product-init

product-init is a skill for Claude Code from tikalk/adlc-team-skills. It costs 43 tokens per session (2,526 once invoked), scanned A, original, MIT.

A documentation tool that works backwards from an existing product’s code and documents to identify its product decisions. A brownfield project is an already-built product being changed or documented.

In plain words
What is it for?
Use it to analyse feature areas, classify evidence into product decision records, flag inconsistencies, and create draft decision files with an index.
Why use it?
It helps teams recover the reasoning behind an inherited or undocumented product without starting the documentation from scratch.

Skill for Claude Code

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

Good fit Use it to analyse feature areas, classify evidence into product decision records, flag inconsistencies, and create draft decision files with an index.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tikalk/adlc-team-skills/product-init
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 tikalk/adlc-team-skills --skill product-init
Clone the repo
git clone --depth 1 https://github.com/tikalk/adlc-team-skills

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 product-init

README.md
[![agentmods](https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/product-init/github.svg)](https://agentmods.dev/skills/tikalk/adlc-team-skills/product-init)
Your own site
<a href="https://agentmods.dev/skills/tikalk/adlc-team-skills/product-init"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/product-init/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 product-init

Your own site · 80×15
<a href="https://agentmods.dev/skills/tikalk/adlc-team-skills/product-init"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/product-init.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,526 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. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Memory Poisoning · line 174
    Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.
    Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
  • medium Excessive Agency · line 82
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
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 $0.00043 $0.02526
Opus 5 $0.00022 $0.01263
Sonnet 5 $0.00009 $0.00505
Haiku 4.5 $0.00004 $0.00253

Measured 4d ago against content hash 9a06afacc100, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

product-init 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 4d ago.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/bash/pdr-lib.sh, scripts/bash/setup-product-init.sh, scripts/powershell/pdr-lib.ps1, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/product/product-init/SKILL.md · 327 lines

How it starts

The opening of the file, as written. The whole thing — 327 lines — stays where its author put it; the contents beside it link to each section on GitHub.

product-init

What this skill does

Reverse-engineers product decisions from an existing product using a three-phase analysis pipeline:

  1. Discovery Agent: Scans each feature-area for raw product signals (code, docs, pricing)
  2. Pattern Agent: Classifies signals into PDR categories, scores strategic importance
  3. Synthesis Agent: Cross-feature-area analysis, flags inconsistencies

Output: Individual PDR-{NNN}.md files (status Discovered) in .adlc/drafts/pdr/ with an auto-generated pdr.md index.

When to use

  • Existing product with no formal PDRs
  • Brownfield codebase needs product documentation
  • Team onboarding — walking through product rationale
  • Post-acquisition or inherited codebase

When NOT to use

  • New product (use /product-specify instead)
  • Minor PDR updates (use /product-clarify instead)

Execution Steps

Phase 0: Environment Setup

Run setup script to resolve paths and detect feature-areas:

sh: scripts/bash/setup-product-init.sh [--json]
ps: scripts/powershell/setup-product-init.ps1

Setup output (JSON):

{
  "REPO_ROOT": "/path/to/project",
  "PDR_DRAFTS_DIR": "/path/to/project/.adlc/drafts/pdr",
  "PRD_FILE": "/path/to/project/PRD.md",
  "feature_areas": ["core", "business", "growth"],
  "next_pdr": "001"
}

Create directories:

mkdir -p "{REPO_ROOT}/.adlc/drafts/pdr"
mkdir -p "{REPO_ROOT}/.adlc/product"

Phase 1: Feature-Area Detection

Detect feature-areas from three sources:

Source Detection Pattern
Directory Structure src/auth/, features/payments/, modules/
Documentation README sections, existing PRD, ROADMAP
Pricing Tiers Starter/Pro/Enterprise feature mapping

Present detected areas:

## Detected Feature-Areas

| # | Feature-Area | Sources | Evidence |
|---|--------------|---------|----------|
| 1 | **Core** | Directory + Docs | src/users/, README "Core Features" |
| 2 | **Business** | Directory + Pricing | src/billing/, pricing.md tiers |

Reply: Y to confirm, n for monolithic, or suggest changes.

Read the full file on GitHub · 327 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 4d ago Changed · -8 lines 9a06afacc100
  2. 10d ago First seen · 335 lines · 43 tokens per session scan A 2e853cec36c0

Subscribe to this mod's changes

product-init is a skill published in the GitHub repository tikalk/adlc-team-skills (133 stars, last pushed 3d ago), licensed MIT. It adds 43 tokens to every session and 2,526 once invoked, about $0.0002 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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