去伪求真深度研究

SKILL效率
效率 未标注权限 许可证不明确
安装这个技能

不只是让 AI 搜索,而是让 AI 的每一句结论都被拆成可验证的 claim,逐条对信源、打真伪、查冲突、补因果——一份能"自证清白"的深度研究引擎。

一句话选型结论

按资料字段整理

去伪求真深度研究是效率类的 Agent Skill,安装方式未标注,权限级别未标注,许可证不明确,有可直接复制的安装命令。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类效率 安装方式未标注 权限级别未标注权限 许可证许可证不明确
累计安装 未标注 本周 未标注
GitHub 星标 未标注 仓库 未标注
下载量 未标注 技能市场下载数
权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

未标注
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
skillhub install user_cd2de2e2/net-deep-research
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    执行上面的命令安装;也可以把仓库里的 SKILL.md 手动放进客户端的 skills 目录。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

效率
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方user_cd2de2e2仓库 未标注 · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式未标注安装包 community
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验未标注上游最后核验时间 · 数据更新 1791625896
正文体量21.3 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
整理待办与日程

把零散任务收进清单,排出优先级。

批量处理重复任务

把固定动作做成模板,重复执行。

把流程写成清单

把口头流程整理成可复用的步骤。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 有可直接复制的安装命令,不用自己翻文档找入口。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在效率场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
去伪求真深度研究当前 未标注权限 未标注 未标注 未标注 有
Nano PDF 文档 联网访问 ClawHub 市场 424.9 万 OpenClaw 有
自动更新程序 浏览器控制 ClawHub 市场 296.4 万 OpenClaw 有
Gemini 助手 联网访问 ClawHub 市场 254.7 万 OpenClaw 有
word DOCX 文档 联网访问 ClawHub 市场 239.6 万 OpenClaw 有
Excel XLSX 前端 联网访问 ClawHub 市场 227.0 万 OpenClaw 有

SKILL.md 全文

21.3 KB
模型实际读到的说明书原文,来自技能仓库

Net Deep Research

When this skill is triggered, do not answer immediately.

Turn the request into a controlled research workflow:
1. classify the question,
2. normalize the scope,
3. decompose it into subquestions,
4. derive critical claims,
5. research in rounds,
6. resolve or expose conflicts,
7. answer from a structured evidence map.

Trigger Handling

If the user message starts with /net:
- remove the /net prefix
- trim whitespace
- treat the remainder as the actual research question

Then restate the question in one sentence before researching.

Goal

Produce answers that are:
- current
- evidence-based
- multi-source
- explicit about uncertainty
- grounded in stable public sources
- clear about what is verified vs inferred

Hard Rules

Apply these rules strictly:
1. For predictive, forward-looking, market, macro, or scenario questions, separate the answer into two layers:
- Verified Facts
- Inference
2. Tie every core conclusion to at least one primary source whenever possible.
3. Do not let secondary media, commentary, or community discussion be the only support for a key conclusion when a stronger source family is available.
4. If direct official fetching fails, use the fixed fallback order instead of ad hoc substitution.
5. Do not skip subquestion decomposition for non-trivial questions.
6. Do not treat multiple pages repeating the same original announcement as independent evidence.

Mode Selection

Choose one primary_mode. Add one secondary_mode only if it clearly helps.

Mode A: Current Fact Check

Use for questions about latest status, current availability, recent releases, or whether something is already live.

Mode B: Capability Or Compatibility Verification

Use for questions about support, compatibility, feature availability, plans, versions, models, or platforms.

Mode C: Implementation Or How-To Research

Use for questions about how to build, integrate, deploy, or implement something, including best practices and architecture.

Mode D: Comparison, Selection, Or Policy Confirmation

Use for questions about choosing among alternatives, policy confirmation, framework selection, official rules, or tradeoff analysis.

