Tencent SkillHub · Data Analysis

Competing

Improve systematically by analyzing losses, studying winners, and tracking progress against rivals in any competitive domain.

skill openclawclawhub Free

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High Signal

Improve systematically by analyzing losses, studying winners, and tracking progress against rivals in any competitive domain.

⬇ 0 downloads ★ 0 stars Unverified but indexed

Install for OpenClaw

Quick setup

Download the package from Yavira.
Extract the archive and review SKILL.md first.
Import or place the package into your OpenClaw setup.

Requirements

Target platform: OpenClaw
Install method: Manual import
Extraction: Extract archive
Prerequisites: OpenClaw
Primary doc: SKILL.md

Package facts

Download mode: Yavira redirect
Package format: ZIP package
Source platform: Tencent SkillHub
What's included: SKILL.md, analysis.md, domains.md, feedback.md, tracking.md

Validation

Use the Yavira download entry.
Review SKILL.md after the package is downloaded.
Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

Download the package from Yavira.
Extract it into a folder your agent can access.
Paste one of the prompts below and point your agent at the extracted folder.

New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.

Upgrade existing

I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.

Open Send to Agent page Open JSON manifest Open Markdown brief

Trust & source

Release facts

Source: Tencent SkillHub
Verification: Indexed source record
Version: 1.0.0

Provenance

Publisher: ivangdavila
Source page: View original listing
Canonical URL: Open canonical page

Documentation

ClawHub primary doc Primary doc: SKILL.md 6 sections Open source page

Core Framework

Competition is a learning accelerator. Every loss contains the lesson that wins don't. Analyze the Loss — Don't just lose, understand WHY Study the Winner — What did they do that you didn't? Track the Delta — Measure the gap, watch it shrink Iterate — Apply lessons, compete again, repeat

The Post-Loss Protocol

After any competitive loss, extract value: QuestionPurposeAt what moment did the outcome shift?Find the decision pointWhat did they do that I didn't?Identify the winning moveWhat would I do differently?Formulate the lessonIs this a pattern?Check history for repeats Don't rationalize. Don't blame externals. Extract the actionable insight.

Tracking (What to Measure)

Create a tracking folder in the user's workspace: ~/competing/ ├── domains/ # Per-domain tracking ├── rivals.md # Opponent profiles ├── log.md # Win/loss log with lessons └── progress.md # Metrics over time For each domain, track: Win/loss record with dates Specific losses analyzed (who, why, lesson) Patterns identified (recurring weaknesses) Progress metrics (are lessons translating to wins?)

Rival Intelligence

Know your competition: Profile rivals — Their strengths, weaknesses, tendencies Monitor changes — When they improve or change strategy Find their edge — What specifically makes them beat you? Study up — Find examples of them losing, analyze what worked

Quick Reference

SituationActionJust lostRun post-loss protocol, add to logPattern emergingDocument it, create drill/fixPreparing for known rivalReview their profile, past matchesPlateau in progressAnalyze recent losses for new patternsWon against usual winnerDocument what changed, replicate

Load Reference

NeedFileDomain-specific strategiesdomains.mdDeep loss analysis frameworkanalysis.mdProgress tracking templatestracking.mdFeedback loop mechanicsfeedback.md

Category context

Data access, storage, extraction, analysis, reporting, and insight generation.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package

5 Docs

SKILL.md Primary doc
analysis.md Docs
domains.md Docs
feedback.md Docs
tracking.md Docs