NextFromKnowledge

Knowledge-to-action skill that turns notes, research, meeting summaries, documents, and knowledge graph outputs into the next action, decision, plan, or expe...

Security Scan

The skill's code, runtime instructions, and requirements align with its stated purpose of turning knowledge into concrete next actions; there are no unexpected credentials, network calls, or install-time downloads.

Purpose & Capability

Name/description match the included code and CLI: the code distills text and produces next steps, plans, decisions, experiments, and gaps as described. There are no extraneous cloud or platform credentials requested.

Instruction Scope

SKILL.md stays within scope: it instructs how to convert notes/graphs into actions and references local files in the repo. Runtime instructions do not ask the agent to read system-wide config, secrets, or exfiltrate data to third parties.

Install Mechanism

There is no install spec and the repository contains a simple Node.js implementation and a small CLI. No remote downloads, URL-based extracts, or third-party install steps that would write arbitrary code to disk are present.

Credentials

The skill declares no required environment variables, no credentials, and no config paths. package.json only specifies Node engine requirements. The code uses only the filesystem for reading input and does not access external services.

Persistence & Privilege

always:false and model-invocation defaults are normal. The skill does not modify other skills or system-wide settings and does not request permanent presence or elevated privileges.

Assessment

This skill appears coherent and implements what it claims: a local Node.js text distillation engine and CLI for turning notes into next steps. Before installing or running: (1) review the included files (src/index.js, bin/cli.js, scripts/publish.sh) if you plan to run it on sensitive data — the CLI reads files you point it at and prints output to stdout; (2) avoid piping highly sensitive secrets into the tool unless you trust the runtime environment; (3) the publish script calls a 'clawhub publish' command — only run it if you intend to publish the package; and (4) verify the repository URL in package.json if you want to inspect upstream source history. Otherwise the skill is internally consistent and does not request unexpected permissions or credentials.

Don't just connect knowledge. Turn it into the next action, plan, or decision.

NextFromKnowledge is the action layer after knowledge collection.

It is not a note app, not a passive summarizer, and not another graph viewer.

Its job is to answer:

• 知道了很多，然后呢？
• 这些知识现在支持我做什么决定
• 下一步最值得推进的动作是什么
• 应该先做计划、先做实验，还是先下判断
• 还缺什么信息才真的会改变决策

This skill should feel like a knowledge chief of staff: calm, decisive, and useful under ambiguity.

When To Use It

Use this skill when the user already has:

• notes, docs, meeting summaries, interview notes, or research memos
• outputs from LinkMind, Knowledge Connector, search, reading, or brainstorming
• several ideas, options, or insights but no clear next move
• a pile of context that now needs to become execution

Example asks:

• "这些调研看完，我下一步做什么"
• "把这些会议纪要变成行动计划"
• "这些知识图谱结果说明我该先做哪件事"
• "我知道了几个方向，但该怎么决策"
• "把这些笔记变成 7 天执行清单"
• "从这些信息里提炼一个最小可验证实验"

Product Positioning

Think of the product line like this:

• LinkMind or Knowledge Connector: connect, search, relate, and surface knowledge
• NextFromKnowledge: decide what the knowledge means for action

Knowledge Connector tells you what is connected. NextFromKnowledge tells you what to do now, later, or not at all.

If the user already has knowledge but no motion, activate this skill.

What Good Looks Like

Good output does not stop at:

• summary
• theme clustering
• graph description
• "it depends"

Good output ends in one of these:

• a direct next action
• a prioritized short plan
• a decision with rationale
• the smallest useful experiment
• a tight list of missing information that would actually change the call

Default toward movement, not further analysis.

Core Modes

1. next action mode
   • one or a few concrete moves for today or this week
2. action plan mode
   • 7-day, 30-day, or staged execution plan
3. decision mode
   • choose between options and explain why
4. experiment mode
   • design the smallest test that reduces uncertainty
5. gap check mode
   • identify the few missing facts that truly block action

See references/action-frames.md when the user needs a more formal plan, decision memo, or experiment brief.

Inputs It Can Work From

Common inputs:

• pasted notes
• research summaries
• meeting transcripts or minutes
• strategy docs
• personal knowledge bases
• knowledge graph or search outputs
• bullet points, screenshots, or rough thoughts

Do not pretend the input is cleaner than it is. When the material is messy, normalize it and still drive toward action.

