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Agent Skill · 研究检索

reduce(reduce 搜索)

reduce 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。

reduce 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,权限为需要联网;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 50,810。

总安装 606周安装 25GitHub Stars 53下载 198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:reduce(reduce 搜索)
来源仓库:https://github.com/tkersey/dotfiles
仓库路径:skills/reduce
安装命令:
npx skills add https://github.com/tkersey/dotfiles --skill reduce
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/tkersey/dotfiles --skill reduce

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。

用于在特定上下文中查找和筛选相关信息。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。适用于需要根据关键词或来源线索定位内容的场景。建议结合原始文档进一步了解具体功能实现。使用前请评估是否会触发网络请求或文件操作。

reduce 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/reduce

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/tkersey/dotfiles --skill reduce;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

    它需要需要联网,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

reduce 怎么安装?

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

reduce 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。

reduce 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

reduce 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。

reduce 用的人多吗?

公开数据是累计安装 606 次,近一周安装 25 次,下载 198 次,GitHub 53 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。

reduce 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。

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
reduce

reduce 搜索 · 本页

60653需要联网未明确通过

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

Reduce (De-abstraction for Agents)

Overview

Diagnose abstraction cost versus value and recommend lower-level primitives using a surgical, minimal-incision mindset.

Defaults:

  • Optimize for agent-editability (few layers, explicit config, deterministic commands).
  • Be aggressive: prefer primitives even if it increases short-term duplication or migration work.
  • Preserve observable behavior unless the user explicitly requests a semantic change.
  • Analysis/recommendations only; do not implement unless explicitly asked.

Double Diamond fit

Reduce is a Discover/Define-heavy skill that produces a concrete cut list and migration plan without writing code.

  • Discover: inventory the abstraction stack and locate indirection points.
  • Define: score each abstraction (agent-tax vs value) and choose keep/cut.
  • Develop: select the next-lower replacement rung and the smallest reversible migration.
  • Deliver: report an audit table + prioritized cut list + migration plan + minimal-incision patch suggestions.

Entry Criteria

Use this skill only when at least one condition is true:

  • Change latency is dominated by abstraction/tooling hops rather than local readability.
  • Behavior is controlled by framework hooks, plugins, codegen, or configuration indirection.
  • The target outcome is to remove or downgrade layers while preserving observable behavior.
  • The current interface is changing during interaction, but that evolution is hidden in ad-hoc runtime checks instead of explicit protocol/state boundaries.

Triage Gate

  • Prefer $reduce for architecture/tooling de-abstraction and dependency cuts.
  • Prefer $complexity-mitigator for local readability or control-flow simplification inside the current stack.
  • If both apply, run $reduce first to delete layers, then simplify the residue.
  • If interaction-dependent interfaces are core to the domain (session/capability/progressive protocol), reduce incidental wrappers first; do not flatten the protocol itself without proof.

Core Principles

  • Minimal incision, maximal simplification: target the smallest change that deletes the most indirection.
  • Agent-friendly primitives win: plain files, explicit config, simple CLIs, no hidden generators, no interactive prompts.
  • Prefer deletion over replacement when behavior is unused or redundant (prove unused via repo evidence).
  • Prefer one obvious path over flexible multiplexing (plugins, adapters, DI containers) unless value is proven.

Guardrails

  • Default to repo-local evidence; do not guess usage/value.
  • Do not recommend big-bang rewrites; require seams, phases, proof signals, and a rollback lever.
  • Do not propose breaking external surfaces without a compatibility wrapper or an explicit user ask.
  • Do not add tools/dependencies unless explicitly requested.
  • If implementation is requested, hand off to $tk.
  • Do not collapse an essential evolving interface into one global fixed interface unless the same observable protocol can be proven with deterministic tests.

What "Agent-editability" Means (practical)

An agent can:

  • Find where behavior lives (few hops; few conventions; minimal magic).
  • Change it with a small diff (no repo-wide cascading edits).
  • Run/verify quickly (one deterministic command; minimal environment).

Non-goals (unless explicitly requested):

  • Beautification refactors.
  • Re-platforming for its own sake.
  • Tuning performance/scale beyond what the existing contract requires.

