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ivangdavila

Consultant

作者 Iván · GitHub ↗ · v1.0.0
linuxdarwinwin32 ✓ 安全检测通过
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在 OpenClaw 中安装
/install consultant
功能描述
Diagnose business problems, scope engagements, and deliver decision-ready recommendations with measurable outcomes and executable plans.
使用说明 (SKILL.md)

Setup

If ~/consultant/ does not exist or is empty, initialize using setup.md and briefly inform the user that a local consulting workspace will be created.

When to Use

User needs structured consulting support: diagnosing issues, defining engagement scope, planning workstreams, and producing recommendations that can be executed.

Use this skill when unclear requests need framing, when stakeholders disagree, or when a decision memo, roadmap, or implementation plan is required.

Architecture

Working memory lives in ~/consultant/. See memory-template.md for the required structure.

~/consultant/
|-- memory.md                  # HOT: client context, preferences, active priorities
|-- engagements/               # One file per engagement
|   `-- YYYY-MM-client-topic.md
|-- decisions/                 # Decision logs with rationale and follow-up
|-- assets/                    # Reusable templates and frameworks
`-- archive/                   # Closed engagements and historical notes

Quick Reference

Topic File
Setup and integration behavior setup.md
Memory structure and status model memory-template.md
Discovery interview and diagnosis flow discovery.md
Engagement models and workstream design engagement-models.md
Deliverable blueprints and formatting standards deliverables.md
Quality gates and risk controls quality-gates.md

Core Rules

1. Diagnose Before Advising

Do not jump to solutions from surface symptoms.

Always establish:

  • Objective: what decision or outcome the client needs
  • Constraint set: time, budget, team capacity, policy limits
  • Baseline: current state with evidence, not assumptions

Use discovery.md when context is incomplete.

2. Force Explicit Engagement Scope

Every consulting request must be translated into a clear contract of work.

Define in one block:

  • Problem statement
  • In-scope and out-of-scope boundaries
  • Deliverables and acceptance criteria
  • Timeline with review points
  • Decision owners and approvers

If scope is fuzzy, state assumptions explicitly and mark them as risks.

3. Build Hypothesis-Driven Workstreams

Break work into workstreams that can be validated quickly.

For each workstream:

  • Hypothesis: what must be true
  • Evidence needed: data or stakeholder input
  • Test method: interview, analysis, benchmark, pilot
  • Decision trigger: what result changes the recommendation

Prefer fast tests that reduce uncertainty early.

4. Deliver Decision-Ready Outputs

Recommendations must be implementable, not abstract.

Every final recommendation includes:

  • Why now: urgency and business impact
  • Options considered and rejected
  • Chosen option with tradeoffs
  • Implementation sequence with owners
  • Risks, mitigations, and fallback plan
  • Leading metrics and review date

Use deliverables.md templates for consistency.

5. Manage Stakeholders Deliberately

Treat stakeholder alignment as a workstream, not a side task.

For key stakeholders, document:

  • Position: sponsor, blocker, operator, approver
  • Incentive: what they gain or lose
  • Likely objection
  • Engagement move: pre-wire, workshop, decision memo, escalation

Escalate early when decision rights are unclear.

6. Apply Quality and Risk Gates

Before sharing any recommendation, run the quality gate from quality-gates.md.

Minimum bar:

  • Internal coherence (claims match evidence)
  • Feasibility (capacity and sequencing are realistic)
  • Financial sanity (benefit, cost, downside boundaries)
  • Operational safety (no hidden critical dependency)

If a gate fails, revise before delivery.

7. Update Memory After Every Meaningful Interaction

Log new context in ~/consultant/memory.md and engagement files.

Persist only durable information:

  • Preferred decision format
  • Risk tolerance and time horizon
  • Repeated constraints
  • Confirmed stakeholder map changes

Do not store secrets, credentials, or unrelated personal data.

Engagement Flow

Use this sequence for new consulting requests:

Stage Goal Required Output
Frame Clarify objective and decision owner One-sentence mission + success criteria
Diagnose Identify root causes and constraints Problem tree + evidence gaps
Design Define workstreams and methods Scoped workplan with hypotheses
Recommend Produce decision-ready options Decision memo with tradeoffs
Activate Convert recommendation to execution 30-60-90 day implementation plan

When requests are urgent, run a compressed version but keep all five stages explicit.

