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Openclaw

作者 vinyl bones · GitHub ↗ · v1.4.0
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在 OpenClaw 中安装
/install bkmrk
功能描述
Bookmark intelligence for developers. Browse, search, triage, and manage your AI-analyzed library. Submit URLs, assign projects, trigger deep analysis, and e...
使用说明 (SKILL.md)

BKMRK — Bookmark Intelligence

You are connected to the user's BKMRK library. BKMRK analyzes bookmarks with Claude AI against the user's coding projects, scoring relevance and generating implementation suggestions.

Terminology: The pipeline statuses are newstageddone. Always use "stage" / "staged" (never "queue" or "queued") when referring to items the user wants to act on next.

What Gets Analyzed

BKMRK performs deep content extraction across all source types:

  • Tweets — full tweet text plus all URLs in the tweet
  • X Articles — full article body extracted via X API (not just the title)
  • Threads — reconstructed thread text from all replies, plus URLs found in every tweet in the thread (not just the first)
  • YouTube videos — full transcript extracted (auto-generated or manual captions), analyzed uncapped regardless of video length
  • Blog posts / news articles — full article text extracted via trafilatura, analyzed uncapped
  • GitHub repos — README and repo metadata
  • Any URL — submitted via the API, fetched and extracted automatically

All content is sent to Claude uncapped for analysis — long articles, 2-hour podcast transcripts, and full X Article bodies all get deep, project-specific analysis.

Authentication

All requests require the user's BKMRK API key as a header:

X-API-Key: {BKMRK_API_KEY}

The API key is available at https://bkmrkapp.com/settings under "Your API Key."

What You Can Do

Browse Library

Browse the analyzed bookmark library with filters. Returns scores, statuses, per-project analyses, and executable prompts. Use this for triaging, browsing, and pipeline management.

GET https://bkmrkapp.com/api/agent/library
X-API-Key: {BKMRK_API_KEY}

All query parameters are optional:

  • bookmark_id — Fetch a specific bookmark by UUID (use to check status after submit)
  • status — Filter by card status: new, staged, done, trashed
  • project_id — Filter by project UUID
  • min_score — Minimum relevance score (e.g. 7)
  • priority — Filter by priority: high, medium, low
  • source — Filter by source: sync (from X bookmarks) or agent (submitted via API)
  • limit — Max results (default: 50, max: 100)
  • include_project_analyses — Include per-project deep analysis data (default: true)

Examples:

  • Unactioned high-value items: ?status=new&min_score=7
  • Items staged for a specific project: ?status=staged&project_id=\x3Cuuid>
  • Agent-submitted items only: ?source=agent
  • Low-priority items for cleanup: ?priority=low&min_score=0

Search Library

Keyword search across titles, explanations, actions, authors, and URLs. Use this when looking for something specific.

POST https://bkmrkapp.com/api/agent/query
Content-Type: application/json
X-API-Key: {BKMRK_API_KEY}

{
  "q": "search terms",
  "project": "ProjectName",
  "priority": "high",
  "status": "new",
  "limit": 10
}

All fields are optional. Returns results sorted by relevance score.

Manage Card Status

Move cards through the pipeline: new → staged → done, or trash/restore them.

POST https://bkmrkapp.com/api/status
Content-Type: application/json
X-API-Key: {BKMRK_API_KEY}

Single item:

{ "bookmark_id": "\x3Cuuid>", "status": "staged" }

Batch update:

{ "items": [
    { "bookmark_id": "\x3Cuuid>", "status": "done" },
    { "bookmark_id": "\x3Cuuid>", "status": "trashed" }
] }

Valid statuses: new, staged, done, trashed (use exact values — "staged" not "stage", "trashed" not "trash"). You can also set "channel": "channel-name" on any item.

Manage Projects

List, create, and update coding projects that bookmarks are analyzed against.

List projects:

GET https://bkmrkapp.com/api/projects
X-API-Key: {BKMRK_API_KEY}

Returns all projects with IDs, names, descriptions, tech stacks, and focus areas. Use this to get project UUIDs for other calls.

Create a project:

POST https://bkmrkapp.com/api/projects
Content-Type: application/json
X-API-Key: {BKMRK_API_KEY}

{
  "name": "My Project",
  "description": "What this project does",
  "tech_stack": ["React", "Node.js"],
  "focus_areas": ["performance", "auth"],
  "analysis_persona": "You are a senior React developer focused on performance optimization and server components.",
  "scoring_bias": "Prioritize: React Server Components, streaming SSR, bundle optimization. Deprioritize: Vue, Angular, jQuery."
}

Optional persona fields:

  • analysis_persona — A role description injected into Claude's system prompt when analyzing bookmarks against this project. Makes analysis domain-aware rather than generic. Example: "You are a senior iOS developer focused on SwiftUI patterns, performance optimization, and Claude AI integration for music apps."
  • scoring_bias — What topics to weight highly or deprioritize for this project. Example: "Prioritize: SwiftUI, barcode scanning, vinyl/music, AI agents, Claude skills. Deprioritize: web frameworks, marketing tools."

