Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Evolution Drift Detector
Helps detect when AI agent skills silently mutate across inheritance chains. A skill audited safe in generation 1 may drift far from the original by generati...
skill openclawclawhub Free
Helps detect when AI agent skills silently mutate across inheritance chains. A skill audited safe in generation 1 may drift far from the original by generati...
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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.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.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.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- andyxinweiminicloud
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
A Skill Passes Audit in Gen 1. By Gen 5, It Has Network Access. Nobody Noticed.
Helps detect silent mutations in AI skills as they propagate through inheritance chains, catching drift that static analysis of the original version would miss.
Problem
Skill A is published and audited: clean. Agent B inherits skill A, makes a small tweak β adds a convenience function. Agent C inherits from B, adds error handling that happens to include an HTTP retry mechanism. Agent D inherits from C, and now has a skill with network access that the original audit never saw. Each individual change is small and reasonable. But the cumulative drift transforms a file-reading utility into something that can send data over the network. The original "verified safe" badge still applies in the marketplace β because technically it's the same skill lineage. This is evolutionary drift: small, individually benign mutations that accumulate into a fundamentally different organism. In biology, this is how species diverge. In agent ecosystems, this is how safe skills become unsafe ones without anyone raising a flag.
What This Checks
This detector traces skill lineage and computes semantic drift: Lineage reconstruction β Given a skill, trace its inheritance chain back to the original published version. Map each fork point and modification Per-generation diff β For each generation, compute a structured diff: new capabilities added, permissions changed, external dependencies introduced Capability drift score β Aggregate diffs across generations into a single drift metric. A skill that gained network access over 3 generations scores higher than one where only comments changed Mutation classification β Categorize each change: cosmetic (formatting, comments), functional (new logic), capability-expanding (new permissions, new external calls), safety-reducing (removed checks, weakened validation) Drift alert thresholds β Flag lineages where cumulative drift exceeds the scope of the original audit. "This skill has drifted 73% from the audited version"
How to Use
Input: Provide one of: A skill slug or identifier to trace its full lineage Two versions of a skill to compute drift between them A marketplace inheritance chain URL Output: A drift analysis report containing: Lineage tree with generation markers Per-generation diff summary Capability drift score (0-100) Mutation classification breakdown Re-audit recommendation: YES / WATCH / NO
Example
Input: Check drift for data-sanitizer skill (currently at generation 5) 𧬠EVOLUTION DRIFT REPORT β RE-AUDIT RECOMMENDED Lineage: data-sanitizer Gen 1: original by @securitylab (AUDITED β 2025-03-15) Gen 2: fork by @toolsmith β added CSV support Gen 3: fork by @agent-builder β added retry logic with HTTP fallback Gen 4: fork by @pipeline-dev β added remote schema fetching Gen 5: fork by @data-team β current version in marketplace Per-generation capability changes: Gen 1β2: +csv_parsing (functional, low risk) Gen 2β3: +http_requests (capability-expanding, MEDIUM risk) Added retry mechanism that makes outbound HTTP calls Gen 3β4: +remote_fetch (capability-expanding, HIGH risk) Fetches validation schemas from external URLs Gen 4β5: -input_length_check (safety-reducing, MEDIUM risk) Removed input size validation for "performance" Capability drift score: 78/100 (SIGNIFICANT) Mutation breakdown: Cosmetic: 12 changes Functional: 8 changes Capability-expanding: 2 changes β οΈ Safety-reducing: 1 change β οΈ Original audit scope: file-read, string-transform Current actual scope: file-read, string-transform, http-requests, remote-fetch, unbounded-input Verdict: RE-AUDIT RECOMMENDED The current version has capabilities (network access, remote fetching) that did not exist when the original audit was performed. The "verified" badge from Gen 1 does not cover Gen 5's behavior.
Related Tools
blast-radius-estimator β once drift is detected, use blast-radius to estimate how many agents are running the drifted version trust-decay-monitor β tracks time-based decay of audit validity; evolution-drift-detector tracks content-based decay across inheritance hollow-validation-checker β checks if validation tests are substantive; drifted skills may pass original tests that no longer cover current capabilities supply-chain-poison-detector β detects deliberately poisoned skills; drift detection catches unintentional accumulation of risk
Limitations
Lineage reconstruction depends on marketplace metadata quality β if fork relationships are not tracked, the full chain may not be recoverable. Capability drift scoring uses heuristic classification of changes, and some mutations may be miscategorized (e.g., a "functional" change that implicitly expands capabilities). The detector analyzes what changed, not whether changes are malicious β a high drift score means re-audit is warranted, not that the skill is compromised. Skills with obfuscated or dynamically generated code may resist diff analysis. This tool helps identify where audits have gone stale β it does not replace human security review.
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs
- SKILL.md