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convit-setup确认设置

Agent Skill

convit-setup 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

190

周安装

8

GitHub Stars

1

下载量

67
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:convit-setup(确认设置)
来源仓库:https://github.com/kareem-aez/convit
仓库路径:skills/convit-setup
安装命令:
npx skills add https://github.com/kareem-aez/convit --skill convit-setup
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/kareem-aez/convit --skill convit-setup

简介

convit Setup 根据代码库结构生成 .convitrc.json 配置文件。

  • 适用于初始化 convit 工具链,自动适配项目类型与依赖关系。
  • 严禁直接读取 .env 类敏感文件,必须使用 scripts/ensure-convit-env.mjs 安全检测变量。
  • 遵循零凭证日志政策,不得输出或提交任何密钥、令牌等认证信息。
  • convit-setup 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

convit Setup

🚨 Security Mandate (CRITICAL)

  • Direct Environment Access Forbidden: Never use read_file, grep_search, or any other tool to read .env, .env.local, or any file containing secrets.
  • Environment Verification: To check for required CONVIT_* variables, you MUST ONLY use the ensure-convit-env.mjs script (located in the skill's scripts/ folder). This script safely checks variable names without exposing values.
  • Zero-Credential Policy: Never log, print, or commit any credentials or API keys.

convit Setup Overview

Generates a .convitrc.json tailored to the actual structure of the codebase. The config should capture Intent, not just file paths.

Quick start: (1) Apply the Hierarchy Principle to find the Primary Structural Boundary. (2) Run Structural Analysis (Full-Scan, Depth, Gitignore, Noise). (3) Apply Weighting Engine rules. (4) Synthesize patterns with user patterns first. (5) Ask user to confirm. (6) Write config.

Never include a provider block. API credentials (CONVIT_URL, CONVIT_KEY, CONVIT_MODEL) belong in .env only. The config file is safe to commit.

For the full semantics of every variable, see config-reference.md.


The Mental Model (The Hierarchy Principle)

Before scanning folders, identify the Primary Structural Boundary. This is the deepest semantic unit that defines how the codebase is organized. The agent must reason from first principles, not from a lookup table.

Surgical Core (Weight 10/8). Where the primary application logic lives. Common candidates: src/, lib/, app/. Domain-driven: src/features/auth/, src/modules/payments/, lib/domains/orders/. Layered: controllers/, models/, views/, or handlers/, services/, repositories/. Monorepo: packages/ or apps/ contains distinct projects. Each subdirectory is a top-level scope. Weight 10 for deepest semantic boundary, 8 for broad organizational folders.

Functional Layers (Weight 5). Cross-cutting concerns: ui/, db/, api/. The first segment under the core is the scope when fixed. Example: db/.*db, prisma/.*db.

Auxiliary Support (Weight 3/5). The tools and documentation that support the project. Weight 5: assets/, docs/, images/. Weight 3: .cursor/, .github/, scripts/.

Apply the Hierarchy Principle to any codebase. A 10-year-old COBOL project with cobol/programs/, cobol/copybooks/, cobol/data/ is layered. A brand-new Next.js app with src/app/(auth)/, src/app/(dashboard)/ is domain-driven. The reasoning engine adapts.


Phase 1 — Structural Analysis (Principles, not Folders)

Run this protocol. Do not rely on hardcoded paths.

Full-Scan Protocol

Scan every top-level directory. If a directory is not build noise (e.g. .cursor, .github, assets, docs, scripts), propose it as a scope. Total coverage: the generated config must capture the entire repo, not just application code.

Gitignore Intelligence

Primary Check. If a directory is in .gitignore, skip it. Git already handles it. Do not propose it as a scope or add it to exclude.

Exclusion Candidate. If a directory looks like build output (e.g. dist/, build/, out/, target/) but is NOT in .gitignore, it is a high-priority candidate for the exclude list. Propose adding it.

