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Agent Skill · 研究检索

trace(trace 搜索)

trace 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。

trace 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 56,650。

总安装 447周安装 19GitHub Stars 49下载 157核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:trace(trace 搜索)
来源仓库:https://github.com/soul-brews-studio/arra-oracle-skills
仓库路径:skills/trace
安装命令:
npx skills add https://github.com/soul-brews-studio/arra-oracle-skills --skill trace
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/soul-brews-studio/arra-oracle-skills --skill trace

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

多层级信息检索系统,支持快速到深度搜索模式。覆盖网页、代码与知识库多维数据源。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。输出置信度评分与摩擦系数供结果评估。部分模式依赖联网,可能存在访问限制。建议优先使用低摩擦模式提升效率。

trace 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/trace

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/soul-brews-studio/arra-oracle-skills --skill t…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

trace 怎么安装?

在终端执行 npx skills add https://github.com/soul-brews-studio/arra-oracle-skills --skill trace。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

trace 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

trace 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

trace 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

trace 用的人多吗?

公开数据是累计安装 447 次,近一周安装 19 次,下载 157 次,GitHub 49 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

trace 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
trace

trace 搜索 · 本页

44749调用外部服务未明确未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

/trace - Unified Discovery System

Find + Measure + Log + Distill

Usage

/trace [query]                    # Current repo (default --smart)
/trace [query] --oracle           # Oracle only (fastest)
/trace [query] --deep             # Wave execution (thorough)
/trace [query] --deep --dig       # Combo: trace deep + dig session mining (parallel)
/trace [query] --repo [path]      # Search specific local repo
/trace [query] --repo [url]       # Clone to ghq, then search
/dig alone mines sessions. --dig flag on /trace runs both together.

Directory Structure

ψ/memory/traces/
└── YYYY-MM-DD/              # Date folder
    └── HHMM_[query-slug].md # Time-prefixed trace log

Trace logs are committed - they become Oracle memory for future searches.


Step 0: Timestamp + Calculate Paths

date "+🕐 %H:%M %Z (%A %d %B %Y)"
ROOT="$(pwd)"
TODAY=$(date +%Y-%m-%d)
TIME=$(date +%H%M)

Step 1: Detect Target Repo

Default: Current repo

TARGET_REPO="$ROOT"
TARGET_NAME="$(basename $ROOT)"

With --repo [path]: Local path

TARGET_REPO="[path]"
TARGET_NAME="$(basename [path])"

With --repo [url]: Clone to ghq first

URL="[url]"
ghq get -u "$URL"
GHQ_ROOT=$(ghq root)
OWNER=$(echo "$URL" | sed -E 's|.*github.com/([^/]+)/.*|\1|')
REPO=$(echo "$URL" | sed -E 's|.*/([^/]+)(\.git)?$|\1|')
TARGET_REPO="$GHQ_ROOT/github.com/$OWNER/$REPO"
TARGET_NAME="$OWNER/$REPO"
echo "✓ Cloned to ghq: $TARGET_REPO"

Note: /trace only clones to ghq. Use /learn to create docs in ψ/learn/.


Step 2: Create Trace Log Directory

mkdir -p "$ROOT/ψ/memory/traces/$TODAY"
TRACE_FILE="$ROOT/ψ/memory/traces/$TODAY/${TIME}_[query-slug].md"

Mode 1: --oracle (Oracle Only)

Fastest. Just Oracle MCP, no subagents.

arra_search("[query]", limit=15)

Display results and done. Even if empty.


Mode 2: --smart (Default)

Oracle first → auto-escalate if results < 3

Step 1: Query Oracle first

arra_search("[query]", limit=10)

Step 2: Check result count

  • If Oracle results >= 3 → Display and done
  • If Oracle results < 3 → Auto-escalate to --deep mode

Mode 3: --deep (Wave Execution)

Two waves of parallel search. Each wave has fresh context (no rot).

Wave 1 — Fast surface search (run in parallel)

Agent A: Current/Target Repo Files

You are searching for: [query]
TARGET REPO: [TARGET_REPO]

Search for:
- Files matching query (names, paths)
- Code/docs containing query
- Config files mentioning query

Return findings as text. Main agent compiles.

