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tracetrace 搜索

Agent Skill

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。

总安装

679

周安装

28

GitHub Stars

53

下载量

222
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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:trace(trace 搜索)
来源仓库:https://github.com/soul-brews-studio/oracle-skills-cli
仓库路径:skills/trace
安装命令:
npx skills add https://github.com/soul-brews-studio/oracle-skills-cli --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/oracle-skills-cli --skill trace

简介

命令行版 Oracle 技能套件中的通用搜索模块。

  • 提供波浪式递进检索与并行挖掘能力。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。
  • 支持自定义参数调节搜索广度与深度。
  • 高深度模式可能触发较长响应时间。trace 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 建议结合具体问题类型选择合适模式。

SKILL.md

/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

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

35.39%
按下载量换算79

Claude

31.51%
按下载量换算70

Cursor

20.7%
按下载量换算46

Gemini CLI

10.26%
按下载量换算23

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

可疑

权限和风险

external-service

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 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

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