Token导航 LogoToken导航TokenDH.com
研究检索敏感数据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

783

周安装

32

GitHub Stars

1

下载量

253
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/fish-skills
仓库路径:skills/counselors
安装命令:
npx skills add https://github.com/skinnyandbald/fish-skills --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/fish-skills --skill counselors

简介

counselors 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 适用于需要根据关键词或任务场景从多个来源中筛选信息的场景。
  • 通过关键词、任务场景或来源线索进行信息检索与筛选。
  • 安装命令:npx skills add https://github.com/skinnyandbald/fish-skills --skill counselors。
  • 建议确认权限范围和维护状态,注意是否会触发联网或文件读写操作。

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 2: Agent Selection

Default agents: 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: claude-opus, gemini-3.1-pro, amp-smart 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]

## 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

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

34.66%
按下载量换算88

Claude

32.16%
按下载量换算81

Cursor

17.33%
按下载量换算44

Gemini CLI

9.97%
按下载量换算25

安全审计

Gen Agent Trust Hub

可疑

Socket

可疑

Snyk

未通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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