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agistack

Lead

by AGIstack · GitHub ↗ · v2.1.1 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install lead
Description
Qualify, prioritize, and advance sales prospects into the next best action. Built for founders, sales reps, and operators who need sharper lead judgment, fas...
README (SKILL.md)

Lead

⚠️ Scope Notice
This skill is for sales lead qualification only.
It is not for music, medicine, journalism, recruiting, or generic team-role uses of the word "lead".

Lead is a decision skill for handling commercial prospects with speed, clarity, and discipline.

Use this skill when you need to:

  • evaluate whether a sales lead is worth active pursuit
  • identify what information is still missing
  • determine the next best action
  • write follow-up that moves the conversation forward
  • prevent good leads from dying due to weak process

Lead vs Prospect

Use Prospect before contact.
Use Lead after engagement begins.

Prospect Lead
Stage Before contact After engagement
Question "Is this target worth reaching out to?" "Should I keep pursuing this person?"
Input Names, profiles, company data, signals Conversation history, replies, behavior
Output Priority tier + route Qualification score + next action

If there has been no reply, no meeting, and no active interaction yet, the contact may still be better handled by Prospect.

What this skill does

Lead helps transform raw prospect information into clear action.

It can:

  • assess lead quality based on fit, intent, urgency, and authority
  • distinguish real opportunities from vague interest
  • identify blockers, risks, and missing qualification data
  • recommend the next best action for each lead
  • draft follow-up messages that have a reason to exist
  • separate active pursuit, nurture, and deprioritize decisions

Best use cases

  • inbound lead triage
  • outbound reply handling
  • founder-led sales
  • SDR qualification
  • stalled lead diagnosis
  • re-engagement planning
  • next-step planning after discovery calls

What to provide

Useful input includes:

  • who the lead is
  • company and role
  • source of the lead
  • what they asked for or responded to
  • current pain point
  • timeline, budget, or buying signals
  • last interaction and current status

What this skill should return

A strong response should usually include:

  1. Lead assessment

    • hot / warm / cold
    • strong fit / unclear fit / weak fit
  2. Missing information

    • what must be clarified before investing more time
  3. Risks or friction

    • weak authority
    • weak urgency
    • weak problem clarity
    • weak timing
    • weak follow-through
  4. Next best action

    • pursue now
    • qualify further
    • nurture
    • deprioritize
  5. Optional follow-up draft

    • short
    • relevant
    • specific
    • non-annoying

Decision principles

  • Do not confuse activity with opportunity.
  • Do not treat every lead as pipeline.
  • Do not push unclear leads into active pursuit too early.
  • Preserve momentum when signal is strong.
  • Reduce wasted effort when fit or timing is weak.
  • Always prefer a clear next step over vague optimism.

Execution Protocol (for AI agents)

When user provides lead information, follow this sequence.

Step 1: Extract context

Parse input for:

  • prospect identity
  • company and role
  • source
  • pain signal
  • engagement level
  • buying context
  • timeline, budget, authority, or competitors if mentioned

Step 2: Score only from visible evidence

Assign 0-10 for each dimension using only evidence present in the input.

Fit Score

  • ICP match
  • problem-product alignment
  • role relevance

Intent Score

  • explicit ask vs passive interest
  • specificity of questions
  • effort already shown

Urgency Score

  • timeline mentioned
  • pain severity
  • trigger event or active problem

Authority Score

  • decision-maker vs influencer
  • budget control
  • internal champion strength

If evidence is missing, do not guess. Score conservatively.

Step 3: Identify gaps

List unknowns that block sound judgment, such as:

  • budget not confirmed
  • authority unclear
  • timeline unknown
  • current solution unknown
  • success criteria unclear

Step 4: Recommend action

Use the score as guidance, not certainty.

  • 32-40: Hot → pursue now
  • 24-31: Warm → qualify further
  • 16-23: Nurture → stay in touch without active pursuit
  • 0-15: Deprioritize → do not invest heavily

Step 5: Draft follow-up if needed

If pursue now or qualify further is recommended:

  • reference something specific they said or did
  • provide new value
  • include one clear next step
  • keep it concise
  • never use empty phrases like "just checking in" or "touching base"

Upstream Check (for AI agents)

If user provides only:

  • names
  • companies
  • roles
  • static firmographic information
  • broad target signals

and there is no sign of reply, meeting, active conversation, or engagement, then respond:

"This may still be a prospect rather than an active lead. Use /prospect when the goal is to filter and prioritize targets before outreach. Use Lead only once engagement has begun."

Activation Rules (for AI agents)

Use this skill when the user is asking about:

  • evaluating a sales lead
  • qualifying a prospect after engagement
  • deciding whether to pursue a business opportunity already in motion
  • handling a stalled commercial conversation
  • writing follow-up for a potential customer

Do NOT use this skill for:

  • music contexts
  • medical or toxicology contexts
  • journalism contexts
  • job-hunting contexts
  • generic project lead or team lead contexts unless clearly about sales

If context is ambiguous

Ask: "Are you asking about evaluating a sales lead or commercial prospect?"

