Azure Data Factory
MicrosoftDocs/Agent-Skills
Expert knowledge for Azure Data Factory development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations…
Defines environment variables, architecture design, and build/test commands.
$ npx skills add shinpr/ai-coding-project-boilerplate --skill technical-spec -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install shinpr/ai-coding-project-boilerplate technical-spec --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/shinpr/ai-coding-project-boilerplate.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills-en/technical-spec .claude/skills/technical-spec && 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 "technical-spec" agent skill from https://github.com/shinpr/ai-coding-project-boilerplate/tree/main/.claude/skills-en/technical-spec into .claude/skills/technical-spec/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "technical-spec", 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/shinpr/ai-coding-project-boilerplate/tree/main/.claude/skills-en/technical-specType 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 shinpr/ai-coding-project-boilerplate --skill technical-spec -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install shinpr/ai-coding-project-boilerplate technical-spec --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/shinpr/ai-coding-project-boilerplate.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills-en/technical-spec .agents/skills/technical-spec && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "technical-spec" agent skill from https://github.com/shinpr/ai-coding-project-boilerplate/tree/main/.claude/skills-en/technical-spec into .agents/skills/technical-spec/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "technical-spec", 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 shinpr/ai-coding-project-boilerplate --skill technical-spec -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install shinpr/ai-coding-project-boilerplate technical-spec --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/shinpr/ai-coding-project-boilerplate.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills-en/technical-spec .cursor/skills/technical-spec && 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 "technical-spec" agent skill from https://github.com/shinpr/ai-coding-project-boilerplate/tree/main/.claude/skills-en/technical-spec into .cursor/skills/technical-spec/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "technical-spec", 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/shinpr/ai-coding-project-boilerplate.git --path .claude/skills-en/technical-spec--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 shinpr/ai-coding-project-boilerplate --skill technical-spec -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install shinpr/ai-coding-project-boilerplate technical-spec --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/shinpr/ai-coding-project-boilerplate.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills-en/technical-spec .gemini/skills/technical-spec && 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 "technical-spec" agent skill from https://github.com/shinpr/ai-coding-project-boilerplate/tree/main/.claude/skills-en/technical-spec into .gemini/skills/technical-spec/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "technical-spec", 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 shinpr/ai-coding-project-boilerplate technical-specInstalls 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 shinpr/ai-coding-project-boilerplate --skill technical-spec -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/shinpr/ai-coding-project-boilerplate.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills-en/technical-spec .github/skills/technical-spec && 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 "technical-spec" agent skill from https://github.com/shinpr/ai-coding-project-boilerplate/tree/main/.claude/skills-en/technical-spec into .github/skills/technical-spec/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "technical-spec", 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 shinpr/ai-coding-project-boilerplate --skill technical-spec -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install shinpr/ai-coding-project-boilerplate technical-spec --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/shinpr/ai-coding-project-boilerplate.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills-en/technical-spec .opencode/skills/technical-spec && 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 "technical-spec" agent skill from https://github.com/shinpr/ai-coding-project-boilerplate/tree/main/.claude/skills-en/technical-spec into .opencode/skills/technical-spec/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "technical-spec", 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.
technical-specDefines environment variables, architecture design, and build/test commands.
Technical Spec is an agent skill from shinpr/ai-coding-project-boilerplate. Defines environment variables, architecture design, and build/test commands. Use when configuring environment or designing architecture.
Its SKILL.md is about 1.5k 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 DevOps & Cloud, covering Secrets management. The repository describes itself as: Agentic coding TypeScript boilerplate for Claude Code: sub-agent workflows with built-in quality checks and context engineering. The licence is MIT.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 56913a2. 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.
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.
Technical Spec loads about 1.5k tokens when it runs. Until then it costs about 38 tokens; SKILL.md has 713 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.
- Keep local `.env` files outside version control and provide non-secret example files for required variable namesAutomated 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 shinpr/ai-coding-project-boilerplate at commit 56913a2, republished under its MIT licence (© shinpr). 713 words, ~1,452 tokens.
.claude/skills/technical-spec/SKILL.md (or your agent's skills folder).Inspect manifests, lockfiles, build/test configuration, CI definitions, and representative source files before applying a technology- or command-specific rule. Treat a tool, script, path alias, or runtime as observed only when repository evidence names it. Label conclusions from surrounding patterns as inferred. When a missing decision changes architecture, compatibility, security, or verification, stop and name the exact configuration or user decision required.
These rules apply to a TypeScript application when repository configuration confirms that stack. Select architecture by mapping current requirements and accepted constraints to explicit module responsibilities, dependency direction, data flow, and verification boundaries.
.env files outside version control and provide non-secret example files for required variable namesSelect architecture using these observable decisions:
Select the package manager from the packageManager field, lockfile, or established CI command in that order. Execute only scripts present in the selected manifest.
build - TypeScript buildtype-check - Type check (no emit)test - Run testsBefore executing quality checks, identify what quality mechanisms exist for the change area:
Quality checks are mandatory upon implementation completion:
Phase 1-3: Code Quality Checks
Transition evidence: every applicable static/domain check exits successfully. A missing required script is reported with the manifest/configuration path, and the remaining checks still run; whether the missing check leaves required proof unavailable is decided by the quality-fixer result.