Update a project:

PUT https://bkmrkapp.com/api/projects
Content-Type: application/json
X-API-Key: {BKMRK_API_KEY}

{
  "id": "\x3Cproject-uuid>",
  "description": "Updated description",
  "tech_stack": ["React", "Next.js"],
  "analysis_persona": "You are a full-stack Next.js engineer...",
  "scoring_bias": "Prioritize: App Router, Server Actions, edge runtime."
}

Deep Analysis

Trigger a deep re-analysis of a bookmark against specific projects. Uses Claude Sonnet for thorough analysis. Returns 202 immediately; results appear in the library within 1-2 minutes.

POST https://bkmrkapp.com/api/reanalyze
Content-Type: application/json
X-API-Key: {BKMRK_API_KEY}

{
  "bookmark_id": "\x3Cuuid>",
  "project_ids": ["\x3Cproject-uuid>"]
}

Returns job_id, credits_used, and credits_remaining. Each project counts as 1 credit. Limits: Free 25/month, Pro 100/month, Scale 500/month.

Understand Context

Get the user's dashboard summary: projects, tier, stats, and library counts.

GET https://bkmrkapp.com/api/context
X-API-Key: {BKMRK_API_KEY}

Returns project list, subscription tier, total bookmarks, items by status, and sync history.

Submit URLs

Send any URL to the library for AI analysis. Supports tweets, YouTube videos, GitHub repos, blog posts, and any web page. Enrichment and analysis run in the background.

POST https://bkmrkapp.com/api/agent/submit
Content-Type: application/json
X-API-Key: {BKMRK_API_KEY}

{
  "url": "https://example.com/interesting-article"
}

Supported URL types:

  • Tweet URLs (x.com/user/status/123) — fetches full tweet data, thread context, and all URLs
  • YouTube URLs — extracts full video transcript for analysis
  • Any other URL — extracts full article text, title, and og:image

Optionally include "project_ids": ["\x3Cuuid>"] to analyze against specific projects. Returns 202 with bookmark_id and job_id. Results appear in 1-2 minutes.

Submissions count towards your monthly bookmark cap (Pro 200/month, Scale 500/month). Requires a paid plan.

Create Account (Onboarding)

If the user doesn't have a BKMRK account yet:

POST https://bkmrkapp.com/api/agent/onboard
Content-Type: application/json

{
  "email": "[email protected]",
  "consent": true
}

Returns an API key immediately. No OAuth needed.

Example Agent Workflows

Daily triage

  1. GET /api/context — check current state
  2. GET /api/agent/library?status=new&min_score=7 — find high-value unactioned items
  3. POST /api/status — stage the best ones, trash the noise

Project deep-dive

  1. GET /api/projects — get project UUIDs
  2. GET /api/agent/library?project_id=\x3Cuuid> — see what's relevant to that project
  3. POST /api/reanalyze — deep-analyze items that lack per-project data
  4. GET /api/agent/library?project_id=\x3Cuuid> — review enriched results

Bulk cleanup

  1. GET /api/agent/library?priority=low&min_score=0 — find low-value items
  2. POST /api/status with batch "status": "trashed" — clear them out

Submit and verify

  1. POST /api/agent/submit with a URL — returns bookmark_id
  2. GET /api/agent/library?bookmark_id=\x3Cuuid> — check status
    • If "status": "processing" → analysis still running, wait 30-60s and retry
    • If items array has results → analysis complete, show the user the score, explanation, and action

Full API Documentation

For complete endpoint documentation, pricing tiers, and capabilities:

