCP connectors grouped by category, coverage totals, and the top 3 quick-win connectors to add next, all taken from scripts/connector-status.py output. Triggers on \"/contentforge:cf-integrations\", \"what integrations are connected\", \"show connector status\", \"why can't a skill reach my CMS\", \"which connectors should I set up next\". Reads .mcp.json and environment variables only — no network calls, no agent; it reports status but does not configure anything. Pairs with /contentforge:cf-connect for guided setup and /contentforge:cf-add-integration for services outside the registry."
effort: low
argument-hint: "[--category <name>]"
---

# /contentforge:cf-integrations — Integration Status Dashboard

Show the complete integration status for your ContentForge installation — configured vs available connectors, grouped by category, with workflow impact analysis and quick-win recommendations.

## The ground truth about connectors

ContentForge ships with an **empty `.mcp.json`** (`"mcpServers": {}`) by design (v3.9.0 Cowork-safety decision). On a fresh install, expect **0 connectors configured** (or 1-2 if the platform injects its own integrations). Nothing is pre-wired.

**Every number in the dashboard must come from the live script output.** Never render counts, percentages, or connected/available labels that are not present in the JSON returned by `scripts/connector-status.py`. Do not copy numbers from the example in this file.

## When to Use

Use `/contentforge:cf-integrations` when:
- You just installed ContentForge and want to see what's connected
- You're troubleshooting why a skill can't reach an external service
- You want to know which connectors to add next for maximum workflow coverage
- You need a quick overview before onboarding a new team member
- You're planning which integrations to set up for a new project

## What This Command Does

1. **Scan All Connectors** — Run the status script; it checks the connector registry against your `.mcp.json` and environment variables
2. **Build Status Dashboard** — Group results by category with clear configured/available distinction
3. **Calculate Coverage** — Report exactly the totals the script returns
4. **Recommend Quick Wins** — Highlight the top 3 not-yet-configured connectors by workflow impact
5. **Surface Category Gaps** — Identify categories with zero coverage
6. **Provide Next Steps** — For each recommendation, point to `/contentforge:cf-connect <name>`

## Required Inputs

**Optional:**
- **Category filter** — Show only a specific category (e.g., `--category=seo`)
- **Show filter** — `connected`, `available`, or `all` (default: `all`)

## What Happens

### Step 1: Connector Status Check

```
python scripts/connector-status.py --action status
```

This checks:
- `.mcp.json` for HTTP connector entries the user has added
- Environment variables for npx connectors (WordPress, Google Sheets, Semrush, DeepL, etc.)
- Returns JSON with configured/available status per connector, grouped by category, plus summary totals

### Step 2: Format Dashboard by Category

Render the script JSON as a category-grouped dashboard. Each category shows the category name and description, connectors marked `[connected]` or `[available]`, transport type, and the skills each connector unlocks — all taken from the JSON.

**SYNTHETIC EXAMPLE — fabricated for illustration. Always render your actual script output, never this block:**

```
===========================================================
  ContentForge Integration Dashboard
  Connected: 1 of 22 (5%)
===========================================================

  KNOWLEDGE BASE — requirements, brand docs, reference material
  -----------------------------------------------------------
  [available]  Notion (HTTP) — content requirements, brand docs, editorial calendars
  [available]  Confluence (npx) — team wikis, brand guidelines

  CMS — content management and publishing
  -----------------------------------------------------------
  [connected]  Webflow (HTTP) — added by user to .mcp.json
  [available]  WordPress (npx) — needs WORDPRESS_SITE_URL, WORDPRESS_AUTH_TOKEN

  ... (remaining categories from script output)
===========================================================
```

A fresh install typically shows 0-2 connected. That is normal and expected — connectors are opt-in.

### Step 3: Highlight Quick Wins

From the connectors the script reports as *not configured*, recommend the top 3 by workflow impact:

1. **Notion** — powers the most skills (content intake, brand docs, briefs, audits)
2. **Google Sheets** — batch requirement intake, analytics tracking
3. **CMS (Webflow or WordPress)** — end-to-end publish workflow
4. **Design (Canva or Figma)** — featured images and social graphics
5. **SEO (Ahrefs)** — real keyword data for briefs and audits

For each quick win, show: what it unlocks (from script JSON), setup route (`/contentforge:cf-connect <name>`), and effort (HTTP = one `.mcp.json` entry + OAuth on first use; npx = env vars + entry, Claude Code only).

