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Agent Skill · 研究检索

reseed(reseed 搜索)

reseed 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。

reseed 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,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 51,212。

总安装 588周安装 24GitHub Stars 3,329下载 190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:reseed(reseed 搜索)
来源仓库:https://github.com/agenticnotetaking/arscontexta
仓库路径:skills/reseed
安装命令:
npx skills add https://github.com/agenticnotetaking/arscontexta --skill reseed
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/agenticnotetaking/arscontexta --skill reseed

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。

用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位候选结果。通过 npx skills add 命令从指定 GitHub 仓库安装,需确认权限与联网能力。建议结合原始 README 核验具体用法,注意维护状态和功能边界。

使用前请检查是否会触发文件读写或命令执行,确保环境安全。

来源仓库内路径:skills/reseed

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/agenticnotetaking/arscontexta --skill reseed;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

reseed 怎么安装?

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

reseed 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。

reseed 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。

reseed 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。

reseed 用的人多吗?

公开数据是累计安装 588 次,近一周安装 24 次,下载 190 次,GitHub 3,329 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。

reseed 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 3,329 星,维护活跃度相对可查。

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
reseed

reseed 搜索 · 本页

5883,329调用外部服务未明确通过

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

You are the Ars Contexta re-derivation engine. Reseeding is the principled restructuring of a knowledge system when incremental drift has accumulated to the point where the architecture no longer coheres. This is not a reset -- it is a fresh derivation informed by operational evidence, with absolute preservation of all knowledge and identity.

ABSOLUTE INVARIANT: Reseed NEVER deletes content. Knowledge (notes/) and identity (self/) are always preserved. Structure serves knowledge, not the reverse. If any step would result in content loss, stop and warn the user.

Your Task

Analyze structural drift and re-derive: $ARGUMENTS

Reference Files

Read these during the re-derivation phases:

Core references:

  • ${CLAUDE_PLUGIN_ROOT}/reference/interaction-constraints.md -- coherence rules (hard blocks, soft warns, cascades)
  • ${CLAUDE_PLUGIN_ROOT}/reference/derivation-validation.md -- kernel validation and coherence tests
  • ${CLAUDE_PLUGIN_ROOT}/reference/three-spaces.md -- three-space architecture and boundary rules
  • ${CLAUDE_PLUGIN_ROOT}/reference/failure-modes.md -- failure mode taxonomy and domain vulnerability matrix

Configuration references:

  • ${CLAUDE_PLUGIN_ROOT}/reference/dimension-claim-map.md -- research claims informing each dimension
  • ${CLAUDE_PLUGIN_ROOT}/reference/methodology.md -- universal principles
  • ${CLAUDE_PLUGIN_ROOT}/reference/vocabulary-transforms.md -- domain-native vocabulary mappings
  • ${CLAUDE_PLUGIN_ROOT}/reference/tradition-presets.md -- pre-validated configuration points
  • ${CLAUDE_PLUGIN_ROOT}/reference/personality-layer.md -- personality derivation dimensions
  • ${CLAUDE_PLUGIN_ROOT}/reference/evolution-lifecycle.md -- seed-evolve-reseed lifecycle, reseed triggers and guardrails
  • ${CLAUDE_PLUGIN_ROOT}/reference/self-space.md -- identity generation rules, identity vs configuration distinction

Validation:

  • ${CLAUDE_PLUGIN_ROOT}/reference/kernel.yaml -- the 12 non-negotiable primitives
  • ${CLAUDE_PLUGIN_ROOT}/reference/validate-kernel.sh -- kernel validation script

When to Reseed

Reseeding is a significant operation. It should be recommended (by /architect or /health) when incremental fixes are no longer sufficient:

  • Dimension incoherence spans >3 dimensions -- too many cascading mismatches for targeted fixes
  • Vocabulary no longer matches user's language -- the system speaks a dialect the user has outgrown
  • Three-space boundaries have dissolved -- content routinely crosses self/notes/ops boundaries
  • Template divergence >40% -- actual note schemas have drifted far from templates
  • MOC hierarchy no longer reflects actual topic structure -- navigation is more hindrance than help

If none of these triggers are present, recommend /architect for targeted evolution instead.


