Self-Improving Sales Skill

Never overwrite existing files. This is a no-op if .learnings/ is already initialised.

Do not log customer PII, exact contract values, or confidential deal terms. Use deal size ranges (e.g., "$100K-$250K") and anonymize company names when sharing externally.

If you want automatic reminders, use the opt-in hook workflow described in Hook Integration.

Quick Reference

OpenClaw Setup (Recommended)

OpenClaw is the primary platform for this skill. It uses workspace-based prompt injection with automatic skill loading.

Installation

Via ClawdHub (recommended):

clawdhub install self-improving-sales

Manual:

git clone https://github.com/jose-compu/self-improving-sales.git ~/.openclaw/skills/self-improving-sales

Workspace Structure

OpenClaw injects these files into every session:

~/.openclaw/workspace/
├── AGENTS.md          # Multi-agent workflows, delegation patterns
├── SOUL.md            # Behavioral guidelines, personality, principles
├── TOOLS.md           # Tool capabilities, integration gotchas
├── MEMORY.md          # Long-term memory (main session only)
├── memory/            # Daily memory files
│   └── YYYY-MM-DD.md
└── .learnings/        # This skill's log files
    ├── LEARNINGS.md
    ├── DEAL_ISSUES.md
    └── FEATURE_REQUESTS.md

Create Learning Files

mkdir -p ~/.openclaw/workspace/.learnings

Then create the log files (or copy from assets/):

• LEARNINGS.md — objection patterns, competitor intelligence, pipeline insights, deal velocity
• DEAL_ISSUES.md — pipeline leaks, lost deals, pricing errors, forecast misses
• FEATURE_REQUESTS.md — CRM automation, competitive intelligence tools, pipeline analytics

Promotion Targets

When sales learnings prove broadly applicable, promote them:

Optional: Enable Hook

For automatic reminders at session start:

cp -r hooks/openclaw ~/.openclaw/hooks/self-improving-sales
openclaw hooks enable self-improving-sales

See references/openclaw-integration.md for complete details.

Generic Setup (Other Agents)

For Claude Code, Codex, Copilot, or other agents, create .learnings/ in the project or workspace root:

mkdir -p .learnings

Create the files inline using the headers shown above.

Add reference to agent files

Add to AGENTS.md, CLAUDE.md, or .github/copilot-instructions.md:

Self-Improving Sales Workflow

When sales issues or patterns are discovered:

1. Log to .learnings/DEAL_ISSUES.md, LEARNINGS.md, or FEATURE_REQUESTS.md
2. Review and promote broadly applicable learnings to:
   • Battle cards — competitive positioning and differentiation
   • Objection handling scripts — proven responses to common objections
   • Pricing playbooks — discount policies, packaging, and negotiation guardrails
   • Qualification frameworks — MEDDIC/BANT checklists and stage gate criteria

Logging Format

Learning Entry [LRN-YYYYMMDD-XXX]

Append to .learnings/LEARNINGS.md:

## [LRN-YYYYMMDD-XXX] category

**Logged**: ISO-8601 timestamp
**Priority**: low | medium | high | critical
**Status**: pending
**Area**: prospecting | qualification | discovery | proposal | negotiation | closing | renewal

### Summary
One-line description of the sales insight

### Details
Full context: what happened in the deal, why the outcome occurred, what the
correct approach or response is. Include specific objection language, competitor
positioning, or deal dynamics.

### Deal Context

**Objection / Situation:**
> Exact quote or paraphrase of the objection, competitor claim, or deal blocker

**Response Used:**
> What was said or done in response

**Outcome:**
Won | Lost | Stalled | Pushed — and why

### Suggested Action
Specific change to pitch, process, pricing, or qualification criteria

### Metadata
- Source: call_transcript | deal_review | win_loss_analysis | pipeline_review | competitor_intel | forecast_review
- Deal Size: $50K-$100K | $100K-$250K | $250K-$500K | $500K+ (use ranges)
- Segment: SMB | mid_market | enterprise | strategic
- Industry: technology | financial_services | healthcare | manufacturing | retail | other
- Related Deals: DEAL-YYYYMMDD-XXX (if linked to a deal issue)
- Tags: tag1, tag2
- See Also: LRN-20250410-001 (if related to existing entry)
- Pattern-Key: objection.budget_freeze | competitor.free_tier (optional)
- Recurrence-Count: 1 (optional)
- First-Seen: 2025-01-15 (optional)
- Last-Seen: 2025-01-15 (optional)

