Improve
fossasia/eventyay-interpretation
Survey any codebase as a senior advisor and produce prioritized, self-contained implementation plans for OTHER models/agents to execute.
A skill your agent uses when starting non-trivial work (touching 3+ files, new features, refactors, bug investigations).
$ npx skills add garagon/nanostack --skill nano -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install garagon/nanostack nano --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/garagon/nanostack.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plan .claude/skills/nano && 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 "nano" agent skill from https://github.com/garagon/nanostack/tree/main/plan into .claude/skills/nano/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nano", 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/garagon/nanostack/tree/main/planType 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 garagon/nanostack --skill nano -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install garagon/nanostack nano --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/garagon/nanostack.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plan .agents/skills/nano && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "nano" agent skill from https://github.com/garagon/nanostack/tree/main/plan into .agents/skills/nano/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nano", 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 garagon/nanostack --skill nano -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install garagon/nanostack nano --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/garagon/nanostack.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plan .cursor/skills/nano && 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 "nano" agent skill from https://github.com/garagon/nanostack/tree/main/plan into .cursor/skills/nano/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nano", 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/garagon/nanostack.git --path plan--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 garagon/nanostack --skill nano -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install garagon/nanostack nano --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/garagon/nanostack.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plan .gemini/skills/nano && 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 "nano" agent skill from https://github.com/garagon/nanostack/tree/main/plan into .gemini/skills/nano/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nano", 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 garagon/nanostack nanoInstalls 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 garagon/nanostack --skill nano -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/garagon/nanostack.git skills-src && mkdir -p .github/skills && cp -r skills-src/plan .github/skills/nano && 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 "nano" agent skill from https://github.com/garagon/nanostack/tree/main/plan into .github/skills/nano/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nano", 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 garagon/nanostack --skill nano -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install garagon/nanostack nano --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/garagon/nanostack.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plan .opencode/skills/nano && 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 "nano" agent skill from https://github.com/garagon/nanostack/tree/main/plan into .opencode/skills/nano/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nano", 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.
nanoA skill your agent uses when starting non-trivial work (touching 3+ files, new features, refactors, bug investigations).
Nano is an agent skill from garagon/nanostack. Use when starting non-trivial work (touching 3+ files, new features, refactors, bug investigations). Produces a scoped, actionable implementation plan before any code is written. Triggers on /nano.
Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `agents/openai.yaml`, `references/product-standards.md` and `references/stack-defaults.md`).
It sits in Agent Workflows, covering Planning and Refactoring. It works with Git. The repository describes itself as: A workflow harness that helps AI coding agents plan, review, test, and ship safer code. The licence is Apache-2.0.
7 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 0372aed. 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.
Shell commands in SKILL.md call:
jqFrom 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.
Nano loads about 3.3k tokens when it runs, and up to ~5.5k if it reads all its reference files. Until then it costs about 51 tokens; SKILL.md has 1,570 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.
The full file from garagon/nanostack at commit 0372aed, republished under its Apache-2.0 licence (© garagon). 1,570 words, ~3,267 tokens.
.claude/skills/nano/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.You turn validated ideas into executable steps. Every file gets named. Every step gets a verification. Every unknown gets surfaced. The plan is a contract: if it says 4 files, the PR should touch 4 files.
Defensive telemetry init. No-op if telemetry is disabled via NANOSTACK_NO_TELEMETRY=1, ~/.nanostack/.telemetry-disabled, or if the helpers are removed.
_P="$HOME/.claude/skills/nanostack/bin/lib/skill-preamble.sh"
[ -f "$_P" ] && . "$_P" nano
unset _PIf no active session exists, initialize one:
~/.claude/skills/nanostack/bin/session.sh statusIf the output shows "active":false, create a session:
~/.claude/skills/nanostack/bin/session.sh init developmentThen run session.sh phase-start plan.
Plan approval mode. This skill reads plan_approval from the session to decide whether to pause. The field has three values:
auto — Present a short plan and continue without waiting. /feature always sets this.manual — Default. Present the plan and wait for explicit approval before building.not_required — Used by --run-mode report_only sprints. Skip the approval gate entirely.Read the value with v1-compat fallback (older sessions may only have autopilot):
PLAN_APPROVAL=$(jq -r '.plan_approval // (if .autopilot then "auto" else "manual" end)' .nanostack/session.json 2>/dev/null)If the file is missing entirely, treat as manual.
Local mode: Run source bin/lib/git-context.sh && detect_git_mode. If result is local, adapt language: "implementation plan" → "paso a paso", "files to modify" → "archivos que vamos a crear", "architecture checkpoint" → skip (overkill for non-technical users). Present the plan as a simple numbered list of what you'll build, not a spec document. Same rigor, accessible words. In the "Next Step" section, do NOT list slash commands (/review, /security, /qa, /ship). Instead say: "Cuando termine, reviso la calidad y te aviso si hay algo que ajustar."
Plain-language contract. When profile == "guided" (or local mode), follow reference/plain-language-contract.md. The plan summary uses the four-block skeleton:
<!-- guided-output:start -->
Resultado: Voy a armar la herramienta en 3 archivos chicos.
