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Self-Improving Sales — 技能工具

v1.0.0

Captures pipeline leaks, objection patterns, pricing errors, forecast misses, competitor shifts, and deal velocity drops to enable continuous sales improveme...

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by @jose-compu (José I. O.)·MIT-0
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License
MIT-0
最后更新
2026/4/14
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OpenClaw
安全
high confidence
The skill's files, scripts, and hooks are coherent with its stated purpose (capturing and promoting sales learnings); it does not request credentials or perform external network actions, but you should review and control hook activation and where logs are stored to avoid accidental exposure of sensitive data.
评估建议
This skill appears to do what it says: local reminders, keyword detection, and scaffolding for sales learnings. Before enabling it: (1) Inspect the scripts (activator.sh, error-detector.sh, extract-skill.sh) to confirm you are comfortable with local file writes; (2) Do not enable the PostToolUse / error-detector hook in environments where command/tool output may contain PII or confidential data — prefer only the lightweight activator hook; (3) If you plan to run the manual git clone, verify the ...
详细分析 ▾
用途与能力
The skill claims to capture sales learnings and expose helpers and hooks for that purpose; the code (activator, error detector, extract-skill) and the OpenClaw hook handlers implement exactly those behaviors (reminders, keyword detection, scaffold creation). No unrelated credentials, binaries, or platform access are requested.
指令范围
Runtime instructions and scripts create and write local markdown logs (.learnings/*), inject a virtual reminder file at agent bootstrap, and (optionally) run a PostToolUse detector that reads the CLAUDE_TOOL_OUTPUT environment variable to look for sales keywords. The skill explicitly warns not to log PII, but the error-detector reads tool output (which can contain sensitive content) — the detector only prints a short reminder and does not transmit data, but you should avoid enabling PostToolUse in sensitive contexts or ensure the tool output is sanitized.
安装机制
There is no automated installer spec; the skill is instruction-first and comes with local scripts and hooks. Manual install guidance references cloning from a GitHub repo (a user account). Cloning from an unknown repo is a standard risk — review the repository and included scripts before running them. No remote downloads or installers are executed automatically by the skill itself.
凭证需求
The skill requests no environment variables or credentials. It does rely on runtime environment vars provided by hosting agents (e.g., CLAUDE_TOOL_OUTPUT) for detection, which are not declared as required but are expected in the hook workflow. There are no requests for cloud keys, tokens, or unrelated secrets.
持久化与权限
always is false and the skill's hooks are opt-in. The hook handlers inject a virtual reminder file at agent bootstrap and the scripts create local files under the workspace or ./skills when run — they do not alter other skills' configurations or request permanent elevated privileges. Enabling the hook (openclaw hooks enable ...) is an explicit user action.
安全有层次,运行前请审查代码。

License

MIT-0

可自由使用、修改和再分发,无需署名。

运行时依赖

无特殊依赖

版本

latestv1.0.02026/4/14

Initial release of the self-improving-sales skill. - Automatically logs pipeline leaks, objection patterns, pricing errors, forecast misses, competitor shifts, and deal velocity drops to markdown files for continuous sales improvement. - Guides users to initialise `.learnings/` directory and files (`LEARNINGS.md`, `DEAL_ISSUES.md`, `FEATURE_REQUESTS.md`) without overwriting existing data. - Provides quick-reference actions for common sales scenarios (e.g., stuck deals, recurring objections, lost deals). - Details standards for logging format, anonymization of sensitive info, and when/how to promote learnings to battle cards, scripts, or frameworks. - Supports integration with OpenClaw or generic agent platforms, including hook for session reminders.

● 无害

安装命令 点击复制

官方npx clawhub@latest install self-improving-sales
镜像加速npx clawhub@latest install self-improving-sales --registry https://cn.clawhub-mirror.com

技能文档

Log sales-specific learnings, deal issues, and feature requests to markdown files for continuous improvement. Captures pipeline leaks, objection patterns, pricing errors, forecast misses, competitor shifts, and deal velocity drops. Important learnings get promoted to battle cards, objection handling scripts, pricing playbooks, or qualification frameworks (MEDDIC/BANT).

First-Use Initialisation

Before logging anything, ensure the .learnings/ directory and files exist in the project or workspace root. If any are missing, create them:

mkdir -p .learnings
[ -f .learnings/LEARNINGS.md ] || printf "# Sales Learnings\n\nObjection patterns, competitor intelligence, pipeline insights, qualification gaps, and deal execution lessons captured during sales operations.\n\nCategories: pipeline_leak | objection_pattern | pricing_error | forecast_miss | competitor_shift | deal_velocity_drop\nAreas: prospecting | qualification | discovery | proposal | negotiation | closing | renewal\n\n---\n" > .learnings/LEARNINGS.md
[ -f .learnings/DEAL_ISSUES.md ] || printf "# Deal Issues Log\n\nLost deals, pipeline leaks, pricing errors, forecast misses, and deal execution failures.\n\n---\n" > .learnings/DEAL_ISSUES.md
[ -f .learnings/FEATURE_REQUESTS.md ] || printf "# Feature Requests\n\nSales tools, CRM automation, competitive intelligence, and pipeline management capabilities requested during sales operations.\n\n---\n" > .learnings/FEATURE_REQUESTS.md

