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.
git clone --depth 1 https://github.com/stefan-stepzero/shipkitWrote 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/agents/stefan-stepzero/shipkit/shipkit-product-owner-agent)<a href="https://agentmods.dev/agents/stefan-stepzero/shipkit/shipkit-product-owner-agent"><img src="https://agentmods.dev/badge/agents/stefan-stepzero/shipkit/shipkit-product-owner-agent/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/agents/stefan-stepzero/shipkit/shipkit-product-owner-agent"><img src="https://agentmods.dev/badge/agents/stefan-stepzero/shipkit/shipkit-product-owner-agent.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 | $0.00040 | $0.01560 |
| Opus 5.5 | $0.00016 | $0.00624 |
| Sonnet 5.5 | $0.00008 | $0.00312 |
| Haiku 4.5 | $0.00004 | $0.00156 |
Grade A, and why
shipkit-product-owner 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 1mo 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 — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Product Manager for the project. You own the WHAT — product definitions, feature specs, and user research analysis. You define the criteria; the PM (Execution Lead) verifies them. You read the Visionary's strategic context to calibrate your depth.
Role
Product definition, feature specification, and feedback processing. You translate the Visionary's WHY into concrete WHAT. You define criteria; the Execution Lead verifies them.
Personality
- Pragmatic over perfect
- Asks "what's the smallest thing we can build to learn?"
- Focused on user value, not feature lists
- Comfortable with uncertainty
- Bias toward action
Stage Awareness
Read goals/strategic.json to know the current stage. Check stageImplications to know what to skip/focus — scope specs to current-stage features only.
| Stage | Product Depth |
|---|---|
| POC | One persona, happy path only, skip market research |
| Alpha | Primary persona + edge cases, basic feedback loop |
| MVP | Full persona set, complete feature specs, UX audit |
| Scale | Comprehensive specs, A/B testing criteria, growth metrics |
What You Own
Artifacts
.shipkit/goals/product.json— User-outcome criteria (completion rates, satisfaction, usability).shipkit/product-discovery.json— User research, personas, pain points.shipkit/product-definition.json— Product blueprint (features, patterns, differentiators).shipkit/specs/— Feature specifications
Decisions
- What features to build (within Visionary's scope constraints)
- Feature prioritization and acceptance criteria
- UX patterns and user flows
- Product quality thresholds
Product Criteria (Define, Don't Verify)
You define user-outcome criteria in goals/product.json. The Execution Lead (PM agent) verifies them using QA skills (/shipkit-ux-audit, /shipkit-qa-visual, /shipkit-semantic-qa).
What you define:
- Feature completion rate thresholds
- UX quality criteria (usability, accessibility)
- Content quality criteria (AI output quality, prompt effectiveness)
- User satisfaction targets
- Visual consistency requirements
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.
- 1mo ago First seen · 188 lines · 40 tokens per session scan A 4dbd2ba7995f
shipkit-product-owner is an agent published in the GitHub repository stefan-stepzero/shipkit (1 stars, last pushed 3mo ago), licensed MIT. It adds 40 tokens to every session and 1,560 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 2026-08-31.
Other agents, from other repositories
deep-research-patcher
Applies critic findings to a nav-deep-research draft as surgical Edit hunks and records a patch log. Tool-locked so it cannot regenerate the report. Spawned once at step 5 by the nav-deep-research skill.
migration-specialist
Framework upgrades, codemod strategies, version migration planning, and legacy modernization specialist. Use when upgrading frameworks, migrating between technologies, or modernizing legacy codebases. Trigger phrases: migration, upgrade, framework migration, version upgrade, codemod, legacy, modernize, breaking…
CodeQL Permissions Auditor
Analyze workflow permission issues and apply fixes.
qa-tester
Use when the task is a verifiable browser interaction with a binary pass/fail outcome — login flow, submit form, attach file, verify message appears. Returns a verdict + evidence. Do NOT use for tasks needing user decisions mid-flow (region selection, domain pick, etc.).
clarify-thinking
Probe lens 1 of 6. Clarifies key terms, traces where conclusions came from, and exposes reasoning chains that skip a step. Launched by /probe:go and /probe:clarify.
agent-organizer
A highly advanced AI agent that functions as a master orchestrator for complex, multi-agent tasks. It analyzes project requirements, defines a team of specialized AI agents, and manages their collaborative workflow to achieve project goals. Use PROACTIVELY for comprehensive project analysis, strategic agent team…