---

Categories for learnings:

Deal Issue Entry [DEAL-YYYYMMDD-XXX]

Append to .learnings/DEAL_ISSUES.md:

## [DEAL-YYYYMMDD-XXX] issue_type

**Logged**: ISO-8601 timestamp
**Priority**: high
**Status**: pending
**Area**: prospecting | qualification | discovery | proposal | negotiation | closing | renewal

### Summary
Brief description of the deal issue

### Deal Details
- **Stage**: Stage where the issue occurred
- **Deal Size**: $100K-$250K (use ranges)
- **Days in Stage**: Number of days stuck or time to loss
- **Segment**: SMB | mid_market | enterprise | strategic

### What Happened
Narrative of what went wrong: missed signals, process breakdown, competitive
loss, pricing confusion, or forecast error.

### Root Cause
Why the deal was lost, stalled, or mispriced. Distinguish symptom from cause.

### Impact
- Revenue impact (range)
- Pipeline coverage impact
- Forecast accuracy impact

### Prevention
How to avoid this issue in future deals: qualification criteria, process gate,
pricing checklist, competitive preparation

### Metadata
- Trigger: pipeline_review | deal_review | win_loss_analysis | forecast_review | CRM_audit
- Competitor: competitor name (if applicable)
- Loss Reason: no_budget | no_decision | lost_to_competitor | timing | product_gap | price
- Related Files: path/to/deal_review.md
- See Also: DEAL-20250110-001 (if recurring pattern)

---

Feature Request Entry [FEAT-YYYYMMDD-XXX]

Append to .learnings/FEATURE_REQUESTS.md:

## [FEAT-YYYYMMDD-XXX] capability_name

**Logged**: ISO-8601 timestamp
**Priority**: medium
**Status**: pending
**Area**: prospecting | qualification | discovery | proposal | negotiation | closing | renewal

### Requested Capability
What sales tool, automation, or capability is needed

### User Context
Why it's needed, what workflow it improves, what revenue impact it could have

### Complexity Estimate
simple | medium | complex

### Suggested Implementation
How this could be built: CRM workflow, Slack integration, dashboard, alert system

### Metadata
- Frequency: first_time | recurring
- Related Features: existing_tool_or_feature

---

ID Generation

Format: TYPE-YYYYMMDD-XXX

• TYPE: LRN (learning), DEAL (deal issue), FEAT (feature request)
• YYYYMMDD: Current date
• XXX: Sequential number or random 3 chars (e.g., 001, A7B)

Examples: LRN-20250415-001, DEAL-20250415-A3F, FEAT-20250415-002

Resolving Entries

When an issue is addressed, update the entry:

1. Change **Status**: pending → **Status**: resolved
2. Add resolution block after Metadata:

### Resolution
- **Resolved**: 2025-01-16T09:00:00Z
- **Action Taken**: Updated battle card / revised pricing playbook / added qualification gate
- **Notes**: Rolled out to team in weekly sales meeting, updated CRM stage criteria

Other status values:

• in_progress — Actively being addressed or tested in live deals
• wont_fix — Decided not to address (add reason in Resolution notes)
• promoted — Elevated to battle card, objection script, or pricing playbook
• promoted_to_skill — Extracted as a reusable skill

Detection Triggers

Automatically log when you encounter:

Pipeline Stalls (→ deal issue with pipeline_leak):

• Deal in same stage for >30 days
• Multiple deals stalling at the same stage
• Conversion rate drop between stages
• Deals pushed from one quarter to next

Objection Patterns (→ learning with objection_pattern):

• Same objection heard in 3+ deals within a quarter
• Objection that consistently leads to no-decision outcomes
• New objection not covered by existing battle cards
• Objection specific to a segment or industry vertical

Pricing Issues (→ deal issue with pricing_error):

• Discount >20% requested by prospect
• Quoting a deprecated or incorrect pricing tier
• Competitor undercut by >30% on similar deal
• Custom pricing requested outside standard packaging

Forecast Misses (→ deal issue with forecast_miss):

• Quarterly forecast accuracy below 80%
• Deal close date pushed more than twice
• Commit deal lost or pushed to next quarter
• Upside deal that was actually a commit

Competitive Intelligence (→ learning with competitor_shift):

• Competitor mentioned in 3+ call transcripts in a month
• Competitor launches new product, feature, or pricing tier
• Prospect received competitive quote or evaluation
• Win rate drops against specific competitor

Deal Velocity (→ learning with deal_velocity_drop):

• Average deal cycle lengthening quarter over quarter
• Specific stage taking 2x historical average
• Deals requiring more meetings to close
• Longer legal/procurement review cycles

Priority Guidelines

Area Tags

Use to filter learnings by sales stage:

Promoting to Permanent Sales Assets

When a learning is broadly applicable (not a one-off deal quirk), promote it to permanent team assets.