Classification Rules

Apply these rules in order:
1. If the question is about how to implement, integrate, deploy, or build, choose Mode C.
2. If the question is about comparing options, choosing the best option, or checking policy or official rules, choose Mode D.
3. If the question is about support, compatibility, or whether a feature exists, choose Mode B.
4. If the question is about the latest or current status of a fact, choose Mode A.

Use a secondary mode only when both are necessary:
- Mode A + Mode B: current support status
- Mode B + Mode C: whether possible, then how to implement
- Mode D + Mode C: choose a solution, then outline implementation

Question Normalization

Before searching, extract:
- subject
- target_capability if any
- time_scope if provided
- region_scope if provided
- version_scope if provided

Do not invent missing scopes.

Then rewrite the request as one normalized question.

Subquestion Decomposition

Before extracting claims, decompose the normalized question into up to 6 subquestions.

Always try to produce:
- core_subquestions: what must be answered to resolve the user's request
- verification_subquestions: what boundaries, prerequisites, or limitations must be checked
- countercheck_subquestions: what likely counterexamples, exceptions, or contradictions should be tested

For simple questions, 2-3 subquestions is enough.
For complex questions, use 4-6 subquestions.

Do not skip this step unless the question clearly qualifies for fast path.

Claim Extraction

Derive at most 3 critical claims from the subquestions.

Typical claim shapes:
- whether the capability exists
- when the capability became available
- what scope, limitations, or exclusions apply
- which option best fits the user's goal
- what implementation path is most appropriate

Every important conclusion in the final answer should map back to one of these claims.

Query Planning

Plan queries per claim, not just per question.

For each important claim, generate these core query slots:
- direct_query
- official_query
- release_query
- contradiction_query

Add one mode-specific slot:
- Mode A -> recent_query
- Mode B -> compatibility_query
- Mode C -> implementation_query
- Mode D -> comparison_query or policy_query

Keep the total query count between 4 and 8 for a normal request.

For technical, product, framework, or API questions, prefer bilingual query planning when helpful:
- use English queries for official docs, repos, and release notes
- use Chinese queries for China-specific products, policy, regional availability, or local interpretation
- do not force bilingual searching when the domain is clearly single-language

Research Rounds

Use a staged research workflow.

Round 1: Primary Evidence

Search primary and official sources first.
Goal: establish the strongest direct evidence for each claim.

Round 2: Independent Verification

Add independent support from a different strong source family.
Goal: confirm scope, version, timing, or practical limitations.

Round 3: Conflict Resolution

Run only when needed.
Trigger this round when:
- strong sources disagree
- timing or version differences matter
- region or plan differences may explain the conflict
- the answer would otherwise rely on weak evidence

Goal: explain the disagreement, not just note it.

Research Budget And Stop Rules

Use these defaults unless the question clearly demands more depth:
- max_search_rounds = 3
- target_primary_sources_per_core_claim = 1
- target_total_supporting_sources_per_core_claim = 2
- max_key_claims = 3

Stop when all of these are true:
- each core claim has direct support or a clearly stated evidence gap
- no major unresolved conflict blocks the main answer
- uncertainty is explicit where evidence is weak

Escalate to another search round when any of these are true:
- a claim depends only on weak or secondary support
- a key source appears outdated for the user's time scope
- two strong sources materially disagree
- implementation advice depends on unverified capability assumptions

Source Routing

Use source families, not fixed websites, as the primary routing method.

Mode A Priority

  1. official announcement, changelog, release notes
  2. official docs
  3. official repository releases
  4. high-quality secondary reporting

Mode B Priority

  1. official docs
  2. API reference or SDK docs
  3. official repository, release, or issue
  4. package registry pages

Mode C Priority

  1. official docs
  2. official repository README, examples, guides
  3. package registry pages
  4. stable technical references

Mode D Priority

  1. official docs or official sites
  2. government, institutional, or standards sources when relevant
  3. official repository, pricing, feature, or explanation pages
  4. high-quality secondary analysis

Preferred Source Families

Prefer these source families when relevant:
- official documentation sites
- official company or organization sites
- official changelogs and release notes
- GitHub repositories and releases
- package registries such as PyPI and npm
- standards sites such as RFC, IETF, and W3C
- government and institutional sites
- stable technical references such as MDN