Workflow

1. Discover: Map the abstraction stack

Inventory what makes change hard.

Required scan (repo-local):

  • Toolchain: build/test commands, task runners, codegen, formatter/linter, monorepo tooling.
  • Runtime: frameworks/meta frameworks, plugin systems, DI, reflection, middleware layers.
  • Data: ORMs/query builders/migrations, caches, queues, service mesh.
  • Frontend: SPA frameworks, bundlers, state libraries.
  • Infra/deploy: k8s, Helm, Terraform layers, bespoke pipelines.

Evidence collection defaults:

  • Prefer direct evidence: package.json scripts, Makefile/justfile, CI config, Dockerfile, deploy manifests.
  • Trace one real request path: input -> validation -> core rule -> persistence -> output.
  • Note every indirection point (codegen boundary, framework hook, config indirection, adapter layers).
  • If interface evolution is suspected, trace at least 2-3 interaction paths and record how the allowed operation set changes after each response/event.

2. Define: Decide whether abstraction cost is too high

Classify each abstraction as: keep | wrap | slice | replace | delete.

Cost signals (agent-tax):

  • Hidden steps: codegen, implicit conventions, runtime magic, reflection, decorators.
  • Indirection: behavior lives in hooks/middleware/config rather than code you can edit.
  • Tool weight: slow installs/builds/tests; large dependency graph; multi-tool orchestration.
  • Non-determinism: environment-sensitive behavior, flaky tests, network-required dev loops.
  • Churn risk: upgrades break frequently; generated diffs; brittle integrations.

Value signals (justification):

  • Hard constraints: compliance, multi-tenant isolation, true scale needs, audited change control.
  • Proven reuse: multiple independent consumers, stable shared domain rules.
  • Operational leverage: materially reduces oncall risk (with evidence).
  • Protocol realism: allowed operations genuinely change with interaction state (for example session phase, capability grants/revocations, adaptive UI state, progressive model stages).

Scoring rubric (make cut decisions mechanical):

  • Agent-tax score (T): 0-3

- 0 = negligible (direct code; obvious entrypoints; no extra tools) - 1 = mild (one extra layer; still searchable; deterministic commands) - 2 = high (codegen/indirection; slow loops; multi-tool orchestration) - 3 = severe (hidden magic; multiple generators; interactive/manual steps; flaky loops)

  • Value score (V): 0-3 (score 0 if you cannot cite evidence)

- 0 = unproven/optional (no tests/docs/callsites/ops evidence) - 1 = convenience (small DX win; could be replaced without changing the contract) - 2 = proven leverage (multiple consumers; reduces a bug-class; real ops benefit) - 3 = mandatory (compliance/legal requirement; SLO-critical; audited change control)

  • Delta (D) = T - V

Default verdict mapping (aggressive, but not reckless):

  • D >= 2: replace or delete (prefer delete if unused)
  • D == 1: slice now, replace next (or wrap to isolate first)
  • D == 0: wrap or slice (reduce surface area and remove sharp edges)
  • D == -1: keep, but simplify interfaces/entrypoints
  • D <= -2: keep

Definitions (verdicts):

  • keep: retain abstraction; reduce incidental friction (docs, scripts, entrypoints).
  • wrap: keep internally, but put a stable adapter in front to localize future removal.
  • slice: remove optional flexibility (plugins, multi-variant configs) to the one proven path.
  • replace: swap for a lower-level primitive with a migration seam.
  • delete: remove entirely.

Aggressive default policy:

  • If value is not proven (tests/docs/callsites/ops evidence), treat it as optional and recommend reduction.
  • If the abstraction exists "for flexibility" but only one variant is used, inline to the one variant.
  • If an abstraction exists to prevent duplication but adds hops/tooling, prefer duplication.

Evidence-confidence modifier (required before final verdict):

  • Confidence level (C): high | medium | low

- high: constraints/value are proven with repo-local evidence (tests/docs/callsites/ops config). - medium: partial evidence exists, but at least one critical assumption is inferred. - low: external obligations are plausible (compliance/SLO/audit/runtime policy), but not proven locally.