When NOT to use Lead

Do not use this skill when:

  • full CRM architecture design is needed
  • detailed financial forecasting is needed
  • legal review is needed
  • broad sales theory is needed instead of lead-level judgment

Works Well With

  • /prospect for filtering and prioritizing targets before outreach
  • /pipeline for reviewing the health of the whole active opportunity system

Output style

Responses should be:

  • concise
  • commercial
  • diagnostic
  • actionable
  • honest about uncertainty

Never inflate lead quality without evidence.
Never recommend aggressive follow-up without a reason.
Never fabricate authority, urgency, budget, or buying intent.

Usage Guidance
This skill appears internally consistent and low-risk: it only processes user-provided lead information and does not ask for credentials or install software. Before installing, confirm the skill source or homepage if provenance matters (skill.json lists https://clawhub.ai but registry metadata shows none). When using the skill, avoid submitting sensitive personal data or confidential customer information unless you're comfortable sharing it with the agent, and remember the skill will generate follow-up text from whatever you provide. If you need tighter privacy or auditability, prefer skills from known publishers or request an auditable provenance/maintainer record.
Capability Analysis
Type: OpenClaw Skill Name: lead Version: 2.1.1 The 'Lead' skill bundle is a purely instructional set of markdown and configuration files designed to guide an AI agent through sales lead qualification and prioritization. It contains no executable code, external dependencies, or instructions to access sensitive system data, and its logic is strictly confined to the stated purpose of business process automation (skill.md, skill.json).
Capability Assessment
Purpose & Capability
Name, description, and declared capabilities (lead qualification, gap identification, action recommendation, follow-up drafting) match the SKILL.md instructions and example usage. The skill does not request unrelated credentials or binaries. Minor metadata inconsistency: registry metadata at the top lists no homepage while skill.json contains a homepage URL (https://clawhub.ai); this is an administrative discrepancy but does not affect functionality.
Instruction Scope
Runtime instructions are narrowly scoped to parsing user-provided lead information, scoring observable dimensions (fit, intent, urgency, authority), identifying gaps, recommending actions, and drafting concise follow-ups. The execution protocol explicitly instructs the agent to score only from visible evidence and not to guess, and does not direct the agent to read local files, system state, or external endpoints beyond user input.
Install Mechanism
No install specification and no code files are present (instruction-only). This is the lowest-risk model: nothing is downloaded or written to disk by the skill itself.
Credentials
The skill requires no environment variables, credentials, or config paths. All recommended inputs are user-provided lead data (names, role, messages, firmographics). There are no disproportionate secret or system access requests.
Persistence & Privilege
The skill is not marked always:true and does not request any persistent installation or modifications to other skills. It can be invoked by the agent (default behavior) but has no elevated privileges or background persistence.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install lead
  3. After installation, invoke the skill by name or use /lead
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v2.1.1
- Added a new README.md file. - Updated language in the Upstream Check to clarify when to use `/prospect` versus Lead, and note the requirement for engagement. - Added `/pipeline` reference under "Works Well With" for integration guidance. - No changes to core skill logic or functionality.
v2.1.0
**Version 2.1.0 Summary:** Introduces clearer guidance on when to use Lead vs Prospect, and adds upstream filtering. - Added a new "Lead vs Prospect" section to clarify stage-appropriate usage. - Introduced an "Upstream Check" to suggest using Prospect when only pre-engagement info is present. - Updated activation rules: use Lead skill only after there has been engagement. - Added interoperability note: recommends `@dpetcr/prospect` for pre-outreach targeting. - No changes to scoring or decision logic.
v2.0.0
**Lead 2.0.0 – Major update for clarity, precision, and decisive sales lead handling.** - Scope narrowed strictly to sales lead qualification (not music, medicine, journalism, or generic roles). - New decision framework: clear scoring and step-by-step protocol for fit, intent, urgency, and authority. - Explicit next-action recommendations (pursue, qualify, nurture, deprioritize) based on evidence; avoids guesswork. - Improved prompts and output guidelines for actionable, non-generic follow-up drafts. - Strong boundaries and use-case rules for when to apply the skill and when not to.
v1.0.0
Initial release with four-file structure
Metadata
Slug lead
Version 2.1.1
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 4
Frequently Asked Questions

What is Lead?

Qualify, prioritize, and advance sales prospects into the next best action. Built for founders, sales reps, and operators who need sharper lead judgment, fas... It is an AI Agent Skill for Claude Code / OpenClaw, with 366 downloads so far.

How do I install Lead?

Run "/install lead" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Lead free?

Yes, Lead is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Lead support?

Lead is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Lead?

It is built and maintained by AGIstack (@agistack); the current version is v2.1.1.

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