Token导航 LogoToken导航TokenDH.com
研究检索执行命令github未标认证来源可访问许可证需确认审计异常

counselorscounselors 搜索

Agent Skill

counselors 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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

745

周安装

32

GitHub Stars

公开资料未说明

下载量

261
CodexClaudeCursorGemini CLI

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

unknown

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:counselors(counselors 搜索)
来源仓库:https://github.com/skinnyandbald/counselors
仓库路径:skills/counselors
安装命令:
npx skills add https://github.com/skinnyandbald/counselors --skill counselors
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/skinnyandbald/counselors --skill counselors

简介

counselors 向多个 AI 编码代理分发提示词并整合反馈,增强解决方案的多样性与鲁棒性。

  • 自动收集上下文信息如最近更改和相关代码片段。
  • 适用于需要多角度审视的问题,比如重构计划或新功能设计。
  • 执行过程中可能涉及大量计算资源消耗,请合理安排任务时机。
  • counselors 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Counselors — Multi-Agent Review Skill

Fan out a prompt to multiple AI coding agents in parallel and synthesize their responses.

Arguments: $ARGUMENTS

If no arguments provided, ask the user what they want reviewed.


Phase 1: Context Gathering

Parse $ARGUMENTS to understand what the user wants reviewed. Then auto-gather relevant context:

  1. Files mentioned in the prompt: Use Glob/Grep to find files referenced by name, class, function, or keyword
  2. Recent changes: Run git diff HEAD and git diff --staged to capture recent work
  3. Related code: Search for key terms from the prompt and read the most relevant files (up to 5 files, ~50KB total cap)

Be selective — don't dump the entire codebase. Pick the most relevant code sections.


Phase 1b: Context7 Staleness Scan

Detect the project's key technologies from package.json, CLAUDE.md, tsconfig.json, or config files (if not already clear from Phase 1 context). For up to 5 key libraries/frameworks:

  1. mcp__plugin_compound-engineering_context7__resolve-library-id — get the Context7 library ID
  2. mcp__plugin_compound-engineering_context7__query-docs — fetch 2-3 relevant snippets focused on APIs, configuration, and breaking changes

Limits:

  • Cap total reference documentation at ~8,000 tokens. Trim the least relevant snippets if exceeded.
  • If a library isn't found in Context7: add a line like [library name] (docs not verified) to the REFERENCE DOCUMENTATION block and continue.
  • If no specific libraries are identifiable from context: skip this phase entirely.

Build a REFERENCE DOCUMENTATION block with library name + version per entry. This block will be included in the prompt (Phase 3) so reviewers can flag outdated patterns.


Phase 2: Agent Selection

Default agents: or-claude-opus, or-gemini-3.1-pro, or-codex-5.4

  1. Use defaults unless the user overrides. If $ARGUMENTS does not contain agent-selection instructions (e.g. "use all agents", "add codex", "only gemini"), skip directly to the confirmation step with the defaults.
  2. If the user requests different agents (in $ARGUMENTS or via follow-up), discover available agents by running via Bash: counselors ls Print the full output, then ask the user to pick using AskUserQuestion. If 4 or fewer agents: Use AskUserQuestion with multiSelect: true, one option per agent. If more than 4 agents: AskUserQuestion only supports 4 options. Use these fixed options: Do NOT combine agents into preset groups (e.g. "claude + codex + gemini"). Each option must be a single agent or "All".

- Option 1: "All [N] agents" — sends to every configured agent - Option 2-4: The first 3 individual agents by ID - The user can always select "Other" to type a comma-separated list of agent IDs from the printed list above

  1. MANDATORY: Confirm the selection before continuing. Echo back the exact list you will dispatch to: Dispatching to: or-claude-opus, or-gemini-3.1-pro, or-codex-5.4 Then ask the user to confirm (e.g. "Look good?") before proceeding to Phase 3. This prevents silent tool omissions. If the user corrects the list, update your selection accordingly.

Phase 3: Prompt Assembly

  1. Generate a slug from the topic (lowercase, hyphens, max 40 chars)

- "review the auth flow" → auth-flow-review - "is this migration safe" → migration-safety-review

  1. Create the output directory via Bash. The directory name MUST always be prefixed with a second-precision UNIX timestamp so runs are lexically sortable and never collide: ./agents/counselors/TIMESTAMP-[slug] For example: ./agents/counselors/1770676882-auth-flow-review Mac tip: Generate with date +%s (seconds since epoch). Millisecond precision is NOT available via date on macOS without GNU coreutils — use date +%s for portable second-precision timestamps.
  2. Write the prompt file using the Write tool to ./agents/counselors/TIMESTAMP-[slug]/prompt.md:
# Review Request

## Question
[User's original prompt/question from $ARGUMENTS]

## Context

### Files Referenced
[Contents of the most relevant files found in Phase 1]

### Recent Changes
[git diff output, if any]

### Related Code
[Related files discovered via search]

## Reference Documentation
[Phase 1b content — current library docs from Context7. If Phase 1b was skipped, omit this section.]