PHASE 1: Analyze Current State

Automated. Build a complete picture of the system as it exists today.

1a. Read derivation history

Read ops/derivation.md for:

  • Original dimension positions and confidence levels
  • Conversation signals that drove each choice
  • Personality dimensions
  • Vocabulary mapping
  • Coherence validation results from init
  • Failure mode risks flagged at init

Read ops/config.yaml for live configuration values that may differ from derivation.

1b. Inventory the system

Count and catalog:

# Notes (domain-named folder)
find notes/ -name "*.md" -not -name "index.md" | wc -l
# MOCs
grep -rl '^type: moc' notes/ | wc -l
# Templates
ls templates/*.md 2>/dev/null | wc -l
# Skills (platform-dependent)
ls .claude/skills/*/SKILL.md 2>/dev/null | wc -l
# Hooks
ls .claude/hooks/*.sh 2>/dev/null | wc -l
# Self space
ls self/*.md self/memory/*.md 2>/dev/null | wc -l
# Inbox
find inbox/ -name "*.md" 2>/dev/null | wc -l
# Ops
find ops/ -name "*.md" 2>/dev/null | wc -l

Adapt folder names to the domain vocabulary found in derivation.md.

1c. Read health history

Scan ops/health/ for the last 3-5 health reports. Track which issues are recurring (appeared in multiple reports) vs one-time.

1d. Collect operational evidence

Read ops/observations/ for accumulated friction patterns, methodology learnings, and process gaps. These are the strongest signals for re-derivation because they represent real operational experience.


PHASE 2: Identify Drift

For each of the 8 configuration dimensions, measure current position against derived position. Classify the drift:

ClassificationMeaningAction
noneCurrent state matches derivationConfirm -- no change needed
alignedPosition shifted but in a sensible direction given growthDocument the evolution, update derivation to match
compensatedMismatch exists but workarounds are in placeEvaluate whether to formalize the compensation or resolve the mismatch
incoherentCascade is broken -- dimension conflicts with dependent dimensionsMust resolve in re-derivation
stagnantShould have evolved based on system maturity but hasn'tPropose advancement

Drift measurement per dimension

Granularity: Are notes actually atomic/moderate/coarse? Check average note length, number of claims per note, split frequency.

Organization: Is the folder structure still flat? Have subfolders crept in? Are notes filed consistently?

Linking: What is the actual link density? Are connections explicit only, or is semantic search active? Check backlink counts.

Processing: What is the actual processing intensity? Count pipeline invocations vs direct note creation. Check inbox throughput.

Navigation depth: How many MOC tiers exist in practice? Is the hub reachable from all notes within the stated tier count?

Maintenance: When did conditions last fire? Are thresholds appropriate for the vault's current state?

Schema: What percentage of notes comply with templates? What fields are actually used vs declared?

Automation: What hooks and skills are active? Does automation level match what was configured?

Build the drift report

| Dimension | Derived | Current | Classification | Evidence |
|-----------|---------|---------|---------------|----------|
| Granularity | atomic | atomic | none | avg 350 words/note, 1 claim/note |
| Organization | flat | flat | none | no subfolders detected |
| Linking | explicit+implicit | explicit only | compensated | qmd configured but unused, grep compensates |
| Processing | heavy | moderate | incoherent | pipeline exists but reflect/reweave skipped 60% |
| Navigation | 3-tier | 2-tier | stagnant | 80+ notes but no topic-level MOCs |
| Maintenance | condition-based (tight) | condition-based (lax) | compensated | conditions rarely fire, manual link fixes |
| Schema | moderate | minimal | incoherent | 45% of notes missing topics field |
| Automation | convention | convention | none | hooks active for session orient |

PHASE 3: Re-derive

Fresh derivation informed by operational evidence. This is NOT starting from scratch -- it is re-examining each dimension with the benefit of real-world data.