When to Promote

• Objection recurs across 3+ deals in a quarter
• Competitive intelligence applies to an entire segment
• Pricing insight affects multiple deal sizes or verticals
• Qualification gap leads to predictable deal failures
• Win/loss pattern is statistically significant (10+ deals)

Promotion Targets

How to Promote

1. Distill the learning into a concise, actionable asset
2. Add to appropriate target (battle card entry, objection script, playbook rule)
3. Update original entry:
   • Change **Status**: pending → **Status**: promoted
   • Add **Promoted**: battle card (or objection script, pricing playbook, MEDDIC framework)

Promotion Examples

Learning (verbose):

Prospect said "We already have a vendor for this." We had no differentiation message ready. Lost the deal because we couldn't articulate unique value vs. incumbent. This happened in 4 deals this quarter against Vendor X.

As battle card (concise):

## Objection: "We already have a vendor"

**Response Framework:**
1. Acknowledge: "That makes sense — most companies in your space do."
2. Probe: "How well is it handling [specific pain point]?"
3. Differentiate: "Where we're different is [unique capability] which means [business outcome]."
4. Proof: "Company Y switched from [vendor] and saw [metric improvement]."

**Trap-Setting Questions:**
- "How much time does your team spend on [task our product automates]?"
- "What happens when [scenario our product handles better]?"

Learning (verbose):

Deals without an identified champion by Stage 3 close at only 12% vs. 48% for deals with a champion. We need a hard gate requiring champion identification before advancing to proposal.

As MEDDIC framework update (actionable):

## Stage Gate: Discovery → Proposal

**Required before advancing:**
- [ ] Champion identified (name, title, access level)
- [ ] Champion has confirmed the problem exists
- [ ] Champion has agreed to introduce economic buyer
- [ ] Decision criteria documented from champion conversation

**Block advancement if:** No champion identified after 3 discovery calls.
Recommend: Re-qualify or move to nurture.

Recurring Pattern Detection

If logging something similar to an existing entry:

1. Search first: grep -r "keyword" .learnings/
2. Link entries: Add **See Also**: DEAL-20250110-001 in Metadata
3. Bump priority if issue keeps recurring
4. Consider systemic fix: Recurring sales issues often indicate:
   • Missing qualification criteria (→ update MEDDIC/BANT framework)
   • Competitive gap (→ create or update battle card)
   • Pricing misalignment (→ revise pricing playbook)
   • Process breakdown (→ add CRM stage gate or automation)

Periodic Review

Review .learnings/ at natural breakpoints:

When to Review

• Before starting a new deal in the same segment or against the same competitor
• After completing quarterly business review (QBR)
• When the same objection or loss reason appears again
• Weekly during pipeline review meetings
• After each win/loss analysis

Quick Status Check

# Count pending sales issues
grep -h "Status\*\*: pending" .learnings/*.md | wc -l

# List pending high-priority deal issues
grep -B5 "Priority\*\*: high" .learnings/DEAL_ISSUES.md | grep "^## \["

# Find learnings for a specific sales stage
grep -l "Area\*\*: negotiation" .learnings/*.md

# Find all competitor-related learnings
grep -B2 "competitor_shift" .learnings/LEARNINGS.md | grep "^## \["

# List objection patterns
grep -B2 "objection_pattern" .learnings/LEARNINGS.md | grep "^## \["

Review Actions

• Resolve addressed deal issues
• Promote recurring objections to battle cards
• Link related entries across files
• Extract reusable qualification criteria as framework updates
• Update forecast model based on historical miss patterns

Simplify & Harden Feed

Ingest recurring sales patterns from simplify-and-harden into playbooks or frameworks.

1. For each candidate, use pattern_key as the dedupe key.
2. Search .learnings/LEARNINGS.md for existing entry: grep -n "Pattern-Key: <key>" .learnings/LEARNINGS.md
3. If found: increment Recurrence-Count, update Last-Seen, add See Also links.
4. If not found: create new LRN-... entry with Source: simplify-and-harden.