Detect Depth

Walk paths. If they go 3+ levels deep (e.g. src/features/auth/internal/), the middle segment is likely the scope. The pattern should capture that segment with ([^/]+). Shallow structures (e.g. src/auth.ts, src/user.ts) suggest a single src/([^/]+) pattern. Deep structures suggest domain-specific patterns like src/features/([^/]+)/.* or src/modules/([^/]+)/.*.

Identify Noise

Look for lockfiles, .cache, dist, target, build, out, __pycache__, .pytest_cache, *.egg-info, generated output (e.g. src/generated/, .prisma/). Add these to exclude. Do not add node_modules — it is already excluded by default.


Phase 2 — The Weighting Engine Rules

Apply these weights when architecting scope patterns. Higher weight wins ties.

WeightBoundary TypeExample Pattern
10Deepest semantic boundarysrc/modules/([^/]+)/.*, packages/([^/]+)/.*, crates/([^/]+)/.*
8Broad organizational folderssrc/([^/]+)/.*, lib/([^/]+)/.*
7Universal Semantic Scopespackage.jsondeps, .gitignoregit, README.mddocs
5Transversal layersui/.*ui, db/.*db, prisma/.*db
5Documentation and Mediaassets/.*, docs/.*, images/.*
3Tooling and Infrastructure.cursor/.*, .github/.*, scripts/.*, config/.*config

The primary boundary gets 10. Fallback patterns (catch-all under core) get 6–8. Universal root files (package.json, gitignore, readme) get 7 to ensure they are more specific than the root catch-all but subservient to deep domain logic. Cross-cutting concerns (UI, DB, API) and auxiliary docs/media get 5. Tooling, scripts, and config get 3.

Transversal layers stay at 5 so the primary boundary (10) overrides when a file lives in both. Example: src/features/auth/ui/button.tsx should scope to auth, not ui. The domain wins.


Phase 3 — Synthesis Logic

Generate regex patterns using ([^/]+) to dynamically capture directory names as scopes. The scope field is "$1" when the pattern captures a segment, or a literal string (e.g. "db", "ui") when the layer is fixed.

Universal Semantic Patterns should be proposed for common root files:

  • package.json and lockfiles → deps
  • .gitignore, .cursorignore, .dockerignoregit
  • README.md, LICENSE, CONTRIBUTING.mddocs
  • .env.example, .env.localenv
  • .convitrc.jsonconvit

User-specific patterns go at the top of the scopePatterns array. They override built-in defaults. If the user has custom domains or conventions, place those first.

Always include a fallback pattern at the end unless the user opts out:

{ "pattern": "src/([^/]+)/.*", "scope": "$1", "weight": 6 }

Adjust the fallback to match the core (e.g. lib/([^/]+)/.* if the core is lib/).


Phase 4 — Ask

Present findings and ask the user to confirm or adjust. Only ask about signals that actually fired. Group patterns by hierarchy so the user sees how the project is being analyzed.

Scope pattern prompts

Group proposed scope patterns under three headers:

Primary Boundary (Weight 8–10)

"Proposed scope pattern: {"pattern": "src/features/([^/]+)/.*", "scope": "$1", "weight": 10} Use this? (yes / adjust / skip)"

Transversal Layers (Weight 5)

"Proposed scope pattern: {"pattern": "ui/.*", "scope": "ui", "weight": 5} Use this? (yes / adjust / skip)"

**Auxiliary Support (Weight 3)"

"Proposed scope pattern: {"pattern": ".cursor/.*", "scope": "cursor", "weight": 3} Use this? (yes / adjust / skip)"

For each pattern, show the proposal and ask. If the user wants to adjust, ask for the corrected pattern, scope, or weight.

