lenserfight: Skill for Claude Code

.agents/skills/product-owner-decider/SKILL.md

product-owner-decider is a skill for Claude Code, Codex from conectlens/lenserfight. It costs 31 tokens per session (421 once invoked), scanned A, original, MIT.

A product decision guide for LenserFight, used to turn unclear requests into decisions about scope, priorities, acceptance criteria, and implementation order. Acceptance criteria are the conditions a feature must meet to be considered complete.

In plain words
What is it for?
Use it to accept, reject, defer, or split features; rank competing work; define completion conditions; assess risks; and produce a formal product decision memo.
Why use it?
It helps resolve competing ideas and ambiguous requests while protecting the product roadmap from work that is too broad or poorly defined.

Skill for Claude CodeCodex

Written for Claude Code and Codex: disable-model-invocation in frontmatter, but also agents/openai.yaml present. Also seen: installed under .agents/ (shared by several agents).

This is conectlens/lenserfight's own configuration. It tells Claude Code and Codex how to work on lenserfight itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything lenserfight configures →

Reuse

Borrowing it

Nothing to install: this file belongs to conectlens/lenserfight. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/conectlens/lenserfight/main/.agents/skills/product-owner-decider/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/conectlens/lenserfight

Made for: Claude Code, Codex.

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-owner-decider

README.md
[![agentmods](https://agentmods.dev/badge/skills/conectlens/lenserfight/product-owner-decider/github.svg)](https://agentmods.dev/skills/conectlens/lenserfight/product-owner-decider)
Your own site
<a href="https://agentmods.dev/skills/conectlens/lenserfight/product-owner-decider"><img src="https://agentmods.dev/badge/skills/conectlens/lenserfight/product-owner-decider/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-owner-decider

Your own site · 80×15
<a href="https://agentmods.dev/skills/conectlens/lenserfight/product-owner-decider"><img src="https://agentmods.dev/badge/skills/conectlens/lenserfight/product-owner-decider.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 421 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 $0.00031 $0.00421
Opus 5 $0.00015 $0.00211
Sonnet 5 $0.00006 $0.00084
Haiku 4.5 $0.00003 $0.00042

Measured 11d ago against content hash 43cabf49bccf, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

product-owner-decider 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 11d 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.

.agents/skills/product-owner-decider/SKILL.md · 35 lines

What it actually says

Product Owner Decider (Lenser)

Use when

  • Project direction or milestone scope is ambiguous.
  • Competing AI agent features need a priority recommendation.
  • A feature must be accepted, rejected, sliced, or deferred to protect the roadmap.

Restrictions

  • Read-First Protocol: You must update docs/* files ONLY after a formal planning or reviewing phase is fully complete and approved.

Workflow

  1. Context Load: Read docs/* to align with the current LenserFight vision and goals.
  2. Logic Processing: Use the Strategic Flowchart to determine the path.
  3. Value Mapping: Calculate scores using the Weighted Decision Matrix.
  4. Execution: Return a formal Product Decision Memo (from Template) with a Mermaid Gantt schema for the timeline.

Load only when needed

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. 11d ago First seen · 35 lines · 31 tokens per session scan A 43cabf49bccf

Subscribe to this mod's changes

product-owner-decider is a skill published in the GitHub repository conectlens/lenserfight (18 stars, last pushed 1mo ago), licensed MIT. It adds 31 tokens to every session and 421 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.