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Public repository for Agent Skills
Leonxlnx/unlazy
unlazy is a tool for DeepSeek Harness. Anti-laziness skill for AI agents. Core: the Depth Tree method, which splits a task N layers deep and gives every leaf the full time budget of the whole task, so effort multiplies with depth. Grounded in 2025-2026 research on model laziness, underthinking and premature completion.

REVIEW SCORECARD
✓ 无Risky检出 · 自动化扫描结果仅供参考,非官方背书
AI DEEP REVIEW
A well-documented anti-laziness skill with runnable verification gates, but its unkeyed evidence binding and shell-execu
README documents a Node 16+ checker with no third-party runtime deps, a parser with explicit rejection rules, a lint script, and a versioned SHA-256 evidence fingerprint, indicating deliberate engineering, though no test suite or CI is mentioned.
The checker executes arbitrary shell code from CHECK: lines and the README itself admits evidence is unkeyed and forgeable by anyone who can edit the ledger, but it mitigates with an approval store outside the repo, a non-executing --status mode, and explicit PATH/shell warnings.
It targets a real and commonly reported pain point (premature completion and underthinking in agentic coding work) with a concrete acceptance-ledger workflow rather than vague prompt advice.
Last updated 2026-09-03 with an unreleased 2.1.0 change set and a CHANGELOG, and the repo is not archived, indicating active development, though the README notes no tagged GitHub release exists.
The README covers install for multiple agents, a quick start, a full gate contract example, shell/PATH caveats, and links to references and templates, though the security section is visibly truncated mid-sentence.
Generated by AI after reading the project README, as a decision aid; neutral scores are given when information is thin. Not an official endorsement.
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前往仓库INSTALL REFERENCE
npx skills add Leonxlnx/unlazyThis command comes from an explicit install reference in the README and is provided for reference only — it is never auto-executed by a DSH host.
PROJECT TOPICS
VALIDATION LADDER
FAQ
Anti-laziness skill for AI agents. Core: the Depth Tree method, which splits a task N layers deep and gives every leaf the full time budget of the whole task, so effort multiplies with depth. Grounded in 2025-2026 resear
unlazy has 3,246 stars and 219 forks on GitHub, last updated 2026-09-03.
unlazy is distributed under the MIT license.
unlazy is listed in the DSH Universe directory as a tool for DeepSeek Harness. This plugin is listed in the DSH Universe directory and covered by its validation pipeline.
CLASSIFICATION EVIDENCE
System reads GitHub Topics first, then compares against the in-site category dictionary and word-root rules. Current match:skill。