Promotion threshold: Recurrence-Count >= 3, seen in 2+ deals or segments, within 90-day window. Targets: battle cards, objection scripts, pricing playbooks, MEDDIC/BANT frameworks, AGENTS.md.

Hook Integration

Enable automatic reminders through agent hooks. This is opt-in.

Quick Setup (Claude Code / Codex)

Create .claude/settings.json in your project:

{
  "hooks": {
    "UserPromptSubmit": [{"matcher": "", "hooks": [{"type": "command", "command": "./skills/self-improving-sales/scripts/activator.sh"}]}],
    "PostToolUse": [{"matcher": "Bash", "hooks": [{"type": "command", "command": "./skills/self-improving-sales/scripts/error-detector.sh"}]}]
  }
}

The UserPromptSubmit hook injects a sales-focused reminder (~50-100 tokens). The PostToolUse hook detects deal-related signals (lost deals, churn, competitor mentions, forecast misses). Use only UserPromptSubmit for lower overhead.

Available Hook Scripts

See references/hooks-setup.md for detailed configuration and troubleshooting.

Automatic Skill Extraction

When a sales learning is valuable enough to become a reusable skill, extract it.

Skill Extraction Criteria

Extraction Workflow

1. Identify candidate: Learning meets extraction criteria
2. Run helper (or create manually):

   ./skills/self-improving-sales/scripts/extract-skill.sh skill-name --dry-run
   ./skills/self-improving-sales/scripts/extract-skill.sh skill-name
   

3. Customize SKILL.md: Fill in template with sales-specific content
4. Update learning: Set status to promoted_to_skill, add Skill-Path
5. Verify: Read skill in fresh session to ensure it's self-contained

Extraction Detection Triggers

In conversation: "This objection keeps coming up", "Save this competitive intel as a skill", "I keep losing deals at this stage", "Every enterprise deal has this procurement issue".

In entries: Multiple See Also links, high priority + resolved, objection_pattern or competitor_shift with broad applicability, same Pattern-Key across deals or segments.

Sales-Specific Best Practices

1. Qualify early — disqualify faster to focus pipeline on winnable deals
2. Document objections immediately — exact wording matters for battle cards
3. Update CRM same day — stale data poisons forecasts and pipeline reviews
4. Track competitor intel in real time — pricing changes and feature launches decay fast
5. Review win/loss quarterly — patterns only emerge with enough data points
6. Log the objection, not just the outcome — "we lost" is less useful than "they said X"
7. Anonymize appropriately — use deal size ranges and avoid customer PII in shared logs
8. Distinguish decision-maker objections from user objections — different responses required
9. Record what you tried — failed responses are as valuable as successful ones
10. Promote aggressively — if an objection appears in 3 deals, it deserves a battle card

Multi-Agent Support

Gitignore Options

Keep learnings local (per-rep):

.learnings/

Track learnings in repo (team-wide): Don't add to .gitignore — learnings become shared team knowledge.

Hybrid (track templates, ignore entries):

.learnings/*.md
!.learnings/.gitkeep

Stackability Contract (Standalone + Multi-Skill)

This skill is standalone-compatible and stackable with other self-improving skills.

Namespaced Logging (recommended for 2+ skills)

• Namespace for this skill: .learnings/sales/
• Keep current standalone behavior if you prefer flat files.
• Optional shared index for all skills: .learnings/INDEX.md

Required Metadata

Every new entry must include:

**Skill**: sales

Hook Arbitration (when 2+ skills are enabled)

• Use one dispatcher hook as the single entrypoint.
• Dispatcher responsibilities: route by matcher, dedupe repeated events, and rate-limit reminders.
• Suggested defaults: dedupe key = event + matcher + file + 5m_window; max 1 reminder per skill every 5 minutes.

Narrow Matcher Scope (sales)

Only trigger this skill automatically for sales signals such as:

• pipeline|opportunity|objection|close-lost|win rate
• quota|forecast|deal stage|discovery call|proposal
• explicit sales intent in user prompt

Cross-Skill Precedence

When guidance conflicts, apply:

1. security
2. engineering
3. coding
4. ai
5. user-explicit domain skill
6. meta as tie-breaker

Ownership Rules

• This skill writes only to .learnings/sales/ in stackable mode.
• It may read other skill folders for cross-linking, but should not rewrite their entries.