Zlibrary To Notebooklm
zstmfhy/zlibrary-to-notebooklm
自动从 Z-Library 下载书籍并上传到 Google NotebookLM。支持 PDF/EPUB 格式,自动转换,一键创建知识库。
Explicit workflow for one bounded implementation using source-grounded discovery, a walking slice, evidence-gated review, validation, and commit.
$ npx skills add raine/consult-llm --skill implement -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install raine/consult-llm implement --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/raine/consult-llm.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/implement .claude/skills/implement && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "implement" agent skill from https://github.com/raine/consult-llm/tree/main/skills/implement into .claude/skills/implement/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implement", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/raine/consult-llm/tree/main/skills/implementType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add raine/consult-llm --skill implement -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install raine/consult-llm implement --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/raine/consult-llm.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/implement .agents/skills/implement && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "implement" agent skill from https://github.com/raine/consult-llm/tree/main/skills/implement into .agents/skills/implement/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implement", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add raine/consult-llm --skill implement -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install raine/consult-llm implement --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/raine/consult-llm.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/implement .cursor/skills/implement && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "implement" agent skill from https://github.com/raine/consult-llm/tree/main/skills/implement into .cursor/skills/implement/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implement", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/raine/consult-llm.git --path skills/implement--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add raine/consult-llm --skill implement -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install raine/consult-llm implement --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/raine/consult-llm.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/implement .gemini/skills/implement && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "implement" agent skill from https://github.com/raine/consult-llm/tree/main/skills/implement into .gemini/skills/implement/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implement", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install raine/consult-llm implementInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add raine/consult-llm --skill implement -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/raine/consult-llm.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/implement .github/skills/implement && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "implement" agent skill from https://github.com/raine/consult-llm/tree/main/skills/implement into .github/skills/implement/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implement", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add raine/consult-llm --skill implement -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install raine/consult-llm implement --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/raine/consult-llm.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/implement .opencode/skills/implement && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "implement" agent skill from https://github.com/raine/consult-llm/tree/main/skills/implement into .opencode/skills/implement/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implement", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
implementExplicit workflow for one bounded implementation using source-grounded discovery, a walking slice, evidence-gated review, validation, and commit.
Implement is an agent skill from raine/consult-llm. Explicit workflow for one bounded implementation using source-grounded discovery, a walking slice, evidence-gated review, validation, and commit. Use only when the user invokes /implement or another skill explicitly delegates to it. Do not trigger for ordinary coding requests, follow-up edits, fixes with an established design, or requests to amend an existing commit.
Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Knowledge Management, covering Source-grounded notebooks. The repository describes itself as: Get a second opinion from another AI model. The licence is MIT.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 69e3ecb. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
BashGlobGrepReadEditWriteFrom allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
gitFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Implement loads about 2.9k tokens when it runs. Until then it costs about 95 tokens; SKILL.md has 1,322 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check noted patterns worth knowing about, such as sudo or a known installer.
allowed-tools: Bash, Glob, Grep, Read, Edit, WriteAutomated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from raine/consult-llm at commit 69e3ecb, republished under its MIT licence (© raine). 1,322 words, ~2,854 tokens.
.claude/skills/implement/SKILL.md (or your agent's skills folder).Implement one bounded unit in the current worktree. Prefer the smallest complete change that satisfies the requested behavior. The current agent researches and implements the unit directly, so do not write the implementation twice as a code-bearing plan.
Presets increase required evidence, not architecture, abstractions, tests, or documentation.
Arguments are $ARGUMENTS.
Parse these flags before starting:
--preset light|standard|design|strict: default standard--parent-plan <path>: authoritative scope or phase brief--reviewer <selector>: consult-llm reviewer selector, repeatable--reviewers <selector,selector>: comma-separated reviewer selectors--validation <command>: expected validation commandEverything else is the implementation request.
Presets:
light: an established local pattern, focused validation, no external reviewstandard: the default, acceptance evidence and runtime exercise where
applicable, no routine external reviewdesign: a meaningful API, ownership, or architecture choice, with one
source-grounded technical-shape review before editsstrict: authentication, secrets, untrusted input, protocols, migrations,
persistence, destructive behavior, concurrency, or FFI, with boundary-focused
evidence and one final diff reviewTreat a component with a strict boundary as strict even when the selected preset is lighter. Strictness adds relevant proof. It does not justify speculative hardening.
Do not ask the user during the workflow unless continuing safely requires a material product choice, public or irreversible contract, dependency, durable-state change, trust-model change, unsafe overwrite, or major scope expansion.
Keep at most one evolving implementation brief under history/ with today's
date prefix. A brief is required only when:
design or strictA sufficient parent plan replaces the brief. Add a local note only for material facts or deviations absent from the parent plan.
