shipping-artifacts▌
phuryn/pm-skills · updated Jun 11, 2026
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The durable documentation set that makes an AI-built (vibe-coded) app reviewable before shipping. A small core every app needs — architecture, user/permission flows, permissions, variables/secrets, and a test-coverage map — plus conditional docs added only when they apply: emails, scheduled work, SEO, and embedded agents/automation. Defines what each doc must capture and how a reviewer or auditor uses it. Use when documenting a codebase for handoff, mapping user journeys and trust-boundary crossings, planning test coverage, or preparing for a security or performance audit.
| name | shipping-artifacts |
| description | "The durable documentation set that makes an AI-built (vibe-coded) app reviewable before shipping. A small core every app needs — architecture, user/permission flows, permissions, variables/secrets, and a test-coverage map — plus conditional docs added only when they apply: emails, scheduled work, SEO, and embedded agents/automation. Defines what each doc must capture and how a reviewer or auditor uses it. Use when documenting a codebase for handoff, mapping user journeys and trust-boundary crossings, planning test coverage, or preparing for a security or performance audit." |
Shipping Artifacts: The Docs That Make AI-Built Code Reviewable
Purpose
AI agents write code fast, but they leave no durable record of intent — what the system is supposed to do, who is allowed to do what, where the secrets live, which rules are actually verified. Without that record, no human (and no auditing agent) can tell whether the code is safe to ship. This skill defines the small set of documents that restore reviewability.
These docs live in /documentation/ and are written for two readers: a human reviewer and the next AI coding agent. They are the intended-state half of every later audit — a security or performance review is only as good as the intent it can compare the code against.
How the set is organized
The set is not a fixed list — it is a small core plus conditional docs you add only when the capability exists.
- Core docs — every reviewable app has these surfaces, so always produce them.
- Conditional docs — include one only if the app actually has that capability. If it doesn't, write a single line in
architecture.md("No scheduled work — nocron.md.") rather than inventing an empty document. Reviewability comes from an honest map, and "we don't do X" is part of the map. - Most docs are reverse-engineered from code by
/document-app. The one exception istests.md, which is derived from the other docs by/derive-tests— it is the verification map, not a description of a subsystem.
Be brutally honest about the current state without being paranoid. The job is an accurate map, not a clean bill of health. Each doc is short, table-and-bullet heavy, and skips generic theory.
Core documents
Each entry: file · one-line purpose · what it must capture · how a reviewer uses it.
-
architecture.md— what the system is and how it hangs together.- Must capture: product overview + key assumptions; tech stack; how auth/sessions/claims flow end to end; the trust boundaries (e.g. service-role vs. client); a short Known risks / assumptions list (each entry backed by where it shows up in the code, not a generic checklist); a "Related Documents" index of every other doc produced.
- Reviewer use: the root document — everything else is cross-referenced from here.
-
flows.md— the journeys where permissions and side effects are actually exercised.- Must capture: each load-bearing flow as actor + precondition + success outcome; the step-by-step sequence across UI → server → data → jobs → providers → agents; the authz check at each protected step (which claim/role/scope, on which resource, and the expected deny case); the trust-boundary crossings (browser→server, server→provider, job→app, agent→tool, webhook→app); the state changes and side effects each step causes (writes, emails queued, jobs triggered, outbound calls).
- Reviewer use: the runtime view a static
permissions.mdmatrix can't show — where and in what order authorization is enforced, and where it can be skipped. - Anti-PRD rule: a flow that doesn't touch permissions, data integrity, external side effects, money, privacy, or operational safety does not belong here. This is a security/operations map, not a feature spec.
-
permissions.md— who is allowed to do what.- Must capture: roles/claims; where scope is derived (token vs. DB); a resource × operation × role matrix; which tables have row-level security and which rely on code-enforced checks.
- Reviewer use: the baseline an access-control audit compares the code against.
flows.mdshows it in motion; this is the static reference.
-
variables.md— configuration and secrets, mapped to risk.- Must capture: a table of Name · used-by · scope (server/client) · source · rotation · risk; explicit confirmation that no secret is bundled client-side; a pre-go-live checklist.
- Reviewer use: the secrets/PII-leak surface and the rotation plan during incident response.
-
tests.md— the verification map: which documented rules are actually checked, which are only proposed, and which are checked by nothing.- Must capture, in three clearly separated sections so the map can't read falsely green:
- Existing coverage — tests that are in the repo today, each tied to the rule it pins (so the map reflects reality, not a wish-list).
- Proposed tests — recommended cases not yet written, marked by test type (automated unit/integration · guarded live · manual review).
- Gaps — documented rules with no verification at all, ranked by what crossing them exposes.
- Each row carries: use-case → rule → expected behavior (including the deny/negative case) → evidence source (doc + code) → status (existing / proposed / none). It also notes which checks are CI-required and gate merges to
main. - Reviewer use: the operational form of "documented == implemented" — it shows whether each rule the other docs claim is actually pinned by a test today, only proposed, or unverified.
- Produced by
/derive-tests(not/document-app), because it is derived from the other docs and the existing test suite rather than read off a subsystem.
- Must capture, in three clearly separated sections so the map can't read falsely green:
Conditional documents (include only when the capability exists)
-
emails.md— every notification the system sends. Include only if the app sends transactional or automated email.- Must capture: the queue → processor → provider path; templates and the variables they accept; retry/backoff behavior; where to look when a send fails.
- Reviewer use: spotting unvalidated template inputs and PII exposure boundaries.
-
cron.md— all scheduled work and how to operate it safely. Include only if scheduled or background jobs exist.- Must capture: an inventory table (job → schedule → function → secrets → limits → retry); how each job stays idempotent; how internal calls authenticate; where to see last runs.
- Reviewer use: finding forgeable triggers and unbounded background jobs.
-
seo.md— how a single-page app handles SEO and social previews. Include only if there are public/indexable or bot-facing routes.- Must capture: the preview approach (static meta / prerender / edge HTML); a route → needs-SEO → public-data-only table; how dynamic metadata is sanitized; bot-vs-human routing.
- Reviewer use: catching public-data-only violations and metadata injection on bot routes.
-
automation.md— embedded agents and other automation paths. Include only if the app embeds AI agents, LLM workflows, tool-calling, webhooks, or external automation.- Must capture, per automation/agent: trigger + owner + whether it runs automatically or only after approval; the inputs it may read and the exact tools/APIs it may call (the tool surface is itself a hard guardrail); where steering lives (the prompt) vs. the non-prompt hard guardrails; the output contract back to the app (schema, validation, failure handling); app-owned side effects vs. agent-owned suggestions; and the controls — approval gates, audit/timeline logging, rate limits, retries, kill switch.
- Reviewer use: makes hidden automation paths visible and draws the line between what an agent proposes and what the app enforces — the highest-risk surface in modern AI-built apps.
Notes
- Each produced doc adds a reference to itself in
architecture.mdunder a "Related Documents" section, so the set stays discoverable. - Skip any conditional document that doesn't apply, and say so in one line rather than inventing content.
- Keep examples and finished templates out of these docs — they describe this system, not the general method.
- The agent operating-context file (
CLAUDE.md/AGENTS.md) is a different artifact — instructions derived from these docs, not system documentation. It is produced at the handoff step by/ship-check, not here. tests.mdis produced by/derive-tests; the rest are produced by/document-app.- Do not include an "updated date" line; the file's history is the source of truth.
How to use shipping-artifacts on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add shipping-artifacts
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches shipping-artifacts from GitHub repository phuryn/pm-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate shipping-artifacts. Access the skill through slash commands (e.g., /shipping-artifacts) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★51 reviews- ★★★★★Chaitanya Patil· Dec 24, 2024
shipping-artifacts fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Lucas Kapoor· Dec 16, 2024
shipping-artifacts is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Arjun Mehta· Dec 12, 2024
shipping-artifacts reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Piyush G· Nov 15, 2024
Registry listing for shipping-artifacts matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Jin Gonzalez· Nov 7, 2024
Solid pick for teams standardizing on skills: shipping-artifacts is focused, and the summary matches what you get after install.
- ★★★★★Arjun Anderson· Nov 3, 2024
We added shipping-artifacts from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Min Zhang· Oct 26, 2024
shipping-artifacts has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Omar Kim· Oct 22, 2024
shipping-artifacts fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Shikha Mishra· Oct 6, 2024
shipping-artifacts reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Noah Agarwal· Sep 25, 2024
shipping-artifacts is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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