setup-analysis-delivery

setup-analysis-delivery is a skill for Claude Code from BlueprintOS/analysis-to-delivery. It costs 52 tokens per session (1,275 once invoked), scanned A, original, MIT.

A project setup guide for an analysis-to-delivery workflow, creating four configuration files that point to project knowledge, compliance rules, technology choices, and document naming rules.

In plain words
What is it for?
Use it when starting the workflow in a new or existing project, detecting its technology stack, and creating the required files under the paths/ directory.
Why use it?
It gives later workflow steps a consistent source of project context and checks that the work starts from a Git repository with the relevant project files identified.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Good fit Use it when starting the workflow in a new or existing project, detecting its technology stack, and creating the required files under the paths/ directory.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/blueprintos/analysis-to-delivery/setup-analysis-delivery
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add BlueprintOS/analysis-to-delivery --skill setup-analysis-delivery
Clone the repo
git clone --depth 1 https://github.com/BlueprintOS/analysis-to-delivery

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for setup-analysis-delivery

README.md
[![agentmods](https://agentmods.dev/badge/skills/blueprintos/analysis-to-delivery/setup-analysis-delivery/github.svg)](https://agentmods.dev/skills/blueprintos/analysis-to-delivery/setup-analysis-delivery)
Your own site
<a href="https://agentmods.dev/skills/blueprintos/analysis-to-delivery/setup-analysis-delivery"><img src="https://agentmods.dev/badge/skills/blueprintos/analysis-to-delivery/setup-analysis-delivery/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for setup-analysis-delivery

Your own site · 80×15
<a href="https://agentmods.dev/skills/blueprintos/analysis-to-delivery/setup-analysis-delivery"><img src="https://agentmods.dev/badge/skills/blueprintos/analysis-to-delivery/setup-analysis-delivery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,275 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00052 $0.01275
Opus 5 $0.00026 $0.00638
Sonnet 5 $0.00010 $0.00255
Haiku 4.5 $0.00005 $0.00128

Measured 8d ago against content hash 4dc61c8b2858, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

setup-analysis-delivery scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/user-invoked/setup-analysis-delivery/SKILL.md · 88 lines

How it starts

The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Setup Analysis-Delivery — 项目配置初始化

Contract

  • 输入: 项目根目录,已检测到的项目文件,可选的既有项目配置
  • 输出: paths/knowledge-path.mdpaths/compliance-path.mdpaths/tech-stack-path.mdpaths/doc-naming-path.md;可选 decisions.md ADR
  • 门控: 4 个 paths/*.md 文件存在且非空(legacy 项目根 *-path.md 可接受但产生 warning);knowledge-path.md 至少含 1 个真实路径后才进入下游字段工作
  • Required rules: context-pointer
  • Required paths: knowledge-path, compliance-path, tech-stack-path, doc-naming-path
  • 下一步: /grill-task

适用场景

  • 拿到一个新项目,需要接 analysis-to-delivery 工作流
  • 给现有项目补这套工作流的配置

流程步骤

1. 检测项目根

  • 必须在 git 仓库根执行(git rev-parse --show-toplevel)
  • 项目根不存在 .git → 提示用户先 git init

2. 检测项目类型

读项目根文件,推断技术栈:

  • pom.xml / build.gradle → Java/Maven/Gradle
  • package.json → Node/前端
  • pyproject.toml / requirements.txt → Python
  • go.mod → Go

3. 生成 4 个项目级配置(canonical)

默认:在项目根的 paths/ 目录下生成 4 个空模板(用户填写后提交到 git)。 这 4 个文件是唯一项目级配置加载输入:

Canonical 文件 作用 模板来源
paths/knowledge-path.md 列项目涉及的外部知识库(领域表结构、合规法规等)路径 paths/knowledge-path.md
paths/compliance-path.md 列项目适用的合规规则文件路径 + 启用开关 paths/compliance-path.md
paths/tech-stack-path.md 列后端/前端/数据库/中间件 + 团队规范路径 paths/tech-stack-path.md
paths/doc-naming-path.md 文档编号、命名前缀、存放目录 paths/doc-naming-path.md

Legacy 兼容:既有 v1.1 项目可能用项目根 *.md(knowledge-path.md 等)。setup-check.py 会把它们识别为 warning 并继续通过。生成时加 --legacy 切换到兼容输出位置(仅 v1.1 旧项目)。

4. 可选记录配置使用 ADR

  • config-used.md 不是配置文件,不参与配置加载,不属于 4 个项目级配置
  • 如需记录"本项目用了哪些配置、为什么这么选",从 templates/CONFIG_USED.md 复制生成
  • config-used.md 应作为阶段 1 交付产物提交,用于审计和交接

5. 验证

  • 4 个文件存在且非空(允许只有注释)
  • python3 scripts/setup-check.py --strict <project> 确认通过(legacy 项目根文件会产生 warning 但仍通过)
  • python3 scripts/field-alignment-check.py --help 确认脚本可用

调用的 rule

  • rules/context-pointer — 三层配置加载规则

结束条件

  • 4 个 paths/*.md 全部生成在项目根(或兼容的 legacy 项目根 *.md)
  • 用户已填写真实内容(paths/knowledge-path.md 必须至少 1 个真实路径)
  • 如生成 config-used.md,已明确标注为配置使用记录 / ADR,而非配置输入
  • setup-check.py --strict <project> 通过(warning 可接受)
  • 已提交到 git(可选,但建议)

Read the full file on GitHub · 88 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 88 lines · 52 tokens per session scan A 4dc61c8b2858

Subscribe to this mod's changes

setup-analysis-delivery is a skill published in the GitHub repository BlueprintOS/analysis-to-delivery (26 stars, last pushed 2mo ago), licensed MIT. It adds 52 tokens to every session and 1,275 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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