Use this compact shape when a brief is needed:
# Implement: <topic>
**Goal:** <one observable outcome>
**Preset:** <preset>
**Parent plan:** <path or n/a>
**Validation:** <commands>
## Scope
- In:
- Out:
## Source facts
- `<path>:<symbol>`: <ownership, contract, or convention>
## Technical shape
- Existing mechanisms to reuse:
- Smallest complete slice:
- Acceptance evidence:
- Real trust or compatibility boundaries:
- Stop conditions:
## Accepted review findings
- <only independently reproduced findings>
## Result
- Acceptance evidence:
- Validation:
- Commit:
- Blockers:Do not pre-write source or test code in the brief. Do not create separate plans, proposal captures, feedback ledgers, or review transcripts. Update the brief only when scope, technical ownership, accepted evidence, or the result changes. Briefs are workflow records. Do not stage or commit them.
A result sentinel is a separate artifact only when a parent plan or caller requires one.
git rev-parse HEAD and inspect git status --short.--validation unless it is plainly wrong.Do not invent future consumers, extension points, defensive layers, or tests for unchanged framework behavior.
Skip this section unless the preset is design. A run receives at most one
external review. Do not run a second review to approve corrections.
Before calling consult-llm, load the consult-llm skill and follow its invocation
contract. Attach the brief or parent plan and focused source files. Use
--task review, supplied reviewer selectors when present, the quoted heredoc
terminator __CONSULT_LLM_END__, and Bash timeout 600000.
Ask whether the technical shape demonstrably conflicts with source-established ownership, behavior, contracts, or trust boundaries. Do not ask for a replacement plan or general hardening advice.
Every reported finding must include:
Tell the reviewer to return no findings when no issue meets this standard. General hardening, hypothetical edge cases, style preferences, alternative valid designs, and speculative callers are not findings.
Independently confirm each finding before accepting it. For a pre-implementation finding, compare the named plan step with the complete current source path and identify the exact contract or acceptance criterion that would fail. Reviewer assertions alone are not evidence.
Ignore findings that cannot be reproduced, have no reachable trigger, protect no accepted behavior or real boundary, duplicate lower-layer guarantees, or ask for more hardening than the demonstrated issue requires. Record only accepted findings and their smallest corrections in the brief. Do not preserve rejected feedback in a ledger.
Implement serially in the current worktree:
Continue with best judgment when a correction preserves accepted behavior, reduces complexity, follows an existing convention, and stays within scope. Stop only when a stop condition from the opening section fires.
Revisit the technical shape when implementation introduces a generic mechanism, pass-through layer, one-consumer abstraction, unexplained convention deviation, or material scope growth. Prefer deletion or a smaller local form.
For every acceptance criterion, obtain concrete evidence from a focused test, manual reproduction, real process or application exercise, or source proof for a static contract.
For standard and above, exercise the changed runtime path and one representative
failure or constrained state when applicable. For strict components, verify only
the relevant input, authorization, persistence, compatibility, error,
cancellation, allocation, and destructive-state boundaries.
Audit the actual diff for:
Run all focused validation and repository-required checks.
Run one final diff review only for strict, or when the implementation materially
diverges from the technical shape or changes a public or generic framework
contract. If a design run already used its review, verify the diff directly
instead. Never create a review cycle.
Load the consult-llm skill and use the same invocation requirements from
section 2. Attach the diff, acceptance criteria, and focused source context. Ask
for deletion-first review and concrete correctness findings. Require every
finding to use the Claim, Trigger, Expected, Actual, Evidence, Smallest
correction, and Verification fields above.
The reviewer must not report hypothetical failures, speculative compatibility, defense-in-depth without a real boundary, new extensibility, unchanged framework behavior, style preferences, or alternative valid designs. A minimality finding must identify exact code that serves no accepted behavior or real boundary.
Before changing code, independently reproduce each finding through the real entry point, a safe command, or a complete source trace from a real boundary to the failure. For unsafe or destructive triggers, source proof must demonstrate the reachable path and violated invariant without executing harm. For a minimality finding, confirm the existing owner or single consumer, apply the smallest safe deletion, and rerun the relevant evidence.
Apply only the smallest correction that resolves a reproduced issue. Ignore unreproduced suggestions. Do not request follow-up review. If a reproduced fix requires redesign or scope expansion, stop and report the blocker.
Commit when acceptance evidence and required validation pass, no blocker remains, and repository instructions permit committing. Never commit workflow records.