Como verlo:
1. Cuando termine cada paso, te muestro lo que cambio.
Que revise:
- La forma mas simple de cumplir lo que pediste.
- Que cada cambio se pueda probar por separado.
- Que no rompa nada que ya estaba funcionando.
Pendiente:
- No probe en una computadora distinta a la tuya.<!-- guided-output:end -->
Resolve context — load upstream artifacts and past solutions in one call:
~/.claude/skills/nanostack/bin/resolve.sh planThe output is JSON with upstream_artifacts (think artifact path if recent), solutions (ranked matches), config, and sprint_metrics (git stats + cycle time from last sprint). Use what's relevant:
key_risk → add to Risks. narrowest_wedge (starting point) → scope constraint. out_of_scope → pre-populate Out of Scope. scope_mode → if "reduce," plan smallest version. premise_validated → if false, flag it.sprint_metrics is present, use it for scope calibration: last sprint's lines changed and file count help estimate whether the current task is Small, Medium, or Large relative to recent work.If think artifact is missing but /think ran, use the visible Think Summary as planning context and disclose the missing artifact. Do not use --from-session or enable the legacy artifact bypass. Ask for missing scope information rather than inventing a brief or marking discovery complete retroactively.
Check git history for recent changes in the affected area — someone may have already started this work or made decisions you need to respect.
If the affected modules are known, check for diarizations (structured module briefs from past sprints) in .nanostack/know-how/diarizations/. If a diarization exists for a module in scope, read it for recurring issues, known risks, and unresolved tensions. These should inform your risk assessment.
If the request is ambiguous, ask clarifying questions using AskUserQuestion before proceeding. Do not guess scope.
If the user doesn't specify their tech stack and needs to pick tools (auth, database, hosting, etc.), check for overrides first, then fall back to defaults:
.nanostack/stack.json if it exists (project-level preferences)~/.nanostack/stack.json if it exists (user-level preferences)plan/references/stack-defaults.md for anything not covered aboveAlways use the latest stable version of every dependency. Don't rely on versions from training data.
<!-- Auto-maintained by bin/graduate.sh. Do not edit manually. -->
<!-- Each rule was promoted from a solution with 3+ applications and validation. -->
<!-- END GRADUATED RULES -->
Apply these constraints during planning. Each one represents a proven pattern or decision from past sprints.
Classify the work:
| Scope | Criteria | Output |
|---|---|---|
| Small | 1-3 files, single concern, clear path | Implementation steps only |
| Medium | 4-10 files, multiple concerns, some unknowns | Product spec + implementation steps + risks |
| Large | 10+ files, cross-cutting, architectural impact | Product spec + technical spec + implementation steps + phased execution |
For small scope: produce a brief plan and move on. Do not over-plan trivial work.
Before writing implementation steps, produce the specs that define what you're building. Skip this for Small scope.
Medium scope: Product Spec only.
Use plan/templates/product-spec.md. Cover: problem, solution, user stories, acceptance criteria, user flow, edge cases, out of scope. Keep it to 1-2 pages. This is what the team reads to understand what "done" looks like.
Large scope: Product Spec + Technical Spec.
Also use plan/templates/technical-spec.md. Cover: architecture, data model, API contracts, integrations, technical decisions, security considerations, migration/rollback. This is what the team reads to understand how the system works.
Present the specs to the user before writing implementation steps. Specs are the contract. If the spec is wrong, the plan will be wrong and the code will be wrong. Get alignment here.
Use the template at plan/templates/plan-template.md as your output structure. Fill in every section that applies to the scope level.
Key requirements:
Before presenting, validate the plan against these engineering concerns:
think/references/latent-vs-deterministic.md for the full framing.Skip this for Small scope — it's overkill for a 3-file change.
If the plan produces anything a user will see or interact with, apply the standards in plan/references/product-standards.md. They are not optional — they cover UI/frontend (shadcn + Tailwind, dark mode, mobile, no AI slop), SEO, LLM SEO, and CLI/TUI defaults per language.
If the plan is a pure library with no user-facing output, skip this section.
Behavior depends on PLAN_APPROVAL (read above):
auto — Present the plan briefly and proceed immediately. The caller (/feature or autopilot) chose this; do not pause.not_required — Skip the approval gate entirely. Save the artifact and continue. This applies to report-only sprints.manual (default) — Present the plan to the user and wait for explicit approval before executing. If the user modifies the plan, update it before proceeding.After the plan is approved (or auto-approved), do these two steps in order:
Step 1: Save the artifact. Run this command now — do not skip it. The save is validated against the per-phase schema (see reference/artifact-schema.md); a plan artifact requires summary.planned_files (array), summary.plan_approval, and context_checkpoint. /review uses planned_files for scope drift.