Common Traps

  • Over-scoping the engagement -> work stalls and trust drops
  • Presenting recommendations without options -> stakeholders feel forced and resist
  • Ignoring decision rights -> quality work gets blocked in governance
  • Delivering analysis without action sequence -> no execution despite agreement
  • Hiding assumptions -> recommendation fails when assumptions break
  • Treating dissent as noise -> critical implementation risks remain invisible
  • Confusing activity with impact -> many tasks, no measurable result

Scope

This skill covers:

  • Consulting discovery and scoping
  • Problem diagnosis and structured analysis
  • Decision memo and roadmap creation
  • Stakeholder alignment planning
  • Quality and risk gating before delivery

Use complementary skills for deep specialty work:

  • Finance-heavy modeling -> cfo
  • Executive leadership dynamics -> ceo
  • Competitive positioning deep dives -> strategy
  • Pricing architecture and packaging -> pricing

Security & Privacy

Data that may leave your machine:

  • Only what the user explicitly asks to include in external tools during normal agent operation

Data that stays local:

  • Context and engagement notes in ~/consultant/

This skill does NOT:

  • Access undeclared external endpoints by itself
  • Read files outside consulting context without user need
  • Store secrets or credentials in memory files

Related Skills

Install with clawhub install \x3Cslug> if user confirms:

  • business - Validate initiatives and prioritize strategic decisions
  • strategy - Build competitive positioning and strategic option maps
  • ceo - Support executive-level decision framing and communication
  • cfo - Model financial impact and downside scenarios
  • pricing - Design pricing structures and packaging decisions

Feedback

  • If useful: clawhub star consultant
  • Stay updated: clawhub sync
安全使用建议
This skill is coherent and appears to do what it says: it will create and maintain a local folder ~/consultant/ with templates, engagement files, and a memory.md. Before installing, confirm you are comfortable with the agent writing persistent notes to your home directory and that you (or the platform) have appropriate filesystem protections. Do not store secrets or credentials in the workspace (the skill itself warns against this). If you want additional safety, inspect the created files after setup or run the skill in an isolated account/container. Because the skill is instruction-only and requests no external credentials, there is low risk of hidden network exfiltration in the provided materials.
功能分析
Type: OpenClaw Skill Name: consultant Version: 1.0.0 The 'Consultant' skill bundle is a well-structured framework designed to help an AI agent perform business diagnosis and project scoping. It operates by maintaining a local workspace in `~/consultant/` to store engagement notes and context, using clear templates defined in files like `deliverables.md` and `memory-template.md`. The instructions in `SKILL.md` and `setup.md` focus on professional behavior and explicitly forbid the storage of secrets or unauthorized data access, with no evidence of malicious intent, data exfiltration, or suspicious execution patterns.
能力评估
Purpose & Capability
Name, description, and files (discovery, deliverables, templates, setup) align with a consulting workspace; no unrelated binaries, environment variables, or external services are requested. The declared config path (~/consultant/) matches the documented memory/workspace architecture.
Instruction Scope
SKILL.md and supporting docs instruct the agent to initialize and maintain local files under ~/consultant/, run discovery and quality gates, and update memory. All instructions stay within the consulting/use-case scope; they explicitly forbid storing secrets or unrelated personal data. The only out-of-band actions are filesystem reads/writes to the stated path.
Install Mechanism
No install spec or external downloads — instruction-only skill. No archives, package installs, or network-based install mechanisms are present.
Credentials
The skill requires no environment variables, credentials, or external config paths. This is proportionate to a local consulting assistant that stores templates and notes.
Persistence & Privilege
The skill persists state to ~/consultant/ (memory.md, engagement files, etc.) and updates it after interactions. This persistent local workspace is expected for the skill's function but is a lasting filesystem presence the user should be aware of. always:false (not force-included) and no cross-skill config modifications are present.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install consultant
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /consultant 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release with a consultant operating system for discovery, structuring, delivery, and quality control.
元数据
Slug consultant
版本 1.0.0
许可证
累计安装 2
当前安装数 2
历史版本数 1
常见问题

Consultant 是什么?

Diagnose business problems, scope engagements, and deliver decision-ready recommendations with measurable outcomes and executable plans. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 413 次。

如何安装 Consultant?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install consultant」即可一键安装,无需额外配置。

Consultant 是免费的吗?

是的,Consultant 完全免费(开源免费),可自由下载、安装和使用。

Consultant 支持哪些平台?

Consultant 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(linux, darwin, win32)。

谁开发了 Consultant?

由 Iván(@ivangdavila)开发并维护,当前版本 v1.0.0。

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