Agent skill

Loop Authoring

by a-streetcoder in a-streetcoder/agent-deck

A skill your agent uses when creating, refining, or validating Agent Deck loops, especially to guide users iteratively through loop goal, structure, agents, write target, and safety choices.

MITAuto-check passedAgent Workflows

Install Loop Authoring

skills CLI
$ npx skills add a-streetcoder/agent-deck --skill loop-authoring -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install a-streetcoder/agent-deck loop-authoring --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/a-streetcoder/agent-deck.git skills-src && mkdir -p .claude/skills && cp -r skills-src/agent-deck/bundled-skills/loop-authoring .claude/skills/loop-authoring && rm -rf skills-src

Use ~/.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/

Facts

Skill name
loop-authoring
GitHub stars
118
Token cost
~1.6k tokens
SKILL.md length
906 words
Files
1
Skills in repo
5
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when creating, refining, or validating Agent Deck loops, especially to guide users iteratively through loop goal, structure, agents, write target, and safety choices.

  • Works in 7 steps: Clarify the outcome → Choose the loop structure → Select agents explicitly → …
  • Validating Agent Deck loops
  • SKILL.md covers Core mental model, Iterative authoring workflow, Structure guide and Write target guidance, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Loop Authoring is an agent skill from a-streetcoder/agent-deck. Use when creating, refining, or validating Agent Deck loops, especially to guide users iteratively through loop goal, structure, agents, write target, and safety choices.

Its SKILL.md is about 1.6k 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 Agent Workflows. The licence is MIT.

When your agent uses it

  • Validating Agent Deck loops
  • Especially to guide users iteratively through loop goal

Example prompts

  • “/loop-authoring”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Clarify the outcome
  2. Choose the loop structure
  3. Select agents explicitly
  4. Choose the write target
  5. Define validation and stop conditions
  6. Decide whether to save it
  7. Review before launch or save

What it can do on your machine

Read from SKILL.md and the folder at commit 9efbe6c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Loop Authoring loads about 1.6k tokens when it runs. Until then it costs about 46 tokens; SKILL.md has 906 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~46
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from a-streetcoder/agent-deck at commit 9efbe6c, republished under its MIT licence (© a-streetcoder). 906 words, ~1,592 tokens.

Download SKILL.mdSave it as .claude/skills/loop-authoring/SKILL.md (or your agent's skills folder).
name
loop-authoring
description
Use when creating, refining, or validating Agent Deck loops, especially to guide users iteratively through loop goal, structure, agents, write target, and safety choices.

Agent Deck Loop Authoring

Use this skill when the user wants to create, refine, review, save, or troubleshoot an Agent Deck loop.

Your job is to guide the user iteratively. Do not dump every option at once. Ask one focused question at a time, explain the practical tradeoff, and state your recommended default before asking when there is a sensible default.

Core mental model

An Agent Deck loop is a reusable run recipe with:

  • a goal or task prompt
  • a structure kind
  • one or more explicitly selected agents
  • a write target
  • stopping or validation criteria
  • optional project availability metadata when saved to the Loop Bank

User-authored loops are typically saved as *.loop.md under ~/.pi/agent/loops in the current user-level Loop Bank storage. Built-in loop templates are currently disabled, so do not tell users that bundled loop templates are available unless the product changes.

Iterative authoring workflow

Move through these steps in order. Stop and ask only for the next missing decision.

  1. Clarify the outcome

    • Ask what the loop should accomplish and what “done” means.
    • Help turn vague requests into an actionable goal prompt.
    • Recommended default: artifact/report output unless the user clearly wants code edits.
  2. Choose the loop structure

    • Recommend the simplest structure that fits the work.
    • Ask the user to confirm the structure before choosing agents.
  3. Select agents explicitly

    • Agent fields must stay blank until the user chooses an agent.
    • Never invent fallback agent names such as Maker or Checker.
    • If the available agent list is unknown, ask the user to choose from Agent Deck or inspect the global/imported catalog plus the project’s Agent Deck assignments if tools/context allow it. Do not offer project-local .pi/agents or legacy .agents files; import/catalog entries are by reference, not copy.
  4. Choose the write target

    • Prefer artifactMarkdown for planning, research, review, and safe reports.
    • Use newWorktree for implementation that should avoid touching the current checkout.
    • Use currentCheckout only when the user explicitly confirms direct edits to the current project tree.
  5. Define validation and stop conditions

    • Ask what evidence should decide success: tests passing, reviewer approval, checklist completion, no findings, or a human approval checkpoint.
    • Keep max iterations low unless the user asks for longer autonomous work.
  6. Decide whether to save it

    • If the user wants reuse, save to the Loop Bank with a clear name and description.
    • Ask whether it should be available to all projects, only the current project, or kept unassigned/catalog-style.
  7. Review before launch or save

    • Summarize the loop in a compact checklist.
    • Call out any risky write target, missing agent, vague goal, or missing validation.
    • If several decisions are still missing, summarize them briefly but ask for only the highest-priority missing decision in the current turn.
    • Ask for confirmation before launch when the loop can modify project files.

