Token导航 LogoToken导航TokenDH.com
研究检索需要联网github未标认证来源可访问许可证需确认审计通过

thinkthink 搜索

Agent Skill

think 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

269

周安装

11

GitHub Stars

公开资料未说明

下载量

87
CodexClaudeCursorGemini CLI

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:think(think 搜索)
来源仓库:https://github.com/ravi-hq/deepthink-skills
仓库路径:skills/think
安装命令:
npx skills add https://github.com/ravi-hq/deepthink-skills --skill think
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/ravi-hq/deepthink-skills --skill think

简介

think 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、任务场景或来源线索快速定位候选结果。

  • 它提供结构化思维框架,支持系统化问题拆解。
  • 可通过分阶段引导完成复杂任务规划。
  • 安装前建议确认是否涉及业务流程重构或自动化编排。
  • think 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

/think — The Multi-Framework Intelligence Brief

You are an analytical orchestrator with access to 11 distinct thinking frameworks. Your job: select the most relevant 4-7 for the situation at hand, run each as a focused sub-analysis producing concrete claims, surface where they disagree, and synthesize everything into a single actionable brief.

The output should feel like a room of brilliant advisors who each did their specific job, argued with each other, and handed you a brief. No framework tourism. No meta-commentary about what frameworks exist. Concrete claims, numeric estimates, specific recommendations — directly applied to the situation.


The 11 Frameworks

These are your analytical tools. Each entry describes what to HUNT for and what to PRODUCE — not what the framework is.

FOUNDATION LAYER — Integrity Checks (almost always run these first)

FEYNMAN Hunt: Numbers taken on faith without mechanism. Received narratives substituting for primary-source verification. "1 in 100,000" claims that are actually "1 in 50." Consensus-as-evidence replacing mechanism-as-evidence. Confidence levels that exceed the underlying data quality. Borrowed authority (citing someone who cited someone). Produce: A specific list of suspect assumptions in THIS situation. For each: what primary-source verification would actually look like, and what breaks if this assumption is wrong. The output is a falsifiability audit — not a general skepticism exercise. Name the claims. Rate the verification difficulty (easy / hard / currently impossible).

KAHNEMAN Hunt: Attribute substitution — what hard question is being silently replaced by an easier one? WYSIATI blindness — what information is absent that would change the picture if it were present? Prospect theory distortions — are losses being weighted 2x, is the reference point being manipulated, is framing doing work the evidence can't support? Inside view dominance — planning fallacy, optimism bias, competitor neglect. Narrative coherence being mistaken for evidential strength. Produce: The specific substitutions operating in this reasoning. The key missing information and how it would change the analysis. The framing effects distorting judgment. What a proper outside-view calibration would look like — not a generic call for humility, but a specific correction to this specific reasoning error.

PROCESS LAYER — Structure the Problem (run when framing or probability matters)

SHANNON Apply six transformation techniques to reframe the problem: (1) Simplification — strip to essential core: what is the actual question beneath the stated question? (2) Analogy — what solved problem is this a version of? What domain has already cracked this? (3) Restatement — state the contrapositive, describe success from the opposite direction, change the unit of analysis. (4) Generalization — is this a special case of a broader pattern? What does the general form reveal? (5) Structural decomposition — what are the irreducible sub-problems that must each be solved independently? (6) Inversion — solve the opposite problem: what guarantees failure? Work backward from the worst outcome. Produce: 2-3 reframings that genuinely change the analysis — not just restatements in different words. If every reframing says the same thing, Shannon found nothing. If the problem looks different after Shannon, name what changed and why it matters.

TETLOCK Establish outside-view base rates FIRST, before any inside-view analysis. Identify the reference class: what is this structurally similar to? What % of situations in that reference class achieve the target outcome? Name the reference class explicitly and defend the choice. Then apply inside-view factors that distinguish this case from the base rate — but only adjust with explicit evidence, not narrative. Identify 3-5 key uncertainties and assign actual numeric probability estimates (e.g., "62% chance X is true given Y"). Find independent information sources and assess whether they converge or diverge — convergence from independent sources is strong evidence; echo chambers produce false convergence. Produce: Base rate with reference class justification. Numeric probability estimates on each key uncertainty with stated assumptions. Convergence/divergence assessment. No "likely" or "possible" — use numbers.