Agent B: Oracle Memory

You are searching for: [query]
PSI DIR: [ROOT]/ψ/

Search ψ/memory/ for:
- Learnings mentioning query
- Retrospectives mentioning query
- Previous trace logs for same query

Return findings as text. Main agent compiles.

After Wave 1: check if answer is sufficient.

  • Sufficient (clear answer found) → skip Wave 2, go to Step 3
  • Insufficient (< 3 results or answer unclear) → run Wave 2

Wave 2 — Deep search (run in parallel, only if Wave 1 insufficient)

Agent C: Git History

You are searching for: [query]
TARGET REPO: [TARGET_REPO]

Search git history:
- Commits mentioning query
- Files created/deleted matching query
- Branch names matching query
Run: git log --all --oneline --grep="[query]"

Return findings as text. Main agent compiles.

Agent D: Cross-Repo (ghq + ~/Code)

You are searching for: [query]

Search other repos:
- find $(ghq root) -maxdepth 3 -name "*[query]*" 2>/dev/null | head -20
- grep -r "[query]" ~/Code --include="*.md" -l 2>/dev/null | head -10

Return findings as text. Main agent compiles.

Agent E: GitHub Issues/PRs

You are searching for: [query]
TARGET REPO: [TARGET_REPO]

If repo has GitHub remote, run:
- gh issue list --search "[query]" --limit 10
- gh pr list --search "[query]" --limit 10

Return findings as text. Main agent compiles.

After both waves, main agent compiles all results → Step 3.


Mode 4: --deep --dig (Combo)

Trace deep + session mining in parallel. Runs both /trace --deep and /dig simultaneously, then merges results into one output.

How it works

Launch trace Wave 1 agents AND the dig session miner at the same time:

In parallel:

  1. Trace agents (Wave 1: Agent A + Agent B) — same as --deep mode above
  2. Dig agent — mines session history for the query:
You are mining session history for: [query]

Run the dig script to get all sessions:
ENCODED_PWD=$(pwd | sed 's|^/|-|; s|[/.]|-|g')
PROJECT_BASE=$(ls -d "$HOME/.claude/projects/${ENCODED_PWD}" 2>/dev/null | head -1)
export PROJECT_DIRS="$PROJECT_BASE"
for wt in "${PROJECT_BASE}"-wt*; do [ -d "$wt" ] && export PROJECT_DIRS="$PROJECT_DIRS:$wt"; done

python3 ~/.claude/skills/dig/scripts/dig.py 0

Then search the session data for mentions of: [query]
Look for:
- Sessions where this topic was worked on
- Timeline of when it was touched
- Which repos it appeared in
- How much time was spent

Return findings as text. Max 500 words.

After Wave 1 + Dig complete:

  • Check trace results — if insufficient, run Wave 2 (same as --deep)
  • Merge all results: trace findings + session history

Combined Output

The trace log includes an extra section:

## Session History (from /dig)
[Sessions where query appeared, timeline, time spent]

This goes between "Oracle Memory" and "Friction Analysis" in the trace log.

When to use

  • "When did we work on X and where is it now?" — both questions answered
  • Investigating a topic across code AND session history
  • Building a complete picture: what exists (trace) + what happened (dig)

Step 3: Calculate Friction Score (Volt-inspired)

After search completes, calculate friction_score using the v2 formula:

friction_score = S + C_offset    (clamped to [0.0, 1.0])

S — Source Score (highest-tier source with relevant result):

Where foundSMeaning
Oracle1.0Frictionless — well-indexed, visible
Repo files0.7Present but not indexed
Git history0.5Buried — existed, hard to surface
Cross-repo0.3Hidden — lives elsewhere
Not found0.0Invisible — doesn't exist yet

C_offset — Completeness (from goal-backward check in Step 4):

ConfidenceC_offset
high+0.00
medium−0.10
low−0.20

Score table:

SituationScore
Oracle + high1.0
Oracle + medium0.9
Files + high0.7
Files + medium0.6
Git + high0.5
Git + medium0.4
Cross-repo + high0.3
Not found0.0

Rule: S = highest-tier source that contained relevant result. Not found → 0.0 regardless of C_offset.

Also calculate coverage: how many of 5 dimensions were searched.