Accessibility, Stability, And Dedup Rules

Prefer sources that are:
- public
- readable without login
- likely to remain available
- broadly reachable for both international and China-based users when possible

Avoid depending on:
- login-gated content
- short-form social posts
- low-signal community threads as the only evidence
- content farms or SEO spam pages
- unattributed reposts

If direct official fetching fails, use this fixed fallback order and do not skip steps:
- official page -> official mirror or official alternate page -> official changelog or release note -> official GitHub or official repository page -> package registry or standards page -> stable technical reference
- government or institution page -> official FAQ -> official press release -> official transcript or bulletin -> high-quality institutional analysis

Apply source dedup rules:
- do not count mirrored pages of the same original announcement as independent evidence
- do not count a media rewrite of an official post as a separate primary source
- treat same-origin release note plus marketing page as one source family unless they provide materially different evidence

Source Filtering And Scoring

Reject a source as key evidence if it:
- requires login for the core content
- does not clearly support any claim
- is only a repost without the original source
- is obviously low quality or SEO-generated

Score each candidate source across 6 dimensions, each from 0 to 2.
Apply the rules for each dimension mechanically: start from score 2 and walk down until a condition matches.
Total score range: 0-12.


1. authority — who published it

Apply these checks in order. Stop at the first match.

Condition Score
The domain IS the official domain of the subject under research (e.g. nextjs.org for Next.js, python.org for Python, rust-lang.org for Rust) 2
The domain IS a .gov, .edu, or standards-body domain (e.g. rfc-editor.org, w3.org, ietf.org, iso.org, ieee.org) 2
The page IS on the subject's own GitHub/GitLab org (e.g. github.com/facebook/react for React) 2
The page IS on a curated developer reference platform (e.g. MDN, caniuse.com, web.dev, docs.rs, nodejs.org/api) 1
The page IS an official package-registry entry (e.g. npmjs.com/package/*, pypi.org/project/*, crates.io/crates/*) 1
The page IS authored by a verified project maintainer or recognized core contributor (e.g. a maintainer's blog, their personal GitHub, a signed commit/issue) 1
The page IS on an established tech publication with editorial process (e.g. arstechnica.com, lwn.net, theverge.com for product news only) 1
None of the above match 0

2. stability — will this URL still work in 12 months

Prefer automated scoring. For each candidate URL, run the bundled Python scorer first:

python3 tools/score_stability.py --json "<url>"

This returns {"score": <0|1|2>, "rule": "<matched_rule>", "explanation": "..."}.

Use the returned score directly. Only fall back to manual scoring when the Python runtime is unavailable.

Manual scoring rules (identical to the script's logic, for reference):

Condition Score
The URL IS a GitHub/GitLab permalink: /releases/tag/*, /blob/<sha>/*, /commit/*, or a repo root with a fixed name 2
The URL IS on docs.* subdomain, *.readthedocs.io, *.github.io, or a /docs/* path on the official domain 2
The URL IS a .gov, .edu, standards-body, or institutional archive page 2
The URL IS a package-registry permalink (e.g. npmjs.com/package/<name>, pypi.org/project/<name>) 2
The URL IS an official blog post on the project's own domain (e.g. nextjs.org/blog/*) 1
The URL IS an official mirror or alternate-source page 1
The URL IS a reputable news outlet or established tech-publication article 1
The URL IS a third-party blog platform (e.g. medium.com, dev.to) — content may be reorganized or paywalled later 1
The page IS a social-media post (Twitter/X, Reddit, Hacker News, etc.) or a personal blog with no institutional backing 0
The URL contains session IDs, temporary tokens, or link-shortener domains (t.co, bit.ly, etc.) 0

3. accessibility — can anyone read it without barriers

Apply these checks in order. Stop at the first match.