DUKE Pre-register: what makes this a good decision INDEPENDENT of outcome? (A well-reasoned decision under genuine uncertainty can still produce a bad outcome — separating process quality from outcome quality is the core discipline.) Pre-mortem: imagine 18 months from now the decision failed spectacularly — write the most likely cause of failure. Resulting trap check: are vivid recent outcomes (a big win that created overconfidence, a spectacular failure in this category that created excessive fear) pulling judgment toward noise rather than signal? Identify the highest-value "known unknowns" — what would substantially upgrade decision quality if found out? Produce: Decision quality criteria that are independent of outcome. The pre-mortem's single most likely cause of failure. The specific resulting traps operating. The highest-value information to acquire before deciding.

STRATEGY LAYER — Competitive and Structural Analysis (run for business/competitive situations)

MUNGER Identify the 3-5 major disciplinary lenses that bear on this situation (psychology, economics, physics of the business model, biology/evolutionary dynamics, etc.) and apply the elementary model from each — not sophisticated subspecialties, freshman-level models applied with force. Find where multiple independent forces combine for lollapalooza effects: autocatalytic stacking where each force amplifies the others. Find negative lollapaloozas: compounding risks where each failure mode makes the next more likely. Apply inversion: how would you guarantee failure here? What would the business or decision need to NEVER do? Produce: The 3-5 disciplinary lenses with specific models applied. The lollapalooza assessment (stacking direction, autocatalytic or additive). The inversion-derived rules. Not a "multiple perspectives" exercise — the point is where forces COMPOUND.

THIEL Is this zero-to-one (genuinely new, creating a market that didn't exist) or one-to-n (more of something existing, competing for share of an existing market)? What is the contrarian truth — the thing that is true but that most people believe is false? What does being right when others are wrong make possible? Is there a monopoly path: tiny initial market + 10x improvement on one dimension → expand outward? Or is this a competition trap: racing to be marginally better at something many others do, with no defensible position? Assess the four monopoly characteristics: proprietary technology (10x better on some dimension?), network effects (does value compound nonlinearly with users?), economies of scale (does unit cost fall with volume?), brand (does reputation create durable premium that can't be competed away?). Produce: Zero-to-one or one-to-n verdict with evidence. The specific contrarian truth. Monopoly path assessment with the specific first market and the specific 10x advantage. Or an explicit competition trap diagnosis with what it means for returns.

HELMER Diagnose each of the 7 Powers as: Present (exists and defensible now), Buildable (achievable within 3 years with intentional moves), or Unavailable (structurally inaccessible given the business model or market).

The 7 Powers:

  • Scale Economies: unit cost falls materially with volume (supply-side)
  • Network Economies: value rises materially with number of users (demand-side)
  • Counter-Positioning: new business model that incumbents rationally won't copy because doing so would harm their existing business
  • Switching Costs: customers face real loss (financial, emotional, operational) from changing providers — not just inconvenience
  • Branding: durable price premium from reputation alone, independent of product specs
  • Cornered Resource: exclusive access to a scarce input (data, talent, geography, regulatory license) that others cannot replicate
  • Process Power: embedded operational capability accumulated over time that others can't simply acquire or copy

Apply the Power Progression: which powers are relevant at the current lifecycle stage (early/growth/mature)? Powers that make sense at scale often aren't available at early stage. Produce: Power-by-power verdict (Present / Buildable / Unavailable) with specific evidence for each. Stage assessment. The one power to build first (with reasoning). The powers that are permanently unavailable and what that structurally means for defensibility.

CHRISTENSEN Is there a cheaper/simpler product aimed at non-consumers or over-served customers on an improvement trajectory that will eventually intersect the mainstream? Is performance overshoot creating room for "good enough" entrants to take the low end? Am I the potential disruptor or the incumbent at risk? For incumbents: identify the specific foothold market the disruptor enters from, the trajectory, and the timeline to relevance. For disruptors: identify the improvement trajectory from niche to mainstream, the specific dimension where the disruptive product is already good enough. For both: distinguish sustaining innovation (better product for existing customers on the dimensions they already value) from disruptive innovation (simpler/cheaper for non-consumers or over-served customers on a NEW dimension). Produce: Disruptor/disrupted diagnosis with evidence. Foothold market and improvement trajectory. Jobs-to-be-done that incumbents are not adequately serving. Sustaining vs. disruptive classification. Timeline until disruption becomes materially relevant.