### Step 4: Show Coverage Summary

Render the script's summary block verbatim (total, connected, available, coverage percent) plus which categories have zero configured connectors.

### Step 5: Provide Next Steps

```
  1. Connect your top quick win:      /contentforge:cf-connect <name>
  2. Setup guide for any connector:   /contentforge:cf-connect <name>
  3. Custom service not in registry:  /contentforge:cf-add-integration
  4. Full connector reference:        CONNECTORS.md and .mcp.json.connectors-reference
```

## Transport Types

| Transport | Setup Effort | Environment | Authentication |
|-----------|-------------|-------------|---------------|
| **HTTP** | Low — one `.mcp.json` entry (user-added) | Cowork + Claude Code | OAuth prompt on first use |
| **npx** | Moderate — env vars + `.mcp.json` entry | Claude Code only | API keys via environment variables |

HTTP connectors work in both Cowork and Claude Code once the user adds them to `.mcp.json` (or connects them at the platform level in Cowork Settings → Integrations). npx connectors require local Node.js and work in Claude Code only. Use `/contentforge:cf-connect <name>` for step-by-step setup of either type.

## Troubleshooting

### "0 connectors connected" on a fresh install
- This is the expected shipped state — `.mcp.json` starts empty. Use `/contentforge:cf-connect <name>` to add your first connector.

### Dashboard shows an HTTP connector as "available" after you added it
- The key name in `.mcp.json` must match the registry name exactly (e.g., `notion`, not `Notion` or `notion-mcp`)
- Confirm `.mcp.json` is in the plugin root and contains valid JSON with a `mcpServers` object
- Restart the session after editing `.mcp.json`

### npx connector shows "not connected" even though env vars are set
- Variables must be set in the shell session that launched Claude Code
- Verify with `echo $VARIABLE_NAME` (should not be empty); on Windows restart the terminal after setting

### Dashboard takes a long time
- The script reads `.mcp.json` and environment variables only — no network calls. If slow, check for filesystem issues.

## Agent Used

None. This skill is entirely script-driven using `scripts/connector-status.py`.

## Related Skills

- **[/contentforge:cf-connect](../cf-connect/SKILL.md)** — Guided setup for a specific connector
- **[/contentforge:cf-add-integration](../cf-add-integration/SKILL.md)** — Connect services not in the registry
- **[/contentforge:create-content](../../commands/create-content.md)** — Main content production pipeline
- **[/contentforge:batch-process](../batch-process/SKILL.md)** — Sequential, checkpointed batch processing

---

**Script:** `python scripts/connector-status.py --action status`
**Network Required:** No (reads local config only)

查看并核实来源

获取价格与运行成本

获取 Skill: 价格未确认
运行 Skill: 尚未确认运行要求，请查看来源中的 Agent、API 和服务费用。
许可证: MIT
价格未确认: 我们尚未确认此 Skill 的价格，现有来源与安装入口仍可使用。

免费获取不代表免费运行，价格标签不代表安全评级。提交价格信息 →

已记录技能来源

已记录技能指令路径，不代表本站运行测试、安全保证或兼容性认证。

安装前审查: 避免自动安装

许可证: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Low GitHub adoption signal
缺少 AI 审查批准
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 28 GitHub stars
Stars/forks activity: 28 stars, 5 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

打开完整审计

工具列表来自元数据，并非已测试的兼容性；Agent 提示词是建议的交接方式。

从一个小任务开始

1阅读来源，确认输入、预期输出、依赖和权限。
2先让 Agent 提出计划，批准环境配置和费用，再进行隔离的小规模测试。
3检查输出和变更文件，只报告实际执行结果，并保留来源版本以便复现。

请在来源中核实依赖、API 密钥及第三方费用。公开仓库不代表所有服务免费。

来源与使用须知

已收录静态检查通过

仓库元数据和审核信号仅供参考。受欢迎、已发现来源、成功运行是不同的事实。

来源仓库: indranilbanerjee/contentforge
许可证: MIT
版本: Unknown
最近 GitHub 推送: 2026年8月17日
目录更新于: 2026年9月12日
技能指令路径: skills/cf-integrations/SKILL.md @ 5f40253ff3a6

版本来自目录元数据，使用前请核实来源发布记录。

质量

53/100

需审查

信任

59/100

Do not auto-install

审计

69/100

需审查

打开完整审计查看评估报告

Dependency or permission surface needs review
Permission surface may require sandboxing
Low GitHub adoption signal
缺少 AI 审查批准
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 28 GitHub stars
Stars/forks activity: 28 stars, 5 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

