Dianping Local-Life Decision Guide for Openclaw

An Openclaw Skills assistant that decodes Dianping ratings, flags suspicious review patterns, and recommends safer local-life merchant choices.

zhangifonly
v1.0.0
Jul 11, 2026
0
695
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install dazhong

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install dazhong using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is Dianping Local-Life Decision Guide?

This Openclaw Skills module turns Dianping ratings, list signals, and review content into a practical local-life decision workflow.

It teaches an agent to distinguish real consumer signal from score inflation, sponsored-review patterns, and promotional store copy, then return a ranked shortlist with risk notes, rationale, and backups.

Dianping Local-Life Decision Guide Use Cases

  • Choosing a restaurant for a meetup, banquet, or quick meal when you need a budget-aware shortlist.
  • Verifying whether a 4.8+ score is trustworthy or inflated by review spikes and soft-ad patterns.
  • Comparing Dianping list signals such as Must-Eat, Black Pearl, and star ratings against real review content.
  • Checking whether a new store's high score and short collection window indicate elevated risk.
  • Advising a merchant on how to respond to negative reviews without sounding emotional or evasive.

How Dianping Local-Life Decision Guide Works

  1. Capture the decision context: scene, budget, location, number of people, and any non-negotiable constraints.
  2. Identify the relevant ranking lens: Must-Eat, Black Pearl, star rating, or category-specific local lists.
  3. Evaluate score quality using review timing, content specificity, low-value praise, and freshness from the latest 30 days.
  4. Inspect merchant clues such as signature dishes, average spend, queue or reservation needs, photo and text consistency, and response quality.
  5. Score risk and fit, then return three verified options with reasons and a backup plan; if asked, provide merchant-facing response guidance.

Dianping Local-Life Decision Guide Setup

This skill is content-driven and has no package dependencies. Add it to your Openclaw Skills workspace, then pass the agent merchant pages, review snippets, screenshots, or copied text for analysis.

mkdir -p <SKILL_DIR>
cp SKILL.md <SKILL_DIR>/dianping-local-life-decision-guide.md
# Restart or reload your Openclaw Skills runtime

For best results, include the scene, budget, location, and any recent review excerpts when invoking the skill.

Dianping Local-Life Decision Guide Data Schema & Taxonomy

This skill is reasoning-first and does not generate persistent files by default. If you persist output, store it as Markdown or JSON reports using the following taxonomy.

Field Purpose Notes
scene Decision context meetup, banquet, quick meal, family dinner
budget Spending constraint per-person or total budget
location Geographic filter district, distance, accessibility
ranking_lens List type being interpreted Must-Eat, Black Pearl, star rating
review_freshness Recency weighting latest 30 days preferred
authenticity_flags Suspicion indicators review spikes, template language, photo mismatch
merchant_fit Product-market fit signature dishes, average spend, queue pressure
merchant_response Service behavior signal response quality to negative reviews
risk_level Overall confidence low, medium, high
recommendation Final output top 3 options plus fallback

Metadata tags used by the skill:

  • dianping
  • local-life
  • restaurant
  • review
  • rating

Dianping Local-Life Decision Guide Advanced Features

  • Review spike detection and score inflation heuristics.
  • Sponsored-review fingerprinting from timing, phrasing, and photo patterns.
  • Freshness-first weighting for the latest 30 days of feedback.
  • Queue and preorder risk checks for peak-time planning.
  • Three-option recommendation sets with backup alternatives.
  • Merchant-facing reply guidance that protects credibility.
  • Context-sensitive advice for meetups, banquets, and quick meals.
  • Openclaw Skills-ready reasoning for local-life decision support.

SKILL.md


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