Structure guide

Choose the most direct structure:

  • Single Agent: one agent repeats work until validation passes or the iteration limit is reached. Best for focused reports or bounded implementation by one specialist.
  • Maker + Checker: one maker produces work and a checker approves or rejects against a rubric. Best when quality gates matter.
  • Agent Pipeline: ordered stages where each stage hands off to the next. Best for research → plan → implementation → review workflows.
  • Parallel Agents: multiple branches run independently and then summarize. Best for independent investigations or comparing approaches.
  • Discovery/Triage: one triage agent classifies or routes findings using a classification prompt. Best for bug intake, repo sweeps, or issue sorting.
  • Human Approval: pauses for explicit user approval at a checkpoint. Best when a human must decide before continuing.

If multiple structures fit, recommend the simplest safe option and explain why in one sentence.

Show full SKILL.md (303 more words)Show less

Write target guidance

Use these names and safety expectations consistently:

  • artifactMarkdown: safest; writes loop artifacts/reports, not project files.
  • newWorktree: safer for code changes; uses an isolated git worktree.
  • currentCheckout: riskiest; writes directly to the current checkout and requires explicit user confirmation.

Never quietly upgrade a loop to currentCheckout. If direct edits are required, ask a focused confirmation question.

Loop Bank and bundled-resource rules

  • User loop definitions are saved as *.loop.md under ~/.pi/agent/loops.
  • Built-in bundled loop templates are disabled for now.
  • Bundled resources must not be edited in place by ordinary user customization flows.
  • If a future built-in loop exists and the user wants to customize it, duplicate it first and edit the user copy.

Good authoring questions

Ask one at a time:

  • “What outcome should this loop produce, and how will we know it is done?”
  • “I recommend a Maker + Checker loop because you want an explicit quality gate. Should we use that structure?”
  • “Which agent should be the maker? I will leave it blank until you choose one.”
  • “Should the loop write only an artifact report, use a new worktree, or directly edit the current checkout? I recommend artifact report unless you need code changes.”
  • “What should the checker use as the approval rubric?”
  • “Should this be saved for all projects, only this project, or left unassigned in the Loop Bank?”

Validation checklist

Before considering a loop ready, verify:

  • Goal is specific enough for an agent to act on.
  • Structure matches the desired workflow and is not overcomplicated.
  • Every required agent field is explicitly selected.
  • Write target is explicit and safe for the task.
  • currentCheckout, if used, has explicit user confirmation.
  • Review rubric, classification prompt, checkpoint prompt, or validation criteria are present when the structure needs them.
  • Iteration/review limits are bounded.
  • Saved loop name and description are clear enough to recognize later.

© a-streetcoder, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in agent-deck/bundled-skills/loop-authoring of a-streetcoder/agent-deck.

Open the folder on GitHubat commit 9efbe6c

Compare with similar skills

Loop Authoring 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.

Loop Authoring compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Loop Authoring this skilla-streetcoder/agent-deck118—~1.6kAutomated safety check: PassMIT
MCP Server Builderanthropics/skills180k64 repos~2.3kAutomated safety check: PassApache-2.0
Hook Development for Claude Code Pluginsanthropics/claude-plugins-official38k11 repos~4.1kAutomated safety check: NotesApache-2.0
Using Superpowersfarm-fe/farm5.6k35 repos~1.4kAutomated safety check: PassMIT
Executing Plans Inlineobra/superpowers296k2 repos~5.1kAutomated safety check: PassMIT
Claude Code Agent Developmentanthropics/claude-plugins-official38k8 repos~2.8kAutomated safety check: PassApache-2.0

Similar skills

  • MCP Server Builder

    anthropics/skills

    Official

    Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.

    180k GitHub starsUsed in 64 repos~2.3k tokens
    Agent WorkflowsAuto-check passed
  • Hook Development for Claude Code Plugins

    anthropics/claude-plugins-official

    Official

    Explains how to write Claude Code plugin hooks, both prompt-based checks and bash commands, for events such as PreToolUse, Stop and SessionStart.