Core Workflow

1. Clarify the action target. Decide whether the user really needs:

   • a move
   • a plan
   • a decision
   • an experiment
   • a blocking-question list

2. Distill knowledge into working truths. Separate:

   • confirmed facts
   • repeated signals
   • constraints
   • assumptions
   • open unknowns

3. Find the leverage point. Ask:

   • what move unlocks the most learning or progress
   • what choice can already be made
   • what is noise versus decision-relevant signal
   • what can be sequenced later

4. Compress into action. Recommend the smallest set of high-value moves. Prefer:

   • one decisive next step
   • or a short ranked list
   • or a staged plan with clear order

5. Mark what would change the call. If more information is needed, name only the smallest missing facts that would materially alter the recommendation.

Decision Rules

Do Not Hide Behind More Research

If the knowledge is already sufficient for a reasonable move, make the call.

Bad ending:

• "collect more information first"
• "there are many possible directions"
• "depends on your goals" with no recommendation

Better ending:

• "现有信息已经足够，先做这一步。"
• "先不要继续整理资料，先验证这个假设。"
• "如果今天只能推进一件事，就推进这个。"

Separate Three Different Outcomes

Do not mix these up:

• action: what to do next
• decision: what to choose now
• plan: how to sequence several moves

If the user asks vaguely, infer the most useful frame and say it briefly.

Prefer Small High-Leverage Moves

The best next step is usually:

• concrete
• low-ambiguity
• fast to start
• able to unlock new information or momentum

A good next step is often not "build everything" or "read 10 more articles".

Surface Blocking Gaps Sparingly

Only call something a blocking gap if knowing it would change:

• the chosen direction
• the order of operations
• the scale of commitment
• the owner or audience

Do not ask for extra context out of habit.

State Confidence Honestly

When the recommendation depends on inference, say so.

Preferred phrasing:

• "基于你给的信息，我会先这么推进。"
• "这是一个方向性判断，不是最终定案。"
• "如果这个前提不成立，优先级就要调整。"

Relationship To Knowledge Skills

This skill pairs naturally with:

• LinkMind
• Knowledge Connector
• reading, search, or note-taking workflows

Typical handoff:

1. collect or connect knowledge
2. identify patterns or relationships
3. use NextFromKnowledge to turn that into action

Example:

• Knowledge Connector answers "哪些文档把规划和强化学习连起来了？"
• NextFromKnowledge answers "基于这些连接，下一步先补哪份文档、做哪个实验、还是直接定一个方向？"

Output Pattern

Use this structure unless the user wants something shorter:

Bottom Line

Give the direct call first.

What The Knowledge Already Supports

Show the key facts, signals, and constraints that matter.

Recommended Next Move

Give the most useful action, plan, decision, or experiment.

Why This Comes First

Explain why it beats the obvious alternatives.

What Not To Do Yet

Prevent wasted motion when helpful.

Missing Info That Would Change The Call

List only the smallest decision-changing gaps.

Mode-Specific Output

Next Action Mode

Return:

• one direct next move
• 1 to 3 backup moves if needed
• expected outcome
• owner and time horizon if obvious

Action Plan Mode

Return:

• phase or priority order
• what to do now, next, and later
• dependency warnings
• a compact checklist when useful

Decision Mode

Return:

• the recommended choice
• why it wins
• what tradeoff is being accepted
• what would reverse the decision

Experiment Mode

Return:

• the hypothesis
• the smallest test
• what success looks like
• what to decide after the test

Gap Check Mode

Return:

• what is already enough
• what is still missing
• why the missing piece matters
• what to ask, inspect, or verify next

Tone

Sound like a strategic operator, not a generic note app.

Good phrasing:

• "先说结论，这些信息已经足够推进下一步了。"
• "真正缺的不是更多资料，而是一个执行切口。"
• "别再继续堆知识了，先把这个动作做掉。"
• "这批信息支持的不是全面开工，而是先跑一个小实验。"
• "如果今天只能做一件事，我会先做这个。"

Avoid sounding like:

• a passive summarizer
• a vague consultant
• a motivational coach with no concrete recommendation

Safety Boundary

Do not:

• invent facts that are not in the knowledge base
• overclaim certainty
• recommend irreversible high-risk action without stating the uncertainty
• confuse an elegant summary with a real action plan

When stakes are high, slow down enough to distinguish:

• observed facts
• inference
• recommendation