Condition Score
Page loaded successfully with NO login prompt, NO paywall overlay, NO captcha challenge, and NO geo-block 2
Page loaded but requires a free account to view beyond the first N paragraphs (e.g. Medium metered wall) 1
Page loaded but the site is known to be geo-restricted in some major regions (e.g. bard.google.com in specific regions) 1
Page requires login or paid subscription to view the core content; the visible portion is only a summary 0
Page is entirely behind a paywall, login wall, or captcha gate 0

4. freshness — how current relative to the question's time scope

This dimension is scored relative to the question, not by absolute recency alone.

Step 1: Determine the reference window.

Question has... Reference window
Explicit time_scope (e.g. "in 2024", "last month", "since v18") Use the user-stated window
A specific version number Match against that version only
No time scope Default to last 12 months

Step 2: Assign score based on how the source falls relative to the window.

Condition Score
Source was published or last-updated WITHIN the reference window, AND explicitly covers the version/timeline asked 2
Source was published or last-updated within the reference window, but does not explicitly mention dates or versions 1
Source date is UNKNOWN but the content appears current (e.g. mentions a recent feature, links to up-to-date references) 1
Source was published or last-updated 12-24 months outside the reference window, but no evidence it has been superseded 1
Source is clearly OUTSIDE the reference window by > 24 months 0
Source has been explicitly SUPERSEDED by a later official announcement, release, or deprecation notice 0

For version-specific questions, apply this version-based override:
| Condition | Score |
|---|---|
| Source explicitly documents or references the target version | 2 |
| Source covers a nearby version (± 1 major) with the same API surface | 1 |
| Source covers a version known to have breaking changes relative to the target | 0 |


5. relevance — does the content directly address the claim

Quantified by evidence proximity: how many inference steps are needed to connect source content to the claim.

Condition Score
Source contains a direct, explicit statement that confirms or refutes the claim — zero inference steps needed 2
Source covers the general topic and allows ONE logical inference step to reach the claim (e.g. it lists a supported feature set, and the user's feature is clearly inside/outside it) 1
Source only mentions the topic tangentially, or requires TWO OR MORE inference steps to connect to the claim 0
Source is about a different subject entirely 0

6. primacy — how close is this to the original information

This dimension punishes mirroring. Two pages repeating the same official announcement should not both score high.

Condition Score
This IS the original source: the official announcement, the original research paper, the first-hand documentation, the actual release note, the commit itself 2
This is a SECONDARY source that retells or analyzes the original, but ADDS meaningful original context (e.g. new benchmark data, a comparison the original didn't do, an implementation walkthrough) 1
This is a TERTIARY or DERIVATIVE source: a pure repost, a summary without added insight, a "news roundup", or a mirrored press release 0
This is a community discussion that merely links to or quotes the primary source without adding verified new information 0

Minimum Rules

  • Do not use a source with total score below 5 (out of 12) as key evidence
  • Every important claim must have at least one source with both authority >= 1 AND relevance >= 1
  • Every core conclusion must be anchored to at least one source with primacy = 2 whenever possible
  • If a claim's best source has primacy = 0, explicitly flag this as a "derivative only" evidence gap
  • Must report the 6-dimension score breakdown for any source used as key evidence in the Sources section (e.g. A:2 S:2 A:2 F:1 R:2 P:2 = 11/12)

Scoring Shortcuts (for fast triage)

Before doing the full 6-dimension score, apply these instant-reject / instant-accept shortcuts:

Shortcut Action
Source is a social media post (Twitter/X, Reddit, HN) AND is not from a verified project maintainer account Auto-score authority=0, stability=0; proceed with remaining 4 dims only
Source is a content farm, SEO spam, or AI-generated slop Reject immediately; do not score
Source is the official GitHub release page of the EXACT project the user asked about Auto-score authority=2, stability=2, primacy=2; score remaining 3 dims fresh
Source is a community forum (StackOverflow, Reddit thread) with an accepted answer from a recognized maintainer Score normally; authority may be 1 for the maintainer's answer

Evidence Extraction

For each claim, extract evidence items with:
- claim_id
- source_title
- source_url
- source_date_hint if available
- evidence_snippet
- source_score
- stance: support, oppose, or partial

Do not over-quote. Extract only the part needed to support the claim.

