Workflows
46 recipes, filter by use case, license, or difficulty.
QM: prove the destructive-action denials hold in every security posture, even the loosest
Run YC's company-wide QM agent with one org-wide security posture, and prove the predeclared hard denials (recursive delete, destructive SQL, mass delete) are refused in every posture including the loosest, so loosening the posture only relaxes approvals, never the destructive-action guardrails.
pgvector on Postgres you already run: prove you picked the right distance operator
Use pgvector in the Postgres you already run instead of standing up a dedicated vector database, and prove the distance operator you query with (<-> L2, <=> cosine, or <#> inner product) matches your embeddings, so your semantic search doesn't silently rank the wrong rows first.
One AGENTS.md, no drift: prove CLAUDE.md is a real symlink and the generated files are in sync
Keep one AGENTS.md as the single source of agent rules, symlink CLAUDE.md to it, and prove with CI that the symlink is committed as a symlink (not a Windows-materialised copy) and that any generated per-tool file byte-matches a fresh regeneration from the source, so nothing silently drifts.
Self-hosting the open-source stack? Prove your backup actually restores before you need it
Make the one self-hosting discipline that matters a machine check: back up your database, destroy the live copy, restore from the backup, and assert the restored data matches the original exactly, so you find a broken backup in CI instead of at 2am.
Chat with a CSV, but pin a known-answer guardrail so a wrong query cannot pass
Ask a CSV or dataframe questions in plain English with PandasAI, but wrap it in a deterministic known-answer check so a confident-but-wrong generated query is caught instead of trusted.
Verify an agent-skills plugin before you ship or install it
Check that a Claude Code / agentskills.io skills package is structurally valid, every SKILL.md has proper frontmatter and a name matching its folder, and the plugin marketplace manifest parses, so a broken skill never fails to load after you publish it.
zvec: run vector search inside your app, no server, offline
Embed a vector database directly into your process with zvec, insert vectors, and query for nearest neighbors, with no separate server to run, config, or babysit.
Vet the fine print a star count hides: real license and a gate on dual-use tools
Before you build on a starred repo, record its actual license (not an assumed permissive one) and whether it is dual-use, so a custom license or an impersonation risk never surprises you after you have shipped.
Read your token receipts right: volume and cost are different leaderboards
Attribute your model usage by both tokens and dollars, so you can see the flip the OpenRouter rankings show: cheap open models dominate volume while premium models dominate spend, and never mistake a high token ranking for value.
ReMe pattern: define prospective memory as a schedule your agent can tick off
Write a reminder schedule config that an agent can load to surface its own future obligations — follow-ups, timed checks, recurring digests — and validate the structure before wiring it up.
LlamaIndex: index your documents and query them at runtime
Point LlamaIndex at a document corpus and build a VectorStoreIndex so an agent can retrieve the relevant chunks at query time instead of stuffing everything into context.
E2B: run model-written code in a sandbox, not on your box
Execute AI-generated code in an isolated E2B cloud sandbox with the API key read from the environment, so untrusted code never touches your laptop or prod.
Write an agent loop in code with smolagents (sandboxed)
Stand up a smolagents CodeAgent that writes Python to act instead of emitting JSON tool calls, and run that model-written code in a sandbox, not on your machine.
Hermes /learn: author a reusable skill from a source, not by hand
Use Hermes Agent's /learn to turn a doc, a repo, or a workflow you just performed into a standards-compliant SKILL.md (and an automatic slash command), instead of hand-writing a skill file that drifts from the real docs.
codebase-memory-mcp: wire the knowledge graph, stop re-reading files
Point your MCP client at a codebase-memory-mcp server so your coding agent queries the repo's knowledge graph instead of re-reading files into context on every question, cutting token spend without changing answer quality.
Vet a SKILL.md before you install it
Treat an agent skill like the untrusted dependency it is: parse its SKILL.md, confirm the frontmatter is well-formed, and surface every executable script it bundles, since the research flagged script-bearing skills as the most dangerous, before you ever let your agent run it.
Scrape politely: honor robots.txt and a crawl delay (the part most skip)
Gate any scraper behind a robots.txt check and a crawl delay so you only fetch what a site allows, at a rate it allows, using nothing but the Python standard library.
Crawl4AI: a page to clean, LLM-ready markdown (no API key)
Write a Crawl4AI run script that turns a page into clean markdown with a cache mode set, and verify the script is valid and shaped right before you point it at a site.
Firecrawl: turn a page into the exact JSON you asked for
Author a Firecrawl extract request that returns schema-structured JSON (not just markdown) and validate the request shape before you spend a crawl on it.
