Building Agent Systems
telagod/code-abyss
AI agent and LLM system engineering reference covering single-agent dev (ReAct, tool calling, plan-execute), multi-agent coordination (swarm, role decomposition, file locking), LLM security (prompt…
A skill your agent uses when building AI features into a product: LLM integration, RAG pipelines, guardrails, streaming, AI UX, prompt engineering, or AI cost control.
$ npx skills add coco-research/coco --skill ai-product -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install coco-research/coco ai-product --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/coco-research/coco.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai-product .claude/skills/ai-product && 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 "ai-product" agent skill from https://github.com/coco-research/coco/tree/main/skills/ai-product into .claude/skills/ai-product/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-product", 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/coco-research/coco/tree/main/skills/ai-productType 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 coco-research/coco --skill ai-product -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install coco-research/coco ai-product --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/coco-research/coco.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ai-product .agents/skills/ai-product && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ai-product" agent skill from https://github.com/coco-research/coco/tree/main/skills/ai-product into .agents/skills/ai-product/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-product", 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 coco-research/coco --skill ai-product -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install coco-research/coco ai-product --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/coco-research/coco.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ai-product .cursor/skills/ai-product && 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 "ai-product" agent skill from https://github.com/coco-research/coco/tree/main/skills/ai-product into .cursor/skills/ai-product/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-product", 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/coco-research/coco.git --path skills/ai-product--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 coco-research/coco --skill ai-product -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install coco-research/coco ai-product --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/coco-research/coco.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ai-product .gemini/skills/ai-product && 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 "ai-product" agent skill from https://github.com/coco-research/coco/tree/main/skills/ai-product into .gemini/skills/ai-product/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-product", 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 coco-research/coco ai-productInstalls 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 coco-research/coco --skill ai-product -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/coco-research/coco.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ai-product .github/skills/ai-product && 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 "ai-product" agent skill from https://github.com/coco-research/coco/tree/main/skills/ai-product into .github/skills/ai-product/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-product", 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 coco-research/coco --skill ai-product -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install coco-research/coco ai-product --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/coco-research/coco.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ai-product .opencode/skills/ai-product && 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 "ai-product" agent skill from https://github.com/coco-research/coco/tree/main/skills/ai-product into .opencode/skills/ai-product/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-product", 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.
ai-productA skill your agent uses when building AI features into a product: LLM integration, RAG pipelines, guardrails, streaming, AI UX, prompt engineering, or AI cost control.
AI Product is an agent skill from coco-research/coco. Use when building AI features into a product: LLM integration, RAG pipelines, guardrails, streaming, AI UX, prompt engineering, or AI cost control. Treats prompts as code and validates every model output.
Its SKILL.md is about 4.5k 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 AI & LLM Engineering, covering Retrieval-augmented generation, LLM guardrails and Budgeting and forecasting. The repository describes itself as: CoCo Super Intelligence is the orchestration layer that turns Claude Code, Cursor, or Codex into an engineering department: a routed advisory board, 226 skills, 386 commands…
4 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 1a642ae. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are typescript).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
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.
AI Product loads about 4.5k tokens when it runs. Until then it costs about 54 tokens; SKILL.md has 776 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 found no risky patterns in SKILL.md.
Automated 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.
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 776 words (~4,495 tokens).
“Expert in shipping production-grade AI-powered features — LLM integration patterns, RAG architecture, prompt engineering that scales, AI UX that users trust, safety and guardrails, streaming, and cost optimization. Treats prompts as code, validates all outputs, and never trusts an LLM…”
Just SKILL.md in skills/ai-product of coco-research/coco.