  • oracle, files, git, cross-repo, github — list which were checked.

Step 4: Goal-Backward Check (GSD verifier-inspired)

Before writing the trace log, ask:

"Did this trace actually answer the original question?"
  • Yes → confidence: high
  • Partial (found related but not exact) → confidence: medium — note what's missing
  • No → confidence: low — note what next step is needed

This prevents "found something → assume done". Omar stops here. Never crosses into deciding for jeera-p.


Step 5: Write Trace Log

---
query: "[query]"
target: "[TARGET_NAME]"
mode: [oracle|smart|deep]
timestamp: YYYY-MM-DD HH:MM
friction_score: [0.0–1.0]
coverage: [oracle, files, git, cross-repo, github]
confidence: [high|medium|low]
---

# Trace: [query]

**Target**: [TARGET_NAME]
**Mode**: [mode] | **Friction**: [score] | **Confidence**: [level]
**Time**: [timestamp]

## Oracle Results
[list results or "None"]

## Files Found
[list files or "None"]

## Git History
[list commits or "None"]

## GitHub Issues/PRs
[list or "None"]

## Cross-Repo Matches
[list or "None"]

## Oracle Memory
[list or "None"]

## Friction Analysis
**Score**: [0.0–1.0] — [interpretation]
**Coverage**: [dimensions searched]
**Goal check**: [Did this answer the question? What's missing?]

## Summary
[Key findings, next steps]

Step 6: Log to Oracle MCP

arra_trace({
  query: "[query]",
  project: "[TARGET_NAME]",
  foundFiles: [...],
  foundCommits: [...],
  foundIssues: [...],
  friction_score: [0.0–1.0],
  confidence: "[high|medium|low]"
})

Friction Score Reference

friction_score = S + C_offset    (clamped to [0.0, 1.0])

1.0 ████████████  Frictionless   — Oracle + high confidence
0.9 ███████████░  Near-perfect   — Oracle + medium confidence
0.7 ████████░░░░  Visible        — Files + high confidence
0.6 ███████░░░░░  Slightly buried — Files + medium confidence
0.5 ██████░░░░░░  Buried         — Git + high confidence
0.4 █████░░░░░░░  Buried-medium  — Git + medium confidence
0.3 ████░░░░░░░░  Hidden         — Cross-repo + high confidence
0.2 ███░░░░░░░░░  Very hidden    — Cross-repo + medium confidence
0.0 ░░░░░░░░░░░░  Invisible      — Not found anywhere

Actionable zones:

RangeAction
0.9–1.0No action needed
0.6–0.89Consider oracle_learn indexing
0.4–0.59Distill + index this session
0.1–0.39Cross-repo consolidation needed
0.0Create / document

Low score = signal: this topic needs better indexing, documentation, or creation. Omar surfaces this. jeera-p decides what to do about it.


Philosophy

Trace → Measure → Distill → Awakening

The Seeking Signal

User ActionMeaningAI Response
/trace XFirst search--smart (Oracle first)
/trace X againStill seekingOracle knows
/trace X --deepReally need itWave execution
Found!RESONANCELog + score

Skill Separation

SkillPurposeWrites to
/traceFind + measureψ/memory/traces/ (logs)
/trace --digFind + measure + mine sessionsψ/memory/traces/ (logs)
/digMine sessions (standalone)Screen only (read-only)
/learnStudy reposψ/learn/ (docs)
/projectDevelop reposψ/incubate/ or active/

Workflow: /trace finds + measures → /learn studies → /project develops Combo: /trace --deep --dig = find + mine in one shot


Summary

ModeSpeedScopeWaves
--oracleFastOracle only—
--smartMediumOracle → maybe deepAuto
--deepThoroughWave 1 + Wave 2 if needed2
--deep --digThorough+Deep + session mining (parallel)2 + dig
Output fieldDescription
friction_score0.0–1.0 how hard to find
coveragedimensions searched
confidencedid trace answer the question

ARGUMENTS: $ARGUMENTS

平台分布

Codex

40%
按下载量换算63

Claude

29.63%
按下载量换算47

Cursor

18.55%
按下载量换算29

Gemini CLI

9.57%
按下载量换算15

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

未通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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