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Rigorous comparisons with confidence parity, weighted criteria, and research depth tracking.

skill openclawclawhub Free

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High Signal

Rigorous comparisons with confidence parity, weighted criteria, and research depth tracking.

⬇ 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, confidence.md, domains.md, preferences.md, traps.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 9 sections Open source page

Core Principle

Comparisons fail when confidence is uneven. Only as reliable as the weakest-researched dimension.

Protocol

Criteria → Research Parity → Confidence Check → Score → Present

1. Criteria

Load domain defaults (domains.md) Overlay user preferences from memory If unknown: "What matters most here?" Output: Ranked criteria with weights (sum = 100%)

2. Research Parity (Critical)

Research each item to equivalent depth before scoring. Track: | Criterion | Item A sources | Item B sources | 5 reviews for A but 1 for B? Research more for B first. Never score unbalanced data.

3. Confidence Check

Verify before presenting: Each item researched equally Each criterion researched equally Source quality comparable Data recency comparable Fail any? Research more OR caveat explicitly.

4. Score

Final = Σ(criterion_score × weight) — Show the math.

5. Present

🆚 [A] vs [B] 📊 CRITERIA: [ranked by weight] 📈 SCORES: [table + confidence per row] 🎯 RESULT: [Winner] by [margin] ⚠️ CAVEATS: [imbalances] 💡 IF [X] MATTERS MORE: [alt winner]

After

Note which criteria user focused on. Update preferences.md by category.

Decline When

Research parity impossible, priorities unclear, or time insufficient. Partial > misleading. References: domains.md, confidence.md, traps.md, preferences.md

Category context

Code helpers, APIs, CLIs, browser automation, testing, and developer operations.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package

5 Docs

SKILL.md Primary doc
confidence.md Docs
domains.md Docs
preferences.md Docs
traps.md Docs