Conflict Handling

If a claim has both supporting and opposing evidence, explicitly mark it as conflicted.

Only use these conflict causes:
- version difference
- timing difference
- region difference
- plan tier difference
- wording ambiguity
- evidence insufficiency

Do not invent a conflict explanation without support.

When a claim is conflicted, internally build this mini-structure before answering:
- claim
- supporting_evidence
- opposing_evidence
- conflict_cause
- current_best_explanation
- residual_uncertainty

Confidence Rules

Assign confidence per key claim:

High

  • at least 2 supporting sources
  • at least 1 strong primary source
  • no major unresolved conflict

Medium

  • at least 1 reasonably strong source
  • some scope limitation or minor conflict

Low

  • only weak support
  • or unresolved conflict
  • or no clear primary source

Evidence Map

Before writing the answer, build this internal structure:
- question_restatement
- primary_mode
- secondary_mode if any
- normalized_question
- subquestions
- claims
- evidence_by_claim
- conflicts
- uncertainties
- final_conclusions
- answer_outline

For predictive, market, macro, or outlook questions, the evidence map must also separate:
- verified_facts
- inference

Do not skip this step.

Final Answer Format

Default section order:
1. Question Restatement
2. Short Answer
3. Key Findings
4. Cross-Source Notes
5. Uncertainties or Limits
6. Sources

For predictive, market, macro, or outlook questions, use this stricter order:
1. Question Restatement
2. Short Answer
3. Verified Facts
4. Inference
5. Cross-Source Notes
6. Uncertainties or Limits
7. Sources

For implementation or comparison questions, add a concise Recommendation block when useful.

Writing Rules

In Short Answer:
- answer directly
- keep it concise

In Key Findings:
- separate confirmed facts from implications
- prioritize evidence from official or primary sources
- tie each core conclusion back to a claim

In Cross-Source Notes:
- explain where sources agree
- explain where they differ
- mention version, timing, regional, or plan differences when relevant

In Verified Facts:
- include only directly supported facts
- keep interpretation minimal
- attach stronger sources first

In Inference:
- derive each inference from the verified facts above
- do not present inference as confirmed fact
- explicitly signal when the inference depends on policy, timing, or assumption-sensitive interpretation

In Uncertainties or Limits:
- clearly state what could not be verified
- clearly state if official sources were unavailable and fallback layers were used
- do not hide missing evidence

In Sources:
- list the most useful sources, not every weak result
- prefer strong primary sources first

Fast Path

Use fast path only when:
- the question is simple
- there is a clear primary source
- there is little risk of ambiguity

Even then:
- check the primary source
- add one independent supporting source if practical
- skip fast path if the answer depends on version, timing, region, or plan differences

Example Handling Pattern

If the user asks:
- /net What is the best agent framework right now, and use it to help me design a game?

Then:
- classify as Mode D with Mode C secondary
- normalize the user goal and split it into selection and implementation subquestions
- compare current agent framework candidates using official docs, GitHub, releases, and stable public references
- verify the top candidate with at least one independent supporting source
- resolve any conflict about maturity, maintenance, or capability scope
- decide which framework best fits the requested goal
- then outline a game-building workflow using that framework
- clearly separate:
- evidence for framework selection
- implementation guidance for the game workflow

Final Reminder

Research first.
Model the question second.
Resolve conflicts third.
Answer last.

常见问题

5 问
答案由本站依据条目字段整理
去伪求真深度研究怎么安装?

在支持 Skills 的客户端里执行:skillhub install user_cd2de2e2/net-deep-research。安装方式为未标注。装完刷新技能列表或重开客户端。

去伪求真深度研究支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

去伪求真深度研究权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

去伪求真深度研究收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

去伪求真深度研究用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

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技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 未标注。