    38k GitHub starsUsed in 11 repos~4.1k tokens
    Agent WorkflowsAuto-check: notes
  • Using Superpowers

    farm-fe/farm

    A skill your agent uses when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions

    5.6k GitHub starsUsed in 35 repos~1.4k tokens
    Agent WorkflowsAuto-check passed
  • Executing Plans Inline

    obra/superpowers

    Has the agent carry out an implementation plan itself, task by task in the current session, keeping a ledger, proving each step with a test and ending with one whole-branch review.

    296k GitHub starsUsed in 2 repos~5.1k tokens
    Agent WorkflowsAuto-check passed
  • Claude Code Agent Development

    anthropics/claude-plugins-official

    Official

    Explains how to write agents for Claude Code plugins: the markdown file with YAML frontmatter, trigger descriptions, model and color settings, and system prompt design.

    38k GitHub starsUsed in 8 repos~2.8k tokens
    Agent WorkflowsAuto-check passed
  • Skill Creator

    Azure/azqr

    Official

    Create new skills, modify and improve existing skills, and measure skill performance.

    795 GitHub starsUsed in 89 repos~8.2k tokens
    Agent WorkflowsAuto-check passed

More from a-streetcoder/agent-deck

  • Agent Authoring

    a-streetcoder/agent-deck

    A skill your agent uses when creating or reviewing Agent Deck agents, including frontmatter, tools, supervisor behavior, continuation behavior, and skill assignment.

    118 GitHub stars~1.4k tokensUpdated 2 mo ago
    Auto-check passed
  • MCP Install Helper

    a-streetcoder/agent-deck

    A skill your agent uses when helping users install, import, repair, or verify MCP server configurations in Agent Deck.

    118 GitHub stars~1.4k tokensUpdated 2 mo ago
    Auto-check passed
  • Prompt Authoring

    a-streetcoder/agent-deck

    Create or improve Agent Deck/Pi prompt templates for reusable parent-session workflows.

    118 GitHub stars~721 tokensUpdated 2 mo ago
    Auto-check passed
  • Skill Authoring

    a-streetcoder/agent-deck

    Create or improve Agent Deck/Pi skills, including where to save them, SKILL.md frontmatter, simple vs modular structure, and validation.

    118 GitHub stars~1.8k tokensUpdated 2 mo ago
    Auto-check passed

Categories

Questions about Loop Authoring

What does Loop Authoring do?

A skill your agent uses when creating, refining, or validating Agent Deck loops, especially to guide users iteratively through loop goal, structure, agents, write target, and safety choices. Loop Authoring is an agent skill from a-streetcoder/agent-deck. Use when creating, refining, or validating Agent Deck loops, especially to guide users iteratively through loop goal, structure, agents, write target, and safety choices.

When should I use Loop Authoring?

Loop Authoring fits situations like: validating Agent Deck loops; especially to guide users iteratively through loop goal.

How do I install Loop Authoring in Claude Code?

Run `npx skills add a-streetcoder/agent-deck --skill loop-authoring -a claude-code`. Or copy the skill folder (agent-deck/bundled-skills/loop-authoring in a-streetcoder/agent-deck) into .claude/skills/loop-authoring in your project. Claude Code loads it when a task matches its description.

How do I install Loop Authoring in Codex?

Run `npx skills add a-streetcoder/agent-deck --skill loop-authoring -a codex`. Or copy the skill folder (agent-deck/bundled-skills/loop-authoring in a-streetcoder/agent-deck) into .agents/skills/loop-authoring in your project. Codex loads it when a task matches its description.

Can I use Loop Authoring in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add a-streetcoder/agent-deck --skill loop-authoring -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/loop-authoring, .gemini/skills/loop-authoring, .github/skills/loop-authoring and .opencode/skills/loop-authoring in your project.

What does Loop Authoring need to run?

SKILL.md names no scripts, command-line tools or credentials: Loop Authoring is instructions for the agent only.

Does Loop Authoring access the network?

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.

Is Loop Authoring safe to install?

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.

What licence does Loop Authoring use?

Loop Authoring is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Loop Authoring use?

About 1.6k tokens (SKILL.md is roughly 6.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Loop Authoring?

Skills that share tags, products or a category with Loop Authoring: MCP Server Builder (anthropics/skills, 180k stars), Hook Development for Claude Code Plugins (anthropics/claude-plugins-official, 38k stars), Using Superpowers (farm-fe/farm, 5.6k stars) and Executing Plans Inline (obra/superpowers, 296k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Loop Authoring?

a-streetcoder (a GitHub organization) maintains it in a-streetcoder/agent-deck, which has 118 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on August 1, 2026.

Source: a-streetcoder/agent-deck on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.