## Instructions
You are providing an independent review. Be critical and thorough.
- Analyze the question in the context provided
- Identify risks, tradeoffs, and blind spots
- Suggest alternatives if you see better approaches
- Be direct and opinionated — don't hedge
- Structure your response with clear headings
- Flag any code patterns that appear outdated vs. the Reference Documentation above

Phase 4: Dispatch

Tell the user before dispatching:

"Dispatching to [N] agents: [list]. This typically takes 2-5 minutes..."

Note the prompt directory path you created (e.g. ./agents/counselors/1772865337-auth-flow-review/). The counselors CLI creates a sibling output directory with a second timestamp suffix.

Run counselors via Bash with the prompt file, passing the user's selected agents:

set -a; for f in ~/.env .env ~/.vibe-tools/.env; do [ -f "$f" ] && source "$f"; done; set +a; counselors run -f ./agents/counselors/[slug]/prompt.md --tools [comma-separated-selections] --json
Why the env sourcing? Claude Code's Bash tool may not inherit API keys (e.g. OPENAI_API_KEY) from the user's interactive shell. The set -a + source pattern loads keys from standard dotenv files portably (works in bash, zsh, sh). Files that don't exist are silently skipped.

Example: --tools claude,codex,gemini

Use Bash timeout: 480000 (8 minutes). Tools run in parallel (not sequentially). Per-tool timeouts in the counselors config control how long each individual tool gets.

Important: Use -f (file mode) so the prompt is sent as-is without wrapping. Use --json to get structured output for parsing.


Phase 5: Read Results (filesystem-based — does NOT depend on stdout)

IMPORTANT: Do NOT rely solely on JSON stdout. The CLI only writes run.json and prints JSON after ALL tools finish. If any tool hangs or the process is killed, stdout will be empty. Always fall back to scanning the filesystem.

Step 1: Find the output directory.

ls -dt ./agents/counselors/[slug]-*/ 2>/dev/null | head -1

If no directory found, the CLI failed before dispatching. Tell the user and suggest counselors doctor. Stop.

Step 2: Check for run.json (happy path). If run.json exists, parse it:

  • status: "success" with wordCount > 0 — genuine success
  • status: "timeout" — tool hit its timeout
  • status: "error" — tool crashed
  • status: "success" with wordCount: 0silent failure (read .stderr)

Step 3: If NO run.json, scan for individual files. For each expected tool, check if {tool-id}.md exists and has size > 0. Check {tool-id}.stderr for error details.

Step 4: Report to user.

  • All tools produced output: Proceed to Phase 6.
  • Some tools produced output: Tell the user which failed and why, then ask: "Continue with [N] of [M] responses, or retry?"
  • Zero tools produced output: Report errors. Suggest counselors doctor. Stop.

Phase 6: Synthesize and Present

Combine all agent responses into a synthesis:

## Counselors Review

**Agents consulted:** [list of agents that responded]

**Consensus:** [What most agents agree on — key takeaways]

**Disagreements:** [Where they differ, and reasoning behind each position]

**Key Risks:** [Risks or concerns flagged by any agent]

**Blind Spots:** [Things none of the agents addressed that seem important]

**Recommendation:** [Your synthesized recommendation based on all inputs]

---
Reports saved to: [output directory from manifest]

Present this synthesis to the user. Be concise — the individual reports are saved for deep reading.


Phase 7: Action (Optional)

After presenting the synthesis, ask the user what they'd like to address. Offer the top 2-3 actionable items from the synthesis as options. If the user wants to act on findings, plan the implementation before making changes.


Error Handling

  • counselors not installed: Tell the user to install it (npm install -g counselors)
  • No tools configured: Tell the user to run counselors init or counselors add
  • No output directory created: CLI failed before dispatching (bad config, missing binary). Check stderr from the Bash call.
  • Output directory exists but no run.json: CLI was killed before all tools finished. Scan for individual .md files — completed tools will have written their output. This is the most common partial-failure mode.
  • Silent failure (status: "success" but wordCount: 0, or .md file is 0 bytes): Read the .stderr file. Common causes: expired API key, 402 payment required, rate limit.
  • Single agent fails: Note it, ask user whether to continue with remaining responses or retry.
  • All agents fail: Report each error from .stderr files. Suggest counselors doctor. Do NOT proceed to synthesis.
  • Never wait indefinitely: The 8-minute Bash timeout is the hard ceiling. Do not add sleep/retry loops.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

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

Codex

35.82%
按下载量换算93

Claude

31.42%
按下载量换算82

Cursor

19.44%
按下载量换算51

Gemini CLI

9.81%
按下载量换算26

安全审计

Gen Agent Trust Hub

未通过

Socket

可疑

Snyk

未通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/skinnyandbald/counselors --skill counselors 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

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills