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.
npx skills add tikalk/adlc-team-skills --skill product-bootgit clone --depth 1 https://github.com/tikalk/adlc-team-skillsWrote 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.
[](https://agentmods.dev/skills/tikalk/adlc-team-skills/product-boot)<a href="https://agentmods.dev/skills/tikalk/adlc-team-skills/product-boot"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/product-boot/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.
<a href="https://agentmods.dev/skills/tikalk/adlc-team-skills/product-boot"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/product-boot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00079 | $0.01499 |
| Opus 5.5 | $0.00032 | $0.00600 |
| Sonnet 5.5 | $0.00016 | $0.00300 |
| Haiku 4.5 | $0.00008 | $0.00150 |
Grade A, and why
product-boot 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
product-boot
Overview
One of the five class boots surfaced by team-boot's Class Boots
catalog. team-boot injects the always-relevant team context (constitution,
CDR index, skills registry) at session start; this skill loads the
product decision layer on demand — the Accepted PDR index from project
memory — and pairs it with decision capture so new product choices are
recorded (/product-specify) rather than evaporating.
Reading decisions and recording decisions are one loop: existing PDRs inform the work; decisions made during the work flow back into the same record system.
When to Use
Invoke at the START of a matching task — before planning the todo list and before implementation — so the PDR context informs planning. Never defer to session end.
Invoke when:
- Starting product work (PRD generation, feature definition, roadmap planning, GTM decisions).
- The session turns product-shaped mid-flight: feature scope, persona definition, monetization, pricing, or target-market choices emerge.
- Reviewing an existing product's decision backdrop (
/product-analyze,/product-roadmapbenefit from the loaded index).
Core Process
Step 1: Locate the PDR Index
From the current working directory (do NOT walk up parent directories):
- Primary:
docs/adlc/memory/pdr/pdr.md(generated by/product-implement; rows start with| PDR) - Fallback:
.adlc/memory/pdr/pdr.md(legacy layout, pre-ADR-401)
If neither exists but docs/adlc/memory/pdr/PDR-*.md or legacy
.adlc/memory/pdr/PDR-*.md files do, synthesize a
lean table from each file (ID from filename; Feature-Area/Status/Title
from frontmatter or first heading). If the directory is empty or absent,
report 0 PDRs — never fabricate rows.
When no local memory index exists in the current working directory and the
directory sits inside a workspace (detected via a .gitmodules marker in an
ancestor), read the workspace root's docs/adlc/memory/ index instead
(ADR-401 dual-read order applies: docs/adlc/memory first, legacy
.adlc/memory fallback).
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.
- 10d ago Changed · +4 lines f363c824815f
- 13d ago Changed · +15 lines a715c2524288
- 15d ago Changed · +4 lines · +12 tokens per session afb318eb4ad9
- 16d ago Changed · +3 lines 52c3d57181b7
- 24d ago Changed · +15 lines 69997a1164e8
- 25d ago First seen · 98 lines · 67 tokens per session scan A 8358a9d14230
product-boot is a skill published in the GitHub repository tikalk/adlc-team-skills (141 stars, last pushed yesterday), licensed MIT. It adds 79 tokens to every session and 1,499 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-21.
Other skills, from other repositories
batch-all-issues
Resolve every open issue one at a time: fact-check each with web research, close the ones that need no action, and run the goal-pr skill to fix, review, and merge the ones that do — repeating until no actionable issues remain.
post-issue-comment
Post a reply comment on a GitHub issue in English with a natural, concise writing style, based on the intent passed as arguments.
orchestrate
Pipeline orchestration: dispatch the highest-priority ready tasks/work units to agents, manage capacity, and coordinate the Todo to Done flow. Invoked as /agiflow:orchestrate. Uses listtasks, listactivetasksbyorg, listmembers, updatetask, getworkunitprogress.
ticket-craft
Create Jira/Asana/Linear tickets optimized for Claude Code execution - AI-native ticket writing.
create-scrap-issue
Create a GitHub issue that consolidates passed content into a single scrap issue with background context and solution details, labeled as maintainer-scrap. Use when the user wants to create a scrap issue, jot down notes as a GitHub issue, or save findings for later.
project-plan
Turn a product goal or feature request into a clear Agiflow project plan with small, testable tasks in Planning status. Use when starting a project, decomposing a feature, clarifying requirements, or converting an idea into an actionable backlog.