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

SituationAction
Deal stuck in same stage >30 daysLog to .learnings/DEAL_ISSUES.md with pipeline_leak category
Objection you couldn't handleLog to .learnings/LEARNINGS.md with category objection_pattern
Pricing mistake discoveredLog to .learnings/DEAL_ISSUES.md with pricing_error category
Forecast missed by >20%Log to .learnings/DEAL_ISSUES.md with forecast_miss category
Lost deal to competitorLog to .learnings/LEARNINGS.md with category competitor_shift
Discount over threshold requestedLog to .learnings/DEAL_ISSUES.md with pricing_error category
Recurring objection across dealsLink with See Also, consider priority bump
Broadly applicable insightPromote to battle card, objection handler, or pricing playbook
Qualification gap identifiedPromote to MEDDIC/BANT framework update

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:

Learning TypePromote ToExample
Objection patternsObjection handling scripts"When prospect says 'too expensive', reframe to ROI"
Competitor intelligenceBattle cards"Competitor X launched free tier — counter with migration cost"
Qualification gapsMEDDIC/BANT frameworks"Always identify economic buyer before demo"
Pricing patternsPricing playbooks"Never discount >15% without VP approval and multi-year commit"
Win/loss patternsDeal review templates"Deals without champion identified by Stage 3 close at 12%"
Process improvementsAGENTS.md"Update CRM within 24 hours of every meeting"

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:

  • Log to .learnings/DEAL_ISSUES.md, LEARNINGS.md, or FEATURE_REQUESTS.md
  • 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:

CategoryUse When
pipeline_leakDeals consistently falling out at a specific stage
objection_patternSame objection surfacing across multiple deals
pricing_errorQuoting wrong price, unapproved discount, packaging mistake
forecast_missPredicted close date or amount significantly off actual
competitor_shiftCompetitor launches feature, changes pricing, or wins pattern
deal_velocity_dropDeals taking longer than historical average to progress

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:

  • Change Status: pendingStatus: resolved
  • 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

PriorityWhen to UseSales Examples
criticalDeal >$500K at risk, data integrity issue, compliance violationEnterprise deal at risk of loss, CRM data corruption, contract pricing error affecting multiple deals
highRecurring objection pattern, forecast miss >20%, competitive threatSame objection losing 3+ deals, quarterly forecast off by 25%, competitor winning all deals in a segment
mediumPipeline hygiene, process improvement, single deal coachingDeals not advancing past discovery, reps not updating CRM, proposal template outdated
lowDocumentation, minor CRM fix, process tweakField label change, report format update, email template refresh

Area Tags

Use to filter learnings by sales stage:

AreaScope
prospectingLead generation, outbound sequences, ICP targeting, SDR handoff
qualificationMEDDIC/BANT scoring, stage gate criteria, champion identification
discoveryPain identification, business case building, stakeholder mapping
proposalPricing, packaging, SOW creation, legal review, procurement
negotiationDiscount requests, contract terms, multi-year commits, procurement
closingFinal approval, signature, procurement, legal, security review
renewalExpansion, upsell, churn prevention, customer success handoff

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

TargetWhat Belongs There
Battle cardsCompetitive positioning, differentiation, trap-setting questions
Objection handling scriptsProven responses with context, follow-up questions, proof points
Pricing playbooksDiscount guardrails, packaging options, negotiation tactics
MEDDIC/BANT frameworksQualification checklists, stage gate criteria, champion tests
Deal review templatesWin/loss analysis structure, pipeline review agendas
AGENTS.mdAutomated CRM workflows, deal scoring rules

How to Promote

  • Distill the learning into a concise, actionable asset
  • Add to appropriate target (battle card entry, objection script, playbook rule)
  • Update original entry:
- Change Status: pendingStatus: 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:

  • Acknowledge: "That makes sense — most companies in your space do."
  • Probe: "How well is it handling [specific pain point]?"
  • Differentiate: "Where we're different is [unique capability] which means [business outcome]."
  • 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:

  • Search first: grep -r "keyword" .learnings/
  • Link entries: Add See Also: DEAL-20250110-001 in Metadata
  • Bump priority if issue keeps recurring
  • 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.

  • For each candidate, use pattern_key as the dedupe key.
  • Search .learnings/LEARNINGS.md for existing entry: grep -n "Pattern-Key: " .learnings/LEARNINGS.md
  • If found: increment Recurrence-Count, update Last-Seen, add See Also links.
  • 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

ScriptHook TypePurpose
scripts/activator.shUserPromptSubmitReminds to evaluate sales learnings after tasks
scripts/error-detector.shPostToolUse (Bash)Triggers on deal issues, competitor mentions, pipeline signals
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

CriterionDescription
RecurringSame objection or deal pattern in 3+ deals or segments
VerifiedStatus is resolved with proven response or process fix
Non-obviousRequired actual deal experience or loss to discover
Broadly applicableNot deal-specific; useful across segments or verticals
User-flaggedUser says "save this as a skill" or similar

Extraction Workflow

  • Identify candidate: Learning meets extraction criteria
  • 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
   
  • Customize SKILL.md: Fill in template with sales-specific content
  • Update learning: Set status to promoted_to_skill, add Skill-Path
  • 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

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

Multi-Agent Support

AgentActivationDetection
Claude CodeHooks (UserPromptSubmit, PostToolUse)Automatic via error-detector.sh
Codex CLIHooks (same pattern)Automatic via hook scripts
GitHub CopilotManual (.github/copilot-instructions.md)Manual review
OpenClawWorkspace injection + inter-agent messagingVia session tools

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

数据来源:ClawHub ↗ · 中文优化:龙虾技能库
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