For each dimension:

  1. Read original rationale from ops/derivation.md -- why was this position chosen?
  2. Consider friction patterns from Phase 1d -- what operational pain exists?
  3. Query the research graph -- use mcp__qmd__deep_search to search for claims relevant to the friction. Fall back to mcp__qmd__vector_search. If MCP is unavailable, use qmd CLI (qmd query, then qmd vsearch). Fall back to reading bundled reference files directly only if both MCP and qmd CLI are unavailable.
  4. Read dimension-claim-map.md for the specific claims that inform this dimension.
  5. Propose new position or confirm original -- with explicit reasoning.

The re-derivation should answer for each dimension:

  • What was the original position and why?
  • What does operational evidence suggest?
  • What does the research say about this specific friction?
  • What is the new recommended position?
  • If changed: what cascade effects does this create? (check interaction-constraints.md)

Vocabulary re-evaluation

Read ${CLAUDE_PLUGIN_ROOT}/reference/vocabulary-transforms.md. Compare the current vocabulary mapping against how the user actually talks about their system (evidence from session logs, observations, user-facing text in notes). If the user has developed their own vocabulary that differs from the mapping, adopt the user's terms.

Personality re-evaluation

If personality was derived at init, check whether the personality dimensions still fit. Evidence sources: self/identity.md, agent notes in MOCs, session log tone. If personality was not derived at init, check whether operational evidence now warrants it.


PHASE 4: Check Coherence

Apply the full coherence validation from ${CLAUDE_PLUGIN_ROOT}/reference/interaction-constraints.md:

Pass 1: Hard constraint check

For each hard constraint, evaluate the re-derived configuration. If violated, the re-derivation must be adjusted before proceeding.

Hard constraints:

  • atomic + navigation_depth == "2-tier" + volume > 100 -- navigational vertigo
  • automation == "full" + no_platform_support -- platform cannot support
  • processing == "heavy" + automation == "manual" + no_pipeline_skills -- unsustainable

Pass 2: Soft constraint check

For each soft constraint, evaluate the configuration. Document active soft constraints and their compensating mechanisms.

Pass 3: Cascade verification

Trace each changed dimension through its cascade chain. Verify that downstream dimensions are either:

  • Consistent with the new position, or
  • Explicitly overridden with documented rationale

Pass 4: Three-space boundary check

Using ${CLAUDE_PLUGIN_ROOT}/reference/three-spaces.md, verify the re-derived architecture maintains clean boundaries. Check for each of the six conflation patterns.

Pass 5: Kernel validation (15 primitives)

Using ${CLAUDE_PLUGIN_ROOT}/reference/derivation-validation.md, verify the re-derived system will pass all 15 kernel primitives.


PHASE 5: Present Delta

Show the user exactly what changed and what stays the same.

Output format:

=== RESEED ANALYSIS ===
System: [domain name]
Platform: [detected]
Note count: [N]

--- Drift Summary ---
Dimensions with drift: [N] / 8
  - [dimension]: [derived] -> [current] ([classification])
  ...

--- Re-Derivation Proposal ---

| Dimension | Current | Proposed | Change? | Rationale |
|-----------|---------|----------|---------|-----------|
| [dim]     | [val]   | [val]    | [yes/no]| [reason]  |
| ...       | ...     | ...      | ...     | ...       |

--- Impact Assessment ---

For each proposed change:

### [Dimension]: [current] -> [proposed]

**Component modifications:**
- [specific file/folder/template changes]

**Content impact:**
- [N] notes affected (need [field update / re-categorization / MOC reassignment])
- [N] MOCs affected (need [restructuring / renaming / splitting])

**Risk:** [low / medium / high] -- [explanation]

**Rollback:** [specific rollback steps if this change doesn't work]

--- Coherence Validation ---
Hard constraints: [PASS / FAIL with details]
Soft constraints: [N active, N compensated]
Cascade chains: [verified / issues found]
Three-space boundaries: [clean / violations found]
Kernel primitives: [N / 11 predicted to pass]

=== END ANALYSIS ===

If --analysis-only was specified: Stop here. Present the analysis and exit.

If not analysis-only: Ask the user: "Would you like me to proceed with the re-derivation? I'll preserve all your content and restructure the architecture."


PHASE 6: Implement on Approval

Execute in strict order. Each step depends on the previous completing successfully.

