Every tool. Right on cue.
Make your AI coding agent more deliberate about context, tools, and verification.
TuckBit is an open-source Agent Skill and optional local tooling for task-aware coding workflows. It guides agents toward the relevant evidence and the necessary checks—without bypassing their own permissions.
Copy the agent install prompt · Install with a command · How it works · Benchmarks
New: optional TuckBit Observatory public preview. Inspect a synthetic demo or explicitly select one local Codex JSONL/normalized JSON export through a loopback-only browser UI. No background capture, remote server, private research receipts or verified billing claims. Local setup and limitations. Start locally with python3 scripts/dashboard_server.py --port 8765.
Public developer preview. The portable skill, metadata discovery, reversible installer, deterministic router and offline benchmark harness are available. Real cross-provider activation, live tool interception, and verified token savings are not established. See what's implemented and the public roadmap.
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Localization is opt-in and remains a preview; some technical reference content falls back to English. Localization details.
Install with your AI agent (no CLI required)
New to GitHub or terminals? Copy the text below into a coding agent that can access your project files and run commands, such as Codex, Claude Code or another compatible agent. It should explain what it will do and ask for permission before making changes.
Help me install TuckBit as an optional Agent Skill in my CURRENT project.
Source: https://github.com/MakeItEzzz555/tuck-bit
1. First inspect TuckBit's README, skills/tuck-bit/SKILL.md and installation/compatibility documentation from this official repository. Do not trust unknown mirrors.
2. Identify which coding-agent host and project skill directory I am using. Prefer a supported, project-scoped installation over a global one.
3. Show me the files and settings you would change, and ask my approval before downloads, dependency installs, file modifications or any other tool commands.
4. Prefer the documented Agent Skills installer when supported (npx skills add MakeItEzzz555/tuck-bit), or the repository's reversible Python installer with a dry run first. If neither is available, explain a manual copy option; do not invent unsupported commands.
5. Preserve existing skills/configurations. Do not overwrite them, install global hooks/MCP servers, enable telemetry, access credentials, or change unrelated projects without specific permission.
6. After approved installation, verify the project-scoped SKILL.md is present. Explain when I can ask the agent to use TuckBit and what remains unverified (installation alone does not prove automatic model activation).
If any step is unsupported or unsafe, stop and explain the alternative rather than guessing.
What this does: asks your own agent to plan and verify installation. Pasting it here does not install anything automatically, and your agent must have appropriate file/tool capabilities. No global configuration changes are authorized by this prompt. Detailed prompt and safety notes.
Install with a command
If you are comfortable with a terminal, first preview the portable skill:
npx skills add MakeItEzzz555/tuck-bit --list
Then install it with the community Agent Skills installer (select the client and scope it supports):
npx skills add MakeItEzzz555/tuck-bit
Installation is distinct from successful model-driven activation. Inspect the source first; don't grant unexpected filesystem, credential or network access. For a dry-run project-scoped Python installer and rollback instructions, see install details and compatibility.
Why TuckBit exists
A simple coding request can become repeated repository scans, entire tool catalogs in context, several agents rereading the same files, or unnecessary test loops. TuckBit's goal is to reduce unproductive work, not required reasoning or checks.
| Without task-aware guidance | TuckBit's intended guidance |
|---|
| Load everything before you know what's needed | Discover only relevant skills, files and tools |
| Delegate small changes to several agents | Start with one worker; parallelize only independent work |
| Repeat reads and tests without inspecting inputs | Reuse valid evidence; rerun checks when dependencies change |
| Optimize token counts regardless of quality | Preserve correctness, approval boundaries and mandatory verification |
These are design goals and guidance, not measured before/after outcomes. Benchmark methodology · Public example.
以上为 README 的开头部分。其余内容请阅读原文。 查看完整 README ↗
