Agent skill

Technical Spec

by shinpr in shinpr/ai-coding-project-boilerplate

Defines environment variables, architecture design, and build/test commands.

MITAuto-check: notesDevOps & Cloud

Install Technical Spec

skills CLI
$ npx skills add shinpr/ai-coding-project-boilerplate --skill technical-spec -a claude-code

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

GitHub CLI
$ gh skill install shinpr/ai-coding-project-boilerplate technical-spec --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/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-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
technical-spec
GitHub stars
232
Token cost
~1.5k tokens
SKILL.md length
713 words
Files
1
Skills in repo
42
Repo updated
First seen
Licence
MIT

At a glance

Defines environment variables, architecture design, and build/test commands.

  • Works in 3 steps: Single Data Source: Store the same… → Structured Data Priority: Use parsed… → Responsibility Separation: Each layer…
  • Configuring environment
  • SKILL.md covers Prerequisite Detection, Basic Technology Stack Policy, Environment Variable… and Architecture Design, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

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.

When your agent uses it

  • Configuring environment
  • Designing architecture

Example prompts

  • “Use the technical-spec skill to define environment variables, architecture design, and build/test commands”
  • “/technical-spec”

Workflow steps

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

  1. Single Data Source: Store the same information in only one place
  2. Structured Data Priority: Use parsed objects rather than JSON strings
  3. Responsibility Separation: Each layer names the data or behavior it owns and the boundary through which other layers use it

What it can do on your machine

Read from SKILL.md and the folder at commit 56913a2. 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

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.

Always · name and description, kept in context so the agent knows when to use it
~38
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:23
    - Keep local `.env` files outside version control and provide non-secret example files for required variable names

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 shinpr/ai-coding-project-boilerplate at commit 56913a2, republished under its MIT licence (© shinpr). 713 words, ~1,452 tokens.

Download SKILL.mdSave it as .claude/skills/technical-spec/SKILL.md (or your agent's skills folder).
name
technical-spec
description
Defines environment variables, architecture design, and build/test commands. Use when configuring environment or designing architecture.

Technical Design Rules

Prerequisite Detection

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.

Basic Technology Stack Policy

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.

Environment Variable Management and Security

Environment Variable Management
  • Centrally manage environment variables and the build-time validation mechanism that enforces their type safety
  • Read environment variables through one typed configuration boundary; application code consumes validated configuration values
  • Give a variable a default only when requirements define valid behavior for absence; otherwise fail configuration validation with the variable name and expected format
Security
  • Keep local .env files outside version control and provide non-secret example files for required variable names
  • Load API keys and secrets from the configured secret store or runtime environment boundary
  • Log and return only fields approved for the current trust boundary; redact credentials, tokens, personal data, and internal diagnostics before returning data across an untrusted boundary

Architecture Design

Architecture Design Principles

Select architecture using these observable decisions:

  • Responsibilities: Each module/layer names the behavior it owns and the behavior it delegates
  • Dependency direction: Imports and runtime calls follow the project boundary rules observed in configuration or representative implementations
  • State/data ownership: Each persisted or mutable value has one authoritative owner
  • Verification boundary: Each public contract has a unit, integration, or E2E check that can observe it

Unified Data Flow Principles

Basic Principles
  1. Single Data Source: Store the same information in only one place
  2. Structured Data Priority: Use parsed objects rather than JSON strings
  3. Responsibility Separation: Each layer names the data or behavior it owns and the boundary through which other layers use it
Data Flow Best Practices
  • Validation at Input: Validate data at input layer and pass internally in type-safe form
  • Centralized Transformation: Consolidate data transformation logic in dedicated utilities
  • Structured Logging: Output structured logs at each stage of data flow

Build and Testing

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 Commands
  • build - TypeScript build
  • type-check - Type check (no emit)
Testing Commands
  • test - Run tests
Show full SKILL.md (295 more words)Show less
Quality Assurance Mechanism Awareness

Before executing quality checks, identify what quality mechanisms exist for the change area:

  • Primary detection: inspect the change area's file types, project manifest, and configuration to identify applicable quality tools
    • Check CI pipeline definitions for checks that cover the affected paths
    • Check for domain-specific linter or validator configurations (e.g., schema validators, API spec validators, configuration file linters)
    • Check for domain-specific constraints in project configuration (naming rules, length limits, format requirements)
  • When a task file supplies Operation Verification Methods, run them as task-specific checks
  • Include discovered domain-specific checks alongside standard quality phases below
Quality Check Requirements

Quality checks are mandatory upon implementation completion:

Phase 1-3: Code Quality Checks

  • Auto-detect and execute the following from package.json scripts:
    • lint + format check
    • Detect unused exports
    • Detect circular dependencies
    • TypeScript build

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 execution

Transition 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.

Auxiliary Commands
  • check:all - Overall integrated check (check:code + test) *for manual batch verification
  • format - Format fixes
  • lint:fix - Lint fixes
Troubleshooting
  • Dependency errors: First record the failing resolver output, selected package manager, manifest, and lockfile state. Use the repository's established clean-install command only when it preserves the lockfile and generated artifacts; request approval before an operation that removes or regenerates dependency state

© shinpr, 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 .claude/skills-en/technical-spec of shinpr/ai-coding-project-boilerplate.

Open the folder on GitHubat commit 56913a2

Compare with similar skills

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.

Technical Spec compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Technical Spec this skillshinpr/ai-coding-project-boilerplate232—~1.5kAutomated safety check: NotesMIT
Azure Data FactoryMicrosoftDocs/Agent-Skills7751 repos~16kAutomated safety check: PassCC-BY-4.0
Finalizezifeo/lade133—~1kAutomated safety check: PassMPL-2.0
Debugsbusso/claudeclaw1941 repos~3.3kAutomated safety check: NotesMIT
Keypaste Designnotinferred/keypaste160—~865Automated safety check: PassAGPL-3.0
Flow Contextflowexec/flow137—~654Automated safety check: PassApache-2.0

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Questions about Technical Spec

What does Technical Spec do?

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.

When should I use Technical Spec?

Technical Spec fits situations like: configuring environment; designing architecture.

How do I install Technical Spec in Claude Code?

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.

How do I install Technical Spec in Codex?

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.

Can I use Technical Spec 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 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.

What does Technical Spec need to run?

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

Does Technical Spec 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 Technical Spec safe to install?

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.

What licence does Technical Spec use?

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.

How many tokens does Technical Spec use?

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.

What are the alternatives to Technical Spec?

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.

Who maintains Technical Spec?

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.