  • External-obligation guardrail:

- If C=low and verdict is replace or delete, cap to slice or wrap until one of these is true: - explicit user approval to change external obligations, or - evidence proving no such obligations exist.

  • Report confidence in the audit row notes for every replace/delete recommendation.

Interaction-evolution guardrail:

  • If evidence shows interface evolution is essential (state-dependent allowed operations), treat that protocol boundary as core domain structure.
  • In that case, prefer slice/wrap on incidental tooling around the protocol before attempting replace/delete of the protocol model itself.

3. Develop: Propose lower-level replacements

Pick the next lower rung on the replacement ladder (avoid big-bang rewrites).

Replacement ladder (common moves):

  • Meta framework -> framework -> stdlib primitives.
  • Codegen -> checked-in artifacts + small deterministic generator (or delete entirely).
  • ORM -> query builder -> parameterized SQL.
  • GraphQL -> REST/JSON -> RPC -> direct function calls (internal only).
  • Implicit runtime gating -> explicit state-indexed protocol map (operation set per state) -> optional typed client/session wrappers.
  • SPA -> server-rendered pages -> static HTML/CSS/JS.
  • k8s -> Docker Compose -> single process + systemd (or platform native).
  • Monorepo tool -> package-manager workspaces -> plain scripts.
  • DI container -> explicit constructors/wiring.
  • Custom DSL -> JSON/YAML/TOML with a small parser + schema.

Deconstruction patterns (agent-centric):

  • "Make the invisible visible": replace conventions with explicit entrypoints and wiring.
  • "Collapse configuration": many layers -> one canonical config file (with comments only if unavoidable).
  • "Delete the orchestrator": replace toolchains with a single scripts/dev and scripts/test (or make dev/test).
  • "Strangler seam": introduce a stable adapter boundary; implement the primitive behind it; migrate callers incrementally.
  • "State-index the protocol": move scattered runtime checks into one explicit transition table (state x operation -> next state).

4. Deliver: Report findings and recommendations

Default output must include:

  1. Abstraction audit (table).
  2. Cut list (prioritized).
  3. Migration plan (phased + proof signals + rollback).
  4. Patch suggestions (minimal incisions; file/command level; no implementation).

Output Profiles

Use one profile per response.

  • Full profile (default): use the complete format in Output Format (default full profile).
  • Quick profile (small audits): use only when both conditions hold:

- Scope is narrow (<=3 abstractions or one subsystem), and - The user asked for concise/minimal output.

Quick profile sections (exact order): 0) Scope + assumptions 1) Top Abstractions (mini-audit) 2) First Cut Recommendation 3) Minimal Migration + Rollback 4) Risks / unknowns

Quick profile minimums:

  • Still include T/V/D for each listed abstraction.
  • Still cite repo-local evidence (or explicitly mark missing evidence).
  • Still provide one deterministic proof signal.
  • If interface evolution is in scope, include one compact state-transition sketch (table or bullets) before final cut recommendations.

Output Format (default full profile)

Use these exact section headers in order. If evidence is missing, keep the header and write Not enough repo evidence yet. rather than omitting sections.

0) Scope + assumptions

  • In-scope surfaces:...
  • Out-of-scope:...
  • Constraints discovered:...

1) Abstraction Audit (table) Include one row per abstraction.

AbstractionWhereWhy it exists (hypothesis)Agent-tax (T:0-3 + why)Value (V:0-3 + evidence)Delta (D=T-V)VerdictReplacement
.........T:2 -...V:1 -...+1keep/wrap/slice/replace/delete...

Notes:

  • "Value" must cite repo-local proof: tests/docs/callsites/ops config.
  • If you cannot cite evidence, score V:0.
  • "Verdict" must be one of: keep | wrap | slice | replace | delete.

2) Cut List (prioritized)

  • P0 (delete first):...
  • P1:...
  • P2:...

Each item must include: expected simplification, blast radius, and fastest proof signal.

3) Migration Plan (per cut item) For each P0/P1 item:

  • Seam/boundary:...
  • Phase 1 (reversible):...
  • Phase 2 (switch traffic/callers):...
  • Phase 3 (delete old path):...
  • Proof signals:... (tests/build/run)
  • Rollback lever:...