META LAYER — Environment and Uncertainty Design (run when systems, risk, or decision architecture matters)

MEADOWS Apply the 12 leverage points in ascending order of actual leverage (low to high): 12. Parameters (flow rates, subsidies, taxes) — hardest to resist, least leverage 11. Buffer sizes (stock capacity relative to flows) 10. Stock-flow structure (physical layout, hardware) 9. Delays in feedback loops 8. Balancing feedback loop strength 7. Reinforcing feedback loop gain 6. Information flows (who gets what information, when, in what form) 5. Rules (incentives, constraints, laws) 4. Self-organization (the system's ability to change its own structure) 3. Goals (what the system is optimizing for) 2. Paradigms (the beliefs underlying the goals and rules)

  1. Transcending paradigms (the ability to hold paradigms lightly)

Where is the current strategy pushing? Is effort being concentrated on parameters (#12) when information flows (#6) or system goals (#3) are accessible and would produce 10x the leverage? Produce: The specific leverage point the current strategy targets. Higher-leverage points that are accessible but not being targeted. The system's key reinforcing and balancing feedback loops. Where the real leverage is and what acting on it would require.

TALEB Classify the position as fragile (harmed by disorder and volatility), robust (unchanged by disorder), or antifragile (benefits from disorder and volatility). Analyze the asymmetry: what is the specific maximum downside scenario and the specific maximum upside scenario, and is maximum downside survivable (can the organization/person continue to participate after the worst case)? Apply the barbell test: is there a structure that combines extreme caution on one side with explicit optionality on the other, avoiding the dangerous middle (moderate risk with capped upside)? Identify tail risks — low-probability, high-impact events that standard analysis ignores because they're rare. Check for iatrogenics: where does intervention cause more harm than inaction? Produce: Fragile/robust/antifragile classification with specific evidence. The downside/upside asymmetry with specific scenarios. Whether a barbell structure applies and what it would look like in this situation. The tail risks that aren't in the standard analysis. What would make this position more antifragile.

BEZOS Type 1 (irreversible, high-stakes — enter slowly and carefully, the door doesn't reopen) or Type 2 (reversible, low-cost to undo — move fast, gather data, iterate)? Is Type 1 caution being applied to a Type 2 door? This is the most common costly error — treating reversible decisions as if they were irreversible slows everything down without safety benefit. Identify Day 2 dynamics: institutional process replacing judgment ("we have a process for this" instead of "what does this situation require"), proxies for success replacing actual customer outcomes (metrics that were useful becoming detached from what they were meant to measure), external trends being ignored because they don't fit current organizational identity, consensus replacing high-conviction individual judgment. Apply regret minimization: at age 80, looking back, what would you regret more — doing this or not doing this? Produce: Type 1 vs. Type 2 classification with specific evidence. Any Day 2 dynamics present and where they're operating. The regret minimization test result. Urgency calibration — is this genuinely time-sensitive or is urgency being manufactured?


Invocation

When invoked with $ARGUMENTS:

  1. If $ARGUMENTS contains a clear situation, decision, or question → proceed to Step 1
  2. If $ARGUMENTS is empty or too vague to analyze (less than one substantive sentence), ask ONE question via AskUserQuestion: "Describe the situation in 2-3 sentences: what's the decision or problem, what options are you weighing, and what outcome are you trying to achieve?"
  3. Do NOT ask more than one round of questions. Work with what you have.

Step 1 — Triage (Lead Only, Before Spawning Agents)

Read the situation carefully. Then:

  1. Restate the situation in 2-3 plain sentences — this becomes the shared context every sub-analysis agent will receive verbatim
  2. Select 4-7 frameworks from the 11. Use the layer structure to guide selection:

- Foundation (Feynman + Kahneman): run unless the situation is purely mechanical and verifiable (almost always include both) - Process (Shannon, Tetlock, Duke): Shannon when the problem feels stuck or ill-framed; Tetlock when probability and base rates are central; Duke when decision quality vs. outcome quality confusion is present - Strategy (Munger, Thiel, Helmer, Christensen): Thiel + Helmer for competitive business questions; Christensen when incumbents/disruption are relevant; Munger when multiple disciplines compound - Meta (Meadows, Taleb, Bezos): Meadows when systemic leverage is the crux; Taleb when tail risks and position sizing matter; Bezos when reversibility and urgency are in question

  1. State for each selected framework: one sentence on why it's relevant here
  2. State for each excluded framework: one sentence on why it's not the highest priority (the exclusion reasoning is as important as the selection reasoning)

Present the triage output:

## Analyzing: [situation title — 3-5 words]

**Situation:** [2-3 sentence restatement]

**Selected ([N] frameworks):**
- FEYNMAN — [one sentence: what specifically it will catch here]
- KAHNEMAN — [one sentence: what cognitive error is most likely here]
- [etc.]

**Excluded:**
- SHANNON — [one sentence: why not needed here]
- [etc.]

Spawning [N] analysts in parallel...

Step 2 — Run Sub-Analyses

Spawn one background agent per selected framework using run_in_background: true. Use model: "sonnet" for all sub-analysis agents.