PLAN_JSON=$(jq -n \
--argjson planned_files '["file1.ts","file2.ts"]' \
--arg plan_approval "$PLAN_APPROVAL" \
--arg checkpoint_summary "Plan for <feature>: N files, key decisions X and Y." \
'{
phase: "plan",
summary: {
planned_files: $planned_files,
plan_approval: $plan_approval
},
context_checkpoint: {
summary: $checkpoint_summary,
key_files: $planned_files,
decisions_made: [],
open_questions: []
}
}')
~/.claude/skills/nanostack/bin/save-artifact.sh plan "$PLAN_JSON"Step 2: Return the plan.
After the plan artifact is saved:
If PLAN_APPROVAL is auto:
Return the approved plan to the caller. Do not build or invoke downstream specialists. /feature owns the full sprint; a standalone /nano call ends with the plan even when approval is automatic.
Otherwise (manual or not_required):
Tell the user:
Plan ready. Next steps in the sprint:
- Build the approved plan
/reviewto run a two-pass code review with scope drift detection/securityto audit for vulnerabilities/qato test that everything worksThese three can run in any order. After all pass,
/shipto create the PR.
Wait for the user to invoke each one.
Before returning control:
_F="$HOME/.claude/skills/nanostack/bin/lib/skill-finalize.sh"
[ -f "$_F" ] && . "$_F" nano success
unset _FPass abort or error instead of success if the plan did not complete normally.
© garagon, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 6 other files (references) in plan of garagon/nanostack.
Open the folder on GitHubat commit 0372aed
Nano 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 |
|---|---|---|---|---|---|---|
| Nano this skillgaragon/nanostack | 207 | — | ~3.3k | Automated safety check: Pass | Apache-2.0 | |
| Improvefossasia/eventyay-interpretation | 1.6k | 10 repos | ~3.7k | Automated safety check: Warn | MIT | |
| Inline Plan ExecutionjnMetaCode/superpowers-zh | 8.3k | — | ~2.5k | Automated safety check: Pass | MIT | |
| Workflow Orchestrationvxcozy/workflow-orchestration | 116 | — | ~1k | Automated safety check: Pass | MIT | |
| Docslatitude-dev/latitude-llm | 4.7k | — | ~2.5k | Automated safety check: Pass | MIT | |
| File-Based Planning in ArabicOthmanAdi/planning-with-files | 27k | — | ~3.2k | Automated safety check: Notes | MIT |
fossasia/eventyay-interpretation
Survey any codebase as a senior advisor and produce prioritized, self-contained implementation plans for OTHER models/agents to execute.
jnMetaCode/superpowers-zh
Executes a written implementation plan task by task in the current session, with a progress ledger, test-first gates and one fresh-context review at the end.
vxcozy/workflow-orchestration
Disciplined task execution with planning, verification, and self-improvement loops.
latitude-dev/latitude-llm
Review the current conversation context and git changes, then persist durable repository knowledge into dev-docs/.md by domain and into AGENTS.md for cross-cutting repo rules.
OthmanAdi/planning-with-files
Arabic edition of a file-based planning skill that keeps task_plan.md, findings.md and progress.md on disk so multi-step agent work survives lost context.
affaan-m/ECC
Turns a one-line objective into a multi-step plan file with PR-sized steps, context briefs, a dependency graph, parallel-step detection and an adversarial review.
garagon/nanostack
First-time setup and guided sprint. An agent skill from garagon/nanostack.
garagon/nanostack
Use before shipping to production. An agent skill from garagon/nanostack.
garagon/nanostack
A skill your agent uses when code is ready to ship — creates PRs, merges, deploys, and verifies.
garagon/nanostack
Document what you learned during this sprint. An agent skill from garagon/nanostack.
garagon/nanostack
Orchestrate parallel agent sessions through a sprint. An agent skill from garagon/nanostack.
garagon/nanostack
Add a feature to an existing project with a full sprint. An agent skill from garagon/nanostack.
Works with
Categories
A skill your agent uses when starting non-trivial work (touching 3+ files, new features, refactors, bug investigations). Nano is an agent skill from garagon/nanostack. Use when starting non-trivial work (touching 3+ files, new features, refactors, bug investigations).
Nano fits situations like: starting non-trivial work (touching 3+ files; bug investigations).
Run `npx skills add garagon/nanostack --skill nano -a claude-code`. Or copy the skill folder (plan in garagon/nanostack) into .claude/skills/nano in your project. Claude Code loads it when a task matches its description.
Run `npx skills add garagon/nanostack --skill nano -a codex`. Or copy the skill folder (plan in garagon/nanostack) into .agents/skills/nano 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 garagon/nanostack --skill nano -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/nano, .gemini/skills/nano, .github/skills/nano and .opencode/skills/nano in your project.
Going by SKILL.md and its folder, Nano needs the command-line tools its instructions call (jq).
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.
Nano is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.2k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Nano: Improve (fossasia/eventyay-interpretation, 1.6k stars), Inline Plan Execution (jnMetaCode/superpowers-zh, 8.3k stars), Workflow Orchestration (vxcozy/workflow-orchestration, 116 stars) and Docs (latitude-dev/latitude-llm, 4.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
garagon (a GitHub user) maintains it in garagon/nanostack, which has 207 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on September 10, 2026.
Source: garagon/nanostack on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.