Exclude path prompts

For each detected build/generated output:

"Found dist/. Add to exclude list? (yes / skip)"

Rules prompts

Ask these three regardless of signals:

  1. "Max subject line length? (default: 50, range: 40–72)"
  2. "Min bullet points in commit body? (default: 1, range: 0–5)"
  3. "Max bullet line length? (default: 72, range: 60–100)"

If the user accepts the default, omit that key from rules. convit uses defaults automatically — only write keys the user explicitly customized.


Phase 5 — Write

Produce .convitrc.json at the project root with only the keys that have non-default or user-confirmed values. Shape must match exactly:

{
  "rules": {
    "maxSubjectLength": 50,
    "maxBulletLength": 72,
    "minBullets": 1
  },
  "scopePatterns": [
    { "pattern": "src/features/([^/]+)/.*", "scope": "$1", "weight": 10 },
    { "pattern": "src/([^/]+)/.*", "scope": "$1", "weight": 6 }
  ],
  "exclude": ["src/generated/prisma"]
}

Rules:

  • temperature is always omitted unless the user explicitly requests it (0.2 is the default and rarely needs changing)
  • Empty arrays ([]) should be omitted entirely
  • rules should be omitted entirely if no rule was customized
  • Never add a provider, apiKey, baseUrl, or model key

After writing, print a summary of what was configured. Offer to run the env setup script, or remind the user to add these to .env or .env.local:

Optional: Run the env setup script to append convit vars if missing.

Before running the script, tell the user explicitly:

I will run the ensure-convit-env.mjs script. It reads your .env or .env.local to check which CONVIT_* var names exist (by name only). It does not read, store, or transmit any values — no keys, no URLs, no secrets. If vars are missing, it appends placeholder lines to the file. The script output may mention local vs cloud (inferred from URL pattern) but never prints the actual URL or any credentials. You can review the script source before I run it.

Only run the script after the user has seen this disclosure and has not objected.

node .agents/skills/convit-setup/scripts/ensure-convit-env.mjs [path-to-project-root]

From project root, omit the path. The script checks .env.local first, then .env, and appends a dev-only block (with a box comment) that these vars should not be committed or uploaded. If the skill is installed globally, use the path to the skill's scripts/ folder.

Or add manually:

# Base URL of the OpenAI-compatible API — used for all LLM requests
CONVIT_URL="https://api.openai.com/v1"
# CONVIT_URL="http://localhost:1234/v1"   # LM Studio
# CONVIT_URL="http://localhost:11434/v1"  # Ollama

# API key — required for cloud providers (OpenAI, Anthropic). Omit for local models
CONVIT_KEY="sk-..."

# Model ID — which model to call. Omit to auto-detect from LM Studio
CONVIT_MODEL="gpt-4o-mini"
# CONVIT_MODEL="llama-3.2-3b-instruct"  # local

# Cost per 1M input tokens (USD) — enables cost display in terminal
# CONVIT_INPUT_COST="0.15"

# Cost per 1M output tokens (USD) — enables cost display in terminal
# CONVIT_OUTPUT_COST="0.60"

# Request timeout in ms — how long to wait for LLM response before aborting
# CONVIT_TIMEOUT="60000"

Example

Input: Next.js app with src/features/auth/, src/features/dashboard/, src/components/ui/. Primary boundary: src/. Depth is 3 levels. Noise: .next/.

Output:

{
  "scopePatterns": [
    { "pattern": "src/features/([^/]+)/.*", "scope": "$1", "weight": 10 },
    { "pattern": "src/components/ui/.*", "scope": "ui", "weight": 5 },
    { "pattern": "src/([^/]+)/.*", "scope": "$1", "weight": 6 }
  ],
  "exclude": [".next/"]
}

Primary boundary is src/features/([^/]+). Transversal layer components/ui/ gets fixed scope ui. Fallback src/([^/]+) catches files outside features. Noise excluded.

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

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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

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按下载量换算26

Claude

28.81%
按下载量换算19

Cursor

17.47%
按下载量换算12

Gemini CLI

9.24%
按下载量换算6

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