4) Patch Suggestions (minimal incisions; no code) List concrete, reviewable edits:

  • Files to add/modify/delete:...
  • Commands to run (deterministic):...
  • What "done" looks like (signal):...

5) Risks / limits

  • ...

Replacement Patterns (Examples)

  • React/SPA for a small static site -> HTML/CSS/JS, no build step.
  • Headless CMS for small docs/marketing -> Git + Markdown (+ static site generator if truly needed).
  • ORM for simple CRUD -> parameterized SQL queries.
  • GraphQL for a single client -> REST/JSON endpoints.
  • State management framework for a small UI -> local state with explicit event handlers.
  • Heavy task runner -> scripts/* or Makefile with 3-5 canonical commands.
  • Multi-layer config system -> one config file + a small loader.
  • Scattered auth/runtime guards -> explicit session-state protocol map (Anonymous/Authed/etc.) + thin per-state adapters.
  • Dynamic capability checks spread across services -> capability-state transition table + adapter selection keyed by capability state.

Interaction-Evolving Interface Addendum

Use this when the system's interface changes as a result of interaction.

Detection checklist:

  • The allowed operation set changes after specific responses/events.
  • Current behavior relies on distributed if authorized, feature flag, or capability checks across many call sites.
  • Clients must "guess and fail" at runtime instead of knowing legal next operations from state.

Recommendation policy:

  • Preserve essential protocol evolution; reduce incidental machinery around it.
  • Prefer explicit protocol boundaries:

- state x operation -> next_state - allowed responses per operation - adapter rules (act) and state updates (upd) for integration points

  • Cut targets first: duplicated wrappers, hidden indirection, multipath config, and non-deterministic orchestrators around the protocol.

Proof signals for this mode:

  • Depth-bounded trace tests (at least to depth 3) over legal transitions.
  • One negative test proving an invalid transition is rejected or unrepresentable.
  • Compatibility check showing a fixed-interface simplification (if proposed) preserves observable traces.

Real Trigger Phrases (from session prompts)

Use these phrases as natural-language routing cues for $reduce:

  • "It just feels over-engineered for what I want. Is there a way you can see that we could start simpler and build things back up?"
  • "I really want to reduce the size of the codebase before building it back up."
  • "Only the minimal needed to support what is needed to remain."
  • "How much could we simplify things?"
  • "Brilliant or over-engineered?"

Weekly re-measure loop:

  • Baseline and trend:

- seq skill-report --root ~/.codex/sessions --skill reduce --snippets 20

  • Prompt-cue hit sampling:

- seq query --root ~/.codex/sessions --spec '{"dataset":"messages","where":[{"field":"role","op":"eq","value":"user"},{"field":"text","op":"regex_any","value":["(?i)over-?engineered","(?i)start simpler","(?i)reduce the size of the codebase","(?i)minimal needed","(?i)simplify things"]}],"select":["timestamp","path","text"],"sort":["-timestamp"],"limit":50,"format":"jsonl"}'

  • After one week, compare cue-hit samples and update frontmatter trigger examples only if precision improves.

Questions (Judgment Calls Only)

  • Research first; do not ask for discoverable facts.
  • Ask only judgment calls, prefer 1 question, max 3.
  • Use request_user_input when available; otherwise ask in a short numbered block.

Good questions (examples):

  • "Can we accept some short-term duplication to delete this framework (recommended: yes)?"
  • "Is it acceptable to add a compatibility wrapper so external callers remain stable (recommended: yes)?"
  • "Is infra allowed to change, or is this strictly code-level (recommended: code-level only)?"

Handoffs

  • If trade-offs remain unclear, invoke $creative-problem-solver.
  • If implementation is requested, hand off to $tk.

Pitfalls

  • Generic advice without locations/evidence.
  • Big-bang rewrites without seams, proof signals, and rollback levers.
  • Removing abstractions that are carrying compliance/ops obligations (without a replacement plan).

平台分布

Codex

37.25%
按下载量换算74

Claude

32.57%
按下载量换算64

Cursor

17.95%
按下载量换算36

Gemini CLI

8.97%
按下载量换算18

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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