GET https://bkmrkapp.com/agent.json
安全使用建议
Before installing or giving this skill an API key: 1) Confirm with the publisher or homepage (https://bkmrkapp.com) that BKMRK_API_KEY is the expected credential and ask them to update the skill metadata to declare it explicitly (requires.env / primaryEnv). 2) Understand that the service will extract and send full article bodies, transcripts, and repository README contents to their analysis pipeline (they state this is sent to Claude 'uncapped') — do not submit private, proprietary, or sensitive URLs unless you accept that exposure. 3) Prefer creating a scoped or revocable API key with minimal permissions, test the skill with non-sensitive bookmarks first, and verify privacy/retention policies on bkmrkapp.com and any underlying LLM provider. 4) If you need stronger guarantees, request that the skill author document how credentials are stored/used and whether data can be restricted or redacted before analysis. Installing is not blocked by these findings, but proceed carefully because the missing credential declaration and uncapped data analysis increase privacy risk.
功能分析
Type: OpenClaw Skill Name: bkmrk Version: 1.4.0 The skill bundle appears benign. It provides a well-defined interface for an AI agent to interact with the `bkmrkapp.com` service, managing bookmarks and projects. All API calls are directed to the stated domain, and authentication uses a user-provided API key as expected. There are no instructions for data exfiltration, malicious execution, persistence, or prompt injection against the OpenClaw agent itself. The `SKILL.md` clearly outlines the purpose and usage of the API endpoints without any hidden or harmful directives.
能力评估
Purpose & Capability
The SKILL.md clearly requires a BKMRK API key (X-API-Key) to call bkmrkapp.com endpoints and describes features that match the 'bookmark intelligence' purpose. However, the skill metadata lists no required environment variables or primary credential. That mismatch (instructions demanding an API key but registry declaring none) is an incoherence that could hide how the agent obtains credentials or how the user is prompted to provide them.
Instruction Scope
Instructions stay within the bulletin-board/bookmark domain (browse, search, stage, reanalyze, manage projects). They do not direct the agent to read local files or unrelated environment variables. Important behavioral detail: the doc states that 'all content is sent to Claude uncapped' and that BKMRK will extract full transcripts, full article bodies, GitHub README contents, etc. That is consistent with the feature but creates a high data-exposure surface (potentially large and sensitive payloads sent off-platform).
Install Mechanism
This is an instruction-only skill with no install spec and no code files, so nothing will be downloaded or written by an installer. That minimizes supply-chain risk.
Credentials
The runtime examples require a BKMRK_API_KEY header for every call, which is proportionate to the service's API usage. However, the skill metadata does not declare any required environment variables or a primary credential, so there's no explicit, reviewed declaration of how credentials are supplied or managed. Also, the described behavior (uncapped forwarding of arbitrary submitted URLs and long transcripts to third-party LLMs) increases the sensitivity of the single credential—any key given grants access to a system that will process possibly private content.
Persistence & Privilege
The skill does not request always:true, does not declare persistent system changes, and does not modify other skills' configurations. The default autonomous invocation setting is unchanged and is expected for skills.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install bkmrk
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /bkmrk 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.4.0
v1.4.0 - Added project-level persona fields—`analysis_persona` and `scoring_bias`—to project creation and update, allowing domain-aware analysis and custom topic weighting. - Documented the new optional query parameter `bookmark_id` for fetching a specific bookmark with the library endpoint. - Updated submission limits to clarify higher caps require a paid plan (Pro 200/month, Scale 500/month). - Expanded project creation and update documentation with usage examples for the new fields.
v1.3.0
- Added a new "What Gets Analyzed" section detailing deep content extraction for Tweets, X Articles, Threads, YouTube videos, blog posts, and GitHub repos. - Clarified that all content types are sent to Claude uncapped for in-depth analysis. - Expanded and clarified supported URL types and extraction details in the "Submit URLs" section. - Improved documentation about handling and analysis of threads, full article extraction, and long-form content. - General documentation enhancements for clearer guidance on usage.
v1.2.1
- Clarified terminology for pipeline statuses; explicitly state to use "stage" / "staged" (never "queue"/"queued") for next-action items. - Added a dedicated "Terminology" note to emphasize correct language in user workflows. - No functional or API changes; this update focuses on documentation precision and clearer guidance.
v1.2.0
No changes detected in this version. - No updates or file modifications were made in version 1.2.0.
v1.1.0
Renamed queued to staged across all status references. Added glowing edge card effects to homepage.
v1.0.0
- Initial release of BKMRK skill. - Submit URLs to your BKMRK library for AI analysis and implementation suggestions. - Query your analyzed bookmark library with advanced filters by project, priority, status, and more. - Create a new BKMRK account and receive an API key instantly. - Integration with your coding projects for relevance scoring and actionable insights.
元数据
Slug bkmrk
版本 1.4.0
许可证
累计安装 0
当前安装数 0
历史版本数 6
常见问题

Openclaw 是什么?

Bookmark intelligence for developers. Browse, search, triage, and manage your AI-analyzed library. Submit URLs, assign projects, trigger deep analysis, and e... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 435 次。

如何安装 Openclaw?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install bkmrk」即可一键安装,无需额外配置。

Openclaw 是免费的吗?

是的,Openclaw 完全免费(开源免费),可自由下载、安装和使用。

Openclaw 支持哪些平台?

Openclaw 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Openclaw?

由 vinyl bones(@bonesvinyl)开发并维护,当前版本 v1.4.0。

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