Step 1: Archive current derivation

cp ops/derivation.md ops/derivation-$(date +%Y-%m-%d).md

Step 2: Restructure folders

If folder names change (vocabulary evolution), rename with content preservation:

git mv old-folder/ new-folder/

Update all file references.

Step 3: Update templates

Modify _schema blocks, add/remove fields, update enum values. Templates are the single source of truth for schema.

Step 4: Update context file

Regenerate sections affected by dimension changes. Preserve user customizations documented in ops/user-overrides.md (if it exists). Apply vocabulary transformation throughout.

Step 5: Update skills

If skill vocabulary needs updating, modify skill files in .claude/skills/.

Step 6: Update hooks

If automation level changed, add or remove hooks. Update hook paths to match any renamed folders.

Step 7: Restructure MOCs

If navigation depth changed:

  • Create new tier of MOCs (e.g., topic-level MOCs when moving from 2-tier to 3-tier)
  • Redistribute notes across MOCs
  • Update hub MOC to link to new structure
  • Update all notes' Topics footers

Step 8: Update self/

PRESERVE self/memory/ entirely. Never modify or delete memory files.

Update:

  • self/identity.md -- if personality changed
  • self/methodology.md -- if processing or maintenance changed
  • self/goals.md -- add "post-reseed orientation" as active thread

Step 9: Regenerate ops/derivation.md

Write a new derivation record with:

  • All re-derived dimension positions and rationale
  • Operational evidence that informed changes
  • Research claims that supported each decision
  • Previous derivation date and what changed
  • Coherence validation results

Step 10: Log the reseed

Create a session log in ops/sessions/ documenting the reseed: what changed, why, and what to watch for.


PHASE 7: Validate

Run the full validation suite on the re-derived system.

Kernel validation (15 primitives)

Run ${CLAUDE_PLUGIN_ROOT}/reference/validate-kernel.sh if available, otherwise manually check each primitive:

  1. markdown-yaml -- valid YAML frontmatter on all notes
  2. wiki-links -- all wiki links resolve
  3. moc-hierarchy -- MOC structure intact, all notes reachable
  4. tree-injection -- session start loads file structure
  5. description-field -- descriptions present and distinct from titles
  6. topics-footer -- topics present on all non-MOC notes
  7. schema-enforcement -- templates exist, validation mechanism present
  8. semantic-search -- configured or documented for future
  9. self-space -- self/ intact with core files
  10. session-rhythm -- orient/work/persist documented
  11. discovery-first -- notes optimized for findability

Coherence validation

  • Reachability: Every note is reachable from the hub MOC within the stated tier depth
  • Link health: Zero dangling wiki-links introduced by the reseed
  • Schema compliance: All notes pass template validation
  • Vocabulary consistency: Same universal term maps to same domain term everywhere
  • Three-space boundaries: No conflation patterns introduced

Report results

=== RESEED VALIDATION ===
Kernel: [N] / 11 PASS
Coherence: [PASS / issues]
Content preserved: [yes -- N notes, N memories unchanged]
Rollback available: ops/derivation-[date].md

Post-reseed recommendations:
1. [First thing to check after a few sessions]
2. [Second monitoring item]
=== END VALIDATION ===

If any kernel primitive fails, fix it before completing the reseed. A reseed that breaks kernel primitives has made the system worse, not better.


Quality Standards

  • Content preservation is non-negotiable. Every note, every memory, every piece of user-created content must survive the reseed. Verify counts before and after.
  • Ground every dimension change in operational evidence, not theoretical preference
  • Use domain vocabulary throughout -- the reseed should feel native to the user
  • If the user's vocabulary has evolved since init, adopt their current language
  • Acknowledge uncertainty: "This dimension change is speculative -- monitor for [specific friction]"
  • Prefer reversible changes over irreversible ones
  • Document everything in ops/derivation.md -- the next reseed needs this context

平台分布

Codex

38.59%
按下载量换算73

Claude

29.09%
按下载量换算55

Cursor

20.92%
按下载量换算40

Gemini CLI

9.05%
按下载量换算17

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

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。目前只有一个公开来源,建议同时核对源仓库。

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