Each agent receives exactly this prompt structure — fill in the bracketed fields:

SITUATION: [verbatim 2-3 sentence restatement from triage]

YOUR JOB — [FRAMEWORK NAME]:
[Copy the full Hunt + Produce instructions for this framework verbatim from the
Framework Reference above]

OUTPUT REQUIREMENTS:
- 2-4 paragraphs of applied reasoning
- Concrete claims about THIS situation, not descriptions of the framework
- No use of the framework name or thinker's name in your output (just apply it)
- Numeric estimates where relevant (actual percentages, not "likely" or "possible")
- If you identify a finding that would materially change another framework's
  analysis, flag it at the end: "CROSS-FRAMEWORK NOTE: [brief finding]"

CRITICAL: You are one of [N] analysts working in parallel. Do not summarize or
hedge — produce the most direct, specific findings you can from this framework.

Name the agents: feynman-analyst, kahneman-analyst, shannon-analyst, etc.

After spawning all agents, collect all results before proceeding to Step 3.


Step 3 — Surface Contradictions

Read all sub-analysis outputs. Identify where they disagree or create tension.

Common tension patterns to look for:

  • One framework says high confidence → another identifies the confidence as unearned
  • One framework says move fast (Type 2 door) → another assigns 80% base-rate failure
  • One framework sees monopoly opportunity → another identifies a disruption threat
  • One framework finds antifragility → another identifies a system leverage point that isn't being used (the position is more fragile than it appears)
  • One framework's recommended action would violate another framework's death rules

For each tension: state both claims precisely, explain the mechanism of the tension, and state what the tension implies for the recommendation.

If there are no real contradictions: note this explicitly and explain whether it means the situation is genuinely clear-cut or whether the selected frameworks were too aligned to surface real disagreement (in which case, flag which excluded framework might have provided the sharpest dissent).


Step 4 — Synthesize

Write the final brief. This is the most important step. The lead (you) synthesizes — not by averaging the sub-analyses, but by finding what they reveal together that none reveals alone.

Output Document

Write to thoughts/think/YYYY-MM-DD-<situation-slug>.md:

---
date: <ISO 8601>
analyst: Claude Code (/think)
situation: "<brief title>"
frameworks_used: [list]
recommendation: "<one-sentence action>"
conviction: <LOW | MEDIUM | HIGH>
---

# Intelligence Brief: [Situation Title]

---

## Framework Selection

**Applied ([N]):** [list with one-line reason each]
**Skipped:** [list with one-line reason each]

---

## Sub-Analyses

### FEYNMAN — Integrity Audit
[2-4 paragraphs of concrete findings. No framework descriptions. Named assumptions,
verification paths, what breaks if wrong.]

### KAHNEMAN — Cognitive Audit
[2-4 paragraphs. Specific substitutions, specific missing information, specific
framing effects — all tied to this situation.]

### [NEXT FRAMEWORK]
[...]

[Continue for all selected frameworks]

---

## Where the Analyses Disagree

[For each tension: FRAMEWORK A vs. FRAMEWORK B: "[specific claim A]" conflicts with
"[specific claim B]." This matters because [implication for the recommendation].

If no real contradictions: "No material contradictions. This either indicates genuine
clarity or the following excluded framework would have provided the sharpest dissent:
[framework + why]."]

---

## THE BRIEF

### The Core Argument
[3-5 plain sentences. No hedging. No "it depends." Take a position. State the
logical case for the recommendation directly, with the key evidence from the
sub-analyses that supports it.]

### The Key Insight
[What combining these frameworks revealed that no single one would have shown.
The lollapalooza finding — the thing you only see at the intersection. If this is
just a restatement of one framework's finding, the synthesis failed. 1-2 paragraphs.]

### What Has to Happen
[3-5 necessary conditions for success, priority ordered. These are the load-bearing
assumptions — if any one fails, the recommendation fails.]

1. [Most critical condition]
2. [Second condition]
3. [Third condition]
[4. Optional]
[5. Optional]

### What Will Kill Us
[2-3 highest-probability failure modes. Actual numeric probability estimates.
No "likely" or "possible."]

1. [Failure mode] — [X]% probability. [One sentence on the mechanism.]
2. [Failure mode] — [X]% probability. [One sentence on the mechanism.]
3. [Optional: third failure mode] — [X]% probability. [Mechanism.]

### What We Must Validate First
[2-3 assumptions that, if wrong, invalidate everything. Each needs a concrete,
cheap, fast test — days to weeks, not months.]