Verified installs: —
结果: —

复制不等于安装。安装数需有成功安装回报，不代表全面的质量保证。

Agent 接入

本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号，让 Agent 无需抓取界面即可排序。

打开安装 API LLM 文本格式打开 Manifest 自动解析计划

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    "version": "trust-score-v4",
    "install_policy": "block",
    "evidence": {
      "stars": "28 GitHub stars",
      "repoActivity": "28 stars, 5 forks",
      "lastPushed": "2mo since push",
      "license": "MIT",
      "repository": "https://github.com/indranilbanerjee/contentforge/tree/master/skills/cf-integrations",
      "install": "npx skills add indranilbanerjee/contentforge --skill cf-integrations",
      "installSafety": "standard package or runtime install path",
      "permissionSurface": "secrets or environment access, shell or command execution",
      "documentation": "Strong README/SKILL.md context",
      "agentOutcomes": "No agent outcome data yet"
    },
    "outcome_evidence": {
      "total": 0,
      "successes": 0,
      "failures": 0,
      "not_relevant": 0,
      "success_rate": null,
      "recent_success_rate": null,
      "recent_failure_rate": null,
      "install_attempts": 0,
      "install_success_rate": null,
      "risk_blocked": 0,
      "setup_required": 0,
      "avg_output_quality": null,
      "production_outcomes": 0,
      "last_outcome_at": null,
      "label": "No agent outcome data yet"
    },
    "auto_install": {
      "allowed": false,
      "sandbox_required": true,
      "reason": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
    },
    "best_for": [
      "design-creative",
      "agent-skill"
    ],
    "known_risks": [
      "AI review approval is missing",
      "Low GitHub adoption signal",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "GitHub adoption: 28 GitHub stars",
      "Stars/forks activity: 28 stars, 5 forks; issue activity unavailable in current metadata",
      "Dependency/runtime risk: command execution surface, credential or environment access",
      "Permission surface: secrets or environment access, shell or command execution"
    ]
  },
  "agent_proven": {
    "version": "agent-proven-v1",
    "score": 0,
    "tier": "unproven",
    "label": "Needs first agent run",
    "summary": "No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.",
    "metrics": {
      "totalOutcomes": 0,
      "successfulOutcomes": 0,
      "failedOutcomes": 0,
      "installAttempts": 0,
      "installSuccessRate": null,
      "successRate": null,
      "recentSuccessRate": null,
      "recentFailureRate": null,
      "riskBlocked": 0,
      "setupRequired": 0,
      "notRelevant": 0,
      "avgOutputQuality": null,
      "avgTimeToUsefulMs": null,
      "productionOutcomes": 0,
      "humanReviewRequired": 0,
      "uniqueAgents": 0,
      "lastOutcomeAt": null
    },
    "signals": [],
    "penalties": [
      "No real agent outcome evidence yet"
    ]
  },
  "audit": {
    "score": 69,
    "risk_level": "needs_review",
    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "Low GitHub adoption signal",
      "AI review approval is missing",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "GitHub adoption: 28 GitHub stars",
      "Stars/forks activity: 28 stars, 5 forks; issue activity unavailable in current metadata"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 53,
    "label": "Needs review"
  },
  "supply": {
    "track": "Design and creative production",
    "scenario": "Design and creative",
    "maintenance": "2mo since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "production agents without a repository review",
    "Low GitHub adoption signal",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "AI review approval is missing",
    "Quality score needs review"
  ],
  "agent_contract": {
    "task_input": "Use cf-integrations in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 67/100 Manual review",
      "Audit: 69/100 Needs review",
      "Safety: 29/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "indranilbanerjee-cf-integrations (cf-integrations)",
      "install_command": "npx skills add indranilbanerjee/contentforge --skill cf-integrations",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "indranilbanerjee-cf-integrations",
      "task": "Use cf-integrations in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/indranilbanerjee-cf-integrations",
    "api": "https://www.openagentskill.com/api/agent/skills/indranilbanerjee-cf-integrations",
    "audit": "https://www.openagentskill.com/skills/indranilbanerjee-cf-integrations/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=indranilbanerjee-cf-integrations&task=Use%20cf-integrations%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20cf-integrations%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20cf-integrations%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/indranilbanerjee-cf-integrations/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/indranilbanerjee-cf-integrations"
  }
}

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创作者: indranilbanerjee
来源: indranilbanerjee/contentforge
收录方: OpenAgentSkill 社区索引

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