Track a tool's hype curve across any Substack (no API key)
Count how often a tool or model is mentioned in a Substack's posts over time, so you can see a hype curve rise and fade, using only the public archive.
Hermes + OKF: a knowledge folder your agent reads before it answers
Wire an OKF knowledge bundle into Hermes so the agent reads knowledge/index.md first, validated bundle conformance + a SOUL.md house rule that points at it.
OKF: turn your repo's tribal knowledge into a bundle your agent reads first
Write one markdown concept per thing worth knowing, cross-linked, as a conformant OKF bundle in version control that any agent can read with no SDK.
Kilo Code: a mode that can only edit the files you let it
Build a docs mode that can read the whole repo but only write to Markdown, using a fileRegex restriction on the edit group.
OpenCode: a model-routed team, cheap to plan, strong to build
Give each agent its own model so planning and review run on a cheap model and only the build runs on your best one.
OpenCode: a read-only Plan pass that cannot touch your files
Separate think from touch: lock the plan agent to read-only (edit + bash deny) so it proposes before it edits, then Tab into build to execute.
Local model chore: draft a sensitive message in private
Ask a free, offline model to draft or soften a delicate message (a note about money, a reply to a doctor, a careful complaint) knowing the contents stay on your machine.
Local model chore: summarize a long PDF without it leaving your laptop
Attach a 30-page PDF or a dense terms-of-service to a local model and get five plain bullets plus anything you need to act on, with the document staying on your machine.
Local model chore: turn a brain-dump into a clean to-do list
Paste messy meeting notes into a free, offline model on your own laptop and get back an organized to-do list, with nothing leaving the machine.
Hermes + DeepSeek V4 Flash: a one-line reasoning-effort throttle
Run one model from cheap-and-fast to deep-and-careful with a single reasoning_effort setting, so you don't pay for deep thinking on easy turns.
Hermes on MiMo-V2.5: a 1M-context agent for pennies
Set MiMo-V2.5 as your everyday Hermes model: 1M context at $0.14/$0.28 per 1M tokens, with tool-use enforcement on for a non-GPT model.
Repomix + Fable 5: Pack a Repo for a Long-Context Review
Flatten an entire codebase into a single file and let Fable 5 hold all of it at once for a whole-system review.
Fabric + Fable 5: Get Through Your Reading Pile
Pipe any article, video transcript, or document into a prebuilt Fabric pattern and have Fable 5 summarize, extract, or analyze it in one line.
Cline + Fable 5: Build or Fix Something Without Writing Code
Use a coding agent inside VS Code that builds and fixes code while you just describe what you want, powered by Fable's stamina.
LibreChat + Fable 5: Show It a Screenshot or a PDF
Run a private, self-hosted ChatGPT-style app where you drop in an image or document and let Claude Fable 5 read it.
Mem0: A Personalization Layer Your Assistant Remembers With
Add user, session, and agent-level memory to an assistant so it remembers preferences across conversations.
Mnemosyne: Fully Local Agent Memory, No Cloud at All
Give your agent persistent memory in a single SQLite file: store a fact, recall it by keyword, fully offline.
Obsidian × MCPVault: Write a Note from Any MCP Client
Create or patch a note in your Obsidian vault through MCPVault, from any MCP client, with frontmatter preserved.
Obsidian × MCPVault: Read a Note from Any MCP Client
Read a note from your Obsidian vault through MCPVault, from any MCP client, including a fully local LM Studio + open-model setup.
Obsidian × MCPVault: The Book Notes System
Dump your highlights and have Claude file the book into your second brain with connections and project-tied takeaways.
Pi: The Reusable Prompt Template
Turn a prompt you retype into a permanent Pi slash command.
Pi: The Safe Diff Reviewer
A code reviewer that reads your staged diff and structurally cannot modify it.
Research Ingestion: File a Source Into Your Knowledge Base
Paste an article or transcript into your vault and have Claude summarize, link, and flag contradictions.
Meeting Processor: Raw Dump to Structured Note
Paste a raw meeting dump into your vault and have Claude turn it into action items, decisions, and links.
Dedupe and Rank a Keyword List with Coreutils
Turn a messy keyword dump into a clean, frequency-ranked list using only shell builtins.
Run LLMs Locally to Replace ChatGPT Plus
Serve a capable open model locally with Ollama and drop the ChatGPT Plus subscription.
Replaces ChatGPT Plus
Local Text-to-Speech that Replaces ElevenLabs
Generate natural speech locally with Piper instead of an ElevenLabs subscription.
Replaces ElevenLabs