When a result sentinel is required, follow the caller's exact path and format. Write it after committing so its commit fields are final. If the caller supplies no format, use:
# Implementation Result: <topic>
status: success | blocked | failed
head_commit: <sha or pending>
commit: <sha or pending>
validation: <commands>
validation_status: passed | failed | skipped
## Summary
- <what changed>
## Acceptance
- <criterion>: met | not met | unknown, with evidence
## Blockers
- <blocker or none>Report concisely:
## Result
- Outcome: <observable result>
- Main implementation: <owners and mechanisms reused>
- Acceptance evidence: <tests or runtime proof>
- Review: <none | accepted reproduced findings | blocker>
- Validation: <commands and results>
- Commit: <sha or reason absent>
- Remaining risks: <none or bounded demonstrated risks>
- Sentinel: <path or n/a>© raine, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/implement of raine/consult-llm.
Open the folder on GitHubat commit 69e3ecb
Implement next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Implement this skillraine/consult-llm | 140 | — | ~2.9k | Automated safety check: Notes | MIT | |
| Zlibrary To Notebooklmzstmfhy/zlibrary-to-notebooklm | 1.7k | 1 repos | ~968 | Automated safety check: Pass | MIT | |
| Multi-Source to NotebookLM Processorjoeseesun/qiaomu-anything-to-notebooklm | 6.2k | — | ~3.6k | Automated safety check: Pass | MIT | |
| Learn From Materialsdmoshehun-prog/learn-from-materials | 937 | — | ~7.9k | Automated safety check: Pass | MIT | |
| NotebookLM Research Workflowclaude-world/notebooklm-skill | 467 | — | ~1.8k | Automated safety check: Pass | MIT | |
| Nlmtmc/nlm | 390 | — | ~2.2k | Automated safety check: Notes | MIT |
zstmfhy/zlibrary-to-notebooklm
自动从 Z-Library 下载书籍并上传到 Google NotebookLM。支持 PDF/EPUB 格式,自动转换,一键创建知识库。
joeseesun/qiaomu-anything-to-notebooklm
Collects content from WeChat articles, web pages, YouTube, podcasts, documents and more, uploads it to NotebookLM and generates podcasts, slides or mind maps.
dmoshehun-prog/learn-from-materials
Turns books, PDFs, slides and web pages into a source-grounded knowledge base and an interactive learning page in English or Chinese, with quizzes, relationship maps and reusable methodology notes.
claude-world/notebooklm-skill
Creates NotebookLM notebooks from URLs, text and files, asks cited questions, runs web research and generates audio, slides, quizzes and other artifacts.
tmc/nlm
Manages Google NotebookLM notebooks via the nlm CLI. An agent skill from tmc/nlm.
agent-skills-hub/agent-skills-hub
Drives a self-hosted Open Notebook instance to organize sources into notebooks, chat with documents, generate notes and multi-speaker podcasts, and search across material.
raine/consult-llm
Multiple LLMs collaboratively brainstorm solutions, building on each other's ideas across rounds.
raine/consult-llm
The agent brainstorms with a partner LLM in alternating turns, building on each other's ideas.
raine/consult-llm
Consult an external LLM with the user's query. An agent skill from raine/consult-llm.
raine/consult-llm
How to invoke the consult-llm CLI. An agent skill from raine/consult-llm.
raine/consult-llm
LLMs propose and critique approaches, agent moderates the debate and synthesizes the best solution, then implements.
raine/consult-llm
The agent debates an opponent LLM through a multi-turn conversation, then synthesizes the best approach and implements.
Categories
Explicit workflow for one bounded implementation using source-grounded discovery, a walking slice, evidence-gated review, validation, and commit. Implement is an agent skill from raine/consult-llm. Explicit workflow for one bounded implementation using source-grounded discovery, a walking slice, evidence-gated review, validation, and commit.
Implement fits situations like: invokes /implement; another skill explicitly delegates to it; ordinary coding requests; follow-up edits.
Run `npx skills add raine/consult-llm --skill implement -a claude-code`. Or copy the skill folder (skills/implement in raine/consult-llm) into .claude/skills/implement in your project. Claude Code loads it when a task matches its description.
Run `npx skills add raine/consult-llm --skill implement -a codex`. Or copy the skill folder (skills/implement in raine/consult-llm) into .agents/skills/implement in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add raine/consult-llm --skill implement -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/implement, .gemini/skills/implement, .github/skills/implement and .opencode/skills/implement in your project.
Going by SKILL.md and its folder, Implement needs the command-line tools its instructions call (git). Its frontmatter pre-approves these tools: Bash, Glob, Grep, Read, Edit, Write.
SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
Implement is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.9k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Implement: Zlibrary To Notebooklm (zstmfhy/zlibrary-to-notebooklm, 1.7k stars), Multi-Source to NotebookLM Processor (joeseesun/qiaomu-anything-to-notebooklm, 6.2k stars), Learn From Materials (dmoshehun-prog/learn-from-materials, 937 stars) and NotebookLM Research Workflow (claude-world/notebooklm-skill, 467 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
raine (a GitHub user) maintains it in raine/consult-llm, which has 140 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on October 7, 2026.
Source: raine/consult-llm on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.