Phase 4: Tests
test - Test executionTransition evidence: all applicable configured test suites pass, or an environment-dependent suite is recorded as blocked with its exact prerequisite.
Phase 5: Code Quality Re-verification
check:code - Re-verify code quality (clean up side effects from test fixes in Phase 4)Completion evidence: static/domain checks still pass after test-related fixes, the build succeeds, and every required test has passed or is explicitly blocked.
check:all - Overall integrated check (check:code + test) *for manual batch verificationformat - Format fixeslint:fix - Lint fixes© shinpr, 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 .claude/skills-en/technical-spec of shinpr/ai-coding-project-boilerplate.
Open the folder on GitHubat commit 56913a2
Technical Spec 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 |
|---|---|---|---|---|---|---|
| Technical Spec this skillshinpr/ai-coding-project-boilerplate | 232 | — | ~1.5k | Automated safety check: Notes | MIT | |
| Azure Data FactoryMicrosoftDocs/Agent-Skills | 775 | 1 repos | ~16k | Automated safety check: Pass | CC-BY-4.0 | |
| Finalizezifeo/lade | 133 | — | ~1k | Automated safety check: Pass | MPL-2.0 | |
| Debugsbusso/claudeclaw | 194 | 1 repos | ~3.3k | Automated safety check: Notes | MIT | |
| Keypaste Designnotinferred/keypaste | 160 | — | ~865 | Automated safety check: Pass | AGPL-3.0 | |
| Flow Contextflowexec/flow | 137 | — | ~654 | Automated safety check: Pass | Apache-2.0 |
MicrosoftDocs/Agent-Skills
Expert knowledge for Azure Data Factory development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations…
zifeo/lade
Finalize a merge request: rebase onto main, run bugs, simplify, and specs in parallel, apply, then refactor last.
sbusso/claudeclaw
Debug container agent issues. An agent skill from sbusso/claudeclaw.
notinferred/keypaste
Keep keypaste's desktop screens, CLI output, site, README and brand assets on brand.
flowexec/flow
This project uses flow for automation. An agent skill from flowexec/flow.
microsoft/testfx
Suggests using Microsoft Testing Platform (MTP) hot reload to iterate fixes on failing tests without rebuilding.
shinpr/ai-coding-project-boilerplate
Selects and designs the smallest integration/E2E test set that proves accepted behavior at an observable boundary.
shinpr/ai-coding-project-boilerplate
Evaluates and optimizes skill file quality using 9 content patterns and 10 editing principles.
shinpr/ai-coding-project-boilerplate
Defines React environment, component architecture, state/data flow, build verification, and frontend non-functional criteria from repository evidence.
shinpr/ai-coding-project-boilerplate
Applies React/TypeScript type safety, component design, and state management rules.
shinpr/ai-coding-project-boilerplate
Selects implementation strategy (vertical slice, horizontal, or hybrid) with risk assessment.
shinpr/ai-coding-project-boilerplate
Coordinates subagents through scale-based planning, approval, implementation, verification, and escalation flows.
Categories
Defines environment variables, architecture design, and build/test commands. Technical Spec is an agent skill from shinpr/ai-coding-project-boilerplate. Defines environment variables, architecture design, and build/test commands.
Technical Spec fits situations like: configuring environment; designing architecture.
Run `npx skills add shinpr/ai-coding-project-boilerplate --skill technical-spec -a claude-code`. Or copy the skill folder (.claude/skills-en/technical-spec in shinpr/ai-coding-project-boilerplate) into .claude/skills/technical-spec in your project. Claude Code loads it when a task matches its description.
Run `npx skills add shinpr/ai-coding-project-boilerplate --skill technical-spec -a codex`. Or copy the skill folder (.claude/skills-en/technical-spec in shinpr/ai-coding-project-boilerplate) into .agents/skills/technical-spec 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 shinpr/ai-coding-project-boilerplate --skill technical-spec -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/technical-spec, .gemini/skills/technical-spec, .github/skills/technical-spec and .opencode/skills/technical-spec in your project.
SKILL.md names no scripts, command-line tools or credentials: Technical Spec 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 notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
Technical Spec is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.5k tokens (SKILL.md is roughly 5.8k 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 Technical Spec: Azure Data Factory (MicrosoftDocs/Agent-Skills, 775 stars), Finalize (zifeo/lade, 133 stars), Debug (sbusso/claudeclaw, 194 stars) and Keypaste Design (notinferred/keypaste, 160 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
shinpr (a GitHub user) maintains it in shinpr/ai-coding-project-boilerplate, which has 232 GitHub stars. The repository holds 42 skills in this directory. The repository was last updated on October 4, 2026.
Source: shinpr/ai-coding-project-boilerplate on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.