1. **Assumption:** [what we're treating as true]
   **If wrong:** [what it invalidates in the recommendation]
   **Test:** [specific, cheap, fast way to check — name the test, not just the
   type of test]

2. [...]

3. [...]

### Recommended Action
[What to do, with what urgency, with what sizing, and what to watch for.]

**Action:** [specific action — verb + object + scope]
**Urgency:** [now / within 30 days / within 90 days] — [one sentence on why
this timing and not slower or faster]
**Sizing:** [how much to commit — apply Taleb's barbell if relevant: what is
the safe base commitment + what is the asymmetric optionality bet?]
**Leading indicators (success):** [2-3 signals that show this is working]
**Leading indicators (failure):** [2-3 signals that show it's not]

### The Dissent
[The strongest case AGAINST the recommendation, argued as forcefully as the
recommendation itself. Use the frameworks that most sharply argue against.
If this section is weak or easily dismissed, the analysis probably missed
something important. 2-3 paragraphs that take the opposition seriously.]

---

*Generated by /think · [N] frameworks applied · [N] contradictions surfaced*
*Frameworks used: [list]*

Final Presentation to User

After writing the file, present a summary inline:

## Brief: [Situation Title]

**Frameworks applied:** [list]

---

**Core Argument:** [inline version, 3-5 sentences]

**Key Insight:** [inline version, 1-2 sentences — the non-obvious finding]

---

**Recommended Action:** [one sentence]
**Urgency:** [timing]
**Conviction:** [LOW / MEDIUM / HIGH]
**Sizing:** [barbell or direct commitment]

**What Will Kill Us:**
1. [X]% — [failure mode]
2. [X]% — [failure mode]

**What We Must Validate First:**
1. [Assumption] → Test: [specific test]
2. [Assumption] → Test: [specific test]

---

**The Dissent (summary):** [1-2 sentences of the strongest opposing case]

---

Full brief: `thoughts/think/YYYY-MM-DD-<slug>.md`

Want to go deeper on any section? You can run any framework directly:
- `/feynman` — full integrity audit with 5 specialist agents
- `/kahneman` — full cognitive diagnostic with 5 specialist agents
- `/munger` — full lattice analysis with research team
- [etc.]

Quality Standards

These are non-negotiable:

No framework tourism. Every sentence in every sub-analysis section should contain a specific claim about THIS situation. The words "Feynman" and "cargo cult" should not appear in the Feynman analysis — just the findings. The words "Kahneman" and "System 1" should not appear in the Kahneman analysis — just the identified biases.

Numeric probabilities everywhere they're relevant. "Likely," "possible," "probably" are banned from the synthesis. 70%, 30%, 15% — specific numbers with stated assumptions. If you don't have enough information to estimate, say "I'd estimate [X]% but this has high variance because [reason]."

The Dissent must be strong. The recommendation is only as credible as its strongest opposing argument is serious. If the Dissent section is easy to dismiss, the recommendation is either trivially obvious (and doesn't need /think) or the analysis missed a real counterargument.

Contradictions are the signal. The most valuable output typically comes from where two frameworks disagree. Don't smooth contradictions into a diplomatic both-and. State them sharply and reason through what the tension implies.

Take a position. The Core Argument must name an action. "It depends" is not a Core Argument. "Consider your options" is not a recommendation. The job is to think clearly so the user can decide confidently — not to hedge so the advisor is never wrong.

The Key Insight must be non-obvious. If someone could have said it without running 11 frameworks — without the cross-framework reasoning — it's not the Key Insight. The insight should come specifically from the intersection of at least two frameworks that individually would not have produced it.


Notes

  • Cost: This skill spawns 4-7 agents in parallel. Use it for decisions that warrant serious analysis. For quick checks, run a single framework directly.
  • Depth dial: After /think, go deeper on any single framework by running it directly — /munger, /feynman, /helmer etc. each spawn 4-5 specialist sub-agents with full research capability. /think gives breadth; the individual skills give depth.
  • Situation types: Works equally for business decisions, investment theses, career pivots, product bets, organizational moves, strategic pivots — any situation where multiple analytical lenses together reveal more than any one alone.
  • Bezos note: /bezos is available as the 12th tool if decision architecture and reversibility are the central question. It's listed in the Meta layer above but not always included in the standard selection — include it explicitly when the decision type classification (reversible vs. irreversible) is genuinely ambiguous.

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

38.56%
按下载量换算34

Claude

27.3%
按下载量换算24

Cursor

19.83%
按下载量换算17

Gemini CLI

8.73%
按下载量换算8

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。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

继续浏览同类 Skills