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-specifygit 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-specify)<a href="https://agentmods.dev/skills/tikalk/adlc-team-skills/product-specify"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/product-specify/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-specify"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/product-specify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
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 160 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 66 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.
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 | $0.00041 | $0.02470 |
| Opus 5.5 | $0.00016 | $0.00988 |
| Sonnet 5.5 | $0.00008 | $0.00494 |
| Haiku 4.5 | $0.00004 | $0.00247 |
Grade A, and why
product-specify 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 5d 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 — 301 lines — stays where its author put it; the contents beside it link to each section on GitHub.
product-specify
What this skill does
Transforms a high-level product idea into documented Product Decision Records (PDRs) through interactive exploration and trade-off analysis.
Key insight: Discussion and exploration happen before committing to formal documentation. The goal is to surface trade-offs, validate assumptions, and make informed decisions collaboratively.
Output: Individual PDR-{NNN}.md files (status Proposed) in .adlc/drafts/pdr/ with an auto-generated pdr.md index.
When to use
Note: Routine decision capture is handled by team-boot's continuous capture mechanism, which writes lightweight drafts directly to
.adlc/drafts/. This skill is for interactive deep-dive exploration — when you want guided trade-off analysis, multi-option comparison, or structured decision facilitation before documenting.
- New product from scratch
- Major product pivots
- Documenting verbal decisions formally
- Team onboarding — walking through product rationale
When NOT to use
- Existing product (use
/product-initinstead) - Minor PDR updates (use
/product-clarifyinstead)
Execution Steps
Phase 0: Environment Setup
sh: scripts/bash/setup-product-specify.sh [--json]
ps: scripts/powershell/setup-product-specify.ps1
Requires: the product-clarify skill (provides pdr-lib.sh): adlc-cli skills add tikalk/adlc-team-skills --skill product-clarify
Setup output (JSON):
{
"REPO_ROOT": "/path/to/project",
"PDR_DRAFTS_DIR": "/path/to/project/.adlc/drafts/pdr",
"PRD_FILE": "/path/to/project/PRD.md",
"next_pdr": "001"
}
Phase 1: Feature-Area Decomposition (Optional)
Analyze the product for distinct business domains. Auto-decompose if multiple domains detected. Use --no-decompose to skip.
Present detected areas:
## Detected Feature Areas
| # | Feature Area | Key Domains | Rationale |
|---|--------------|-------------|-----------|
| 1 | **Auth** | Authentication, Authorization | Core user entry |
| 2 | **Core** | User Management, Profiles | Core data |
| 3 | **Business** | Payments, Subscriptions | Revenue domain |
Reply: Y to confirm, n for monolithic, or suggest changes.
What ships with it
2 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.
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.
- 5d ago Changed e7a1da97b0f0
- 25d ago Changed 90fe6a9cbaaa
- 26d ago Changed · +2 lines c13ab7c38685
- 1mo ago Changed · +6 lines · +13 tokens per session 1bef07f11cab
- 1mo ago Changed · -23 tokens per session fcc6701595c4
- 1mo ago Changed · -8 lines c8f5822d1a79
- 1mo ago First seen · 301 lines · 51 tokens per session scan A d2614e0ca72d
product-specify is a skill published in the GitHub repository tikalk/adlc-team-skills (143 stars, last pushed today), licensed MIT. It adds 41 tokens to every session and 2,470 once invoked, about $0.0002 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 2026-08-30.
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