Open the folder on GitHubat commit 1a642ae
AI Product 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 |
|---|---|---|---|---|---|---|
| AI Product this skillcoco-research/coco | 513 | — | ~4.5k | Automated safety check: Pass | Custom licence | |
| Building Agent Systemstelagod/code-abyss | 244 | — | ~691 | Automated safety check: Pass | MIT | |
| Chatbotericrisco/rsc-harness | 180 | — | ~3.3k | Automated safety check: Pass | MIT | |
| Vertex Agent Builderjeremylongshore/tons-of-skills-marketplace | 2.8k | — | ~898 | Automated safety check: Pass | MIT | |
| Senior Prompt Engineermaslennikov-ig/claude-code-orchestrator-kit | 260 | 3 repos | ~1.4k | Automated safety check: Pass | Custom licence | |
| LLM Application DevMoizIbnYousaf/ai-agent-skills | 1.1k | 1 repos | ~1.3k | Automated safety check: Pass | MIT |
telagod/code-abyss
AI agent and LLM system engineering reference covering single-agent dev (ReAct, tool calling, plan-execute), multi-agent coordination (swarm, role decomposition, file locking), LLM security (prompt…
ericrisco/rsc-harness
A skill your agent uses when a support or sales bot on a live website must behave: persona/system prompt, grounding so it cannot invent prices or policy, jailbreak and injection defense, the human…
jeremylongshore/tons-of-skills-marketplace
Build and deploy generative AI agents on Vertex AI: Gemini model selection, RAG with grounded retrieval, function calling, multimodal extraction, evaluation, and Agent Engine deployment with…
maslennikov-ig/claude-code-orchestrator-kit
Provides reference guides and Python scripts for prompt optimization, RAG evaluation, and agent orchestration when building or tuning LLM systems.
MoizIbnYousaf/ai-agent-skills
Building applications with Large Language Models - prompt engineering, RAG patterns, and LLM integration.
agentscope-ai/OpenJudge
A skill your agent uses when the user has changed a prompt (system prompt, RAG template, agent instruction, etc.) and wants to know whether the candidate is better or worse than the baseline.
coco-research/coco
Turn the project you just shipped into a short, polished, shareable launch video (an "ad") using HyperFrames.
coco-research/coco
Build and validate .arch/index.json — a committed map from each architectural component of this repository to the real directories and files that implement it, pinned to a git commit, with every…
coco-research/coco
Build AI applications with OpenAI Agents SDK - text agents, voice agents, multi-agent handoffs, tools with Zod schemas, guardrails, and streaming.
coco-research/coco
A skill your agent uses when running, reviewing or changing coco's self-evolution cycle: the 30-day loop that observes how skills are actually used, proposes evidence-backed edits to them as one…
coco-research/coco
A skill your agent uses for architecture, current-state, process, data-flow, medallion, or DP diagrams, including redrawing .drawio and Mermaid sources.
coco-research/coco
A skill your agent uses when designing a new REST or GraphQL API, reviewing an API spec before implementation, setting team API standards, or migrating REST to GraphQL.
Categories
A skill your agent uses when building AI features into a product: LLM integration, RAG pipelines, guardrails, streaming, AI UX, prompt engineering, or AI cost control. AI Product is an agent skill from coco-research/coco. Use when building AI features into a product: LLM integration, RAG pipelines, guardrails, streaming, AI UX, prompt engineering, or AI cost control.
AI Product fits situations like: building AI features into a product: LLM integration; prompt engineering; AI cost control.
Run `npx skills add coco-research/coco --skill ai-product -a claude-code`. Or copy the skill folder (skills/ai-product in coco-research/coco) into .claude/skills/ai-product in your project. Claude Code loads it when a task matches its description.
Run `npx skills add coco-research/coco --skill ai-product -a codex`. Or copy the skill folder (skills/ai-product in coco-research/coco) into .agents/skills/ai-product 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 coco-research/coco --skill ai-product -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-product, .gemini/skills/ai-product, .github/skills/ai-product and .opencode/skills/ai-product in your project.
SKILL.md names no scripts, command-line tools or credentials: AI Product is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
AI Product has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
About 4.5k tokens (SKILL.md is roughly 18k 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 AI Product: Building Agent Systems (telagod/code-abyss, 244 stars), Chatbot (ericrisco/rsc-harness, 180 stars), Vertex Agent Builder (jeremylongshore/tons-of-skills-marketplace, 2.8k stars) and Senior Prompt Engineer (maslennikov-ig/claude-code-orchestrator-kit, 260 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
coco-research (a GitHub user) maintains it in coco-research/coco, which has 513 GitHub stars. The repository holds 63 skills in this directory. The repository was last updated on October 10, 2026.
Source: coco-research/coco on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.