The Specific Situation

Anthropic offers two customization systems: Claude Code skills (SKILL.md files in your codebase) and Claude.ai Projects (web-based workspaces with custom instructions and knowledge files). Both let you give Claude persistent context. A developer wonders: should I put my deployment checklist in a Claude Code skill or a Claude.ai Project? Should my API documentation live in a skill’s references/ directory or uploaded as a Project knowledge file?

Technical Foundation

Claude Code Skills are SKILL.md markdown files stored in .claude/skills/. They run in Claude Code (CLI, desktop app, or web app at claude.ai/code). Skills have filesystem access, terminal execution, git integration, and tool permissions. They follow the agentskills.io open standard. Skills use progressive disclosure and support frontmatter controls (paths, allowed-tools, context fork, dynamic injection).

Claude.ai Projects are web-based workspaces in the Claude.ai interface. Each project has custom instructions (a system prompt), uploaded knowledge files (PDFs, code files, docs), and conversation threads. Projects support team sharing within an organization. They run in the browser with no filesystem access, no terminal, and no tool execution beyond web search and artifact generation.

The Working SKILL.md

Deployment checklist as a Claude Code skill:

---
name: deploy-checklist
description: >
  Pre-deployment verification checklist. Runs tests, checks
  environment variables, validates database migrations, and
  verifies health endpoints. Use before deploying to staging
  or production.
disable-model-invocation: true
allowed-tools: Bash(*) Read
---

# Deployment Checklist

## Pre-Deploy Verification
1. Run test suite: `pnpm test --coverage`
   - Require: All tests pass, coverage >= 80%
2. Check environment: `scripts/verify-env.sh $ARGUMENTS[0]`
   - Require: All required env vars set
3. Database: `pnpm db:migrate --dry-run`
   - Require: No pending migrations with destructive changes
4. Build: `pnpm build`
   - Require: Zero warnings, zero errors
5. Lint: `pnpm lint`
   - Require: Zero violations

## Deploy
6. Execute: `pnpm deploy:$ARGUMENTS[0]`

## Post-Deploy
7. Health check: `curl -sf https://$ARGUMENTS[0].example.com/health`
8. Smoke test: `pnpm test:smoke --env=$ARGUMENTS[0]`
9. Log tail: `scripts/tail-logs.sh $ARGUMENTS[0] --last=5m`

The same checklist in a Claude.ai Project would be pasted as custom instructions. Claude would read it on every conversation start but could not execute pnpm test, curl, or any terminal command. You would need to run commands yourself and paste output back into the conversation.

Feature comparison table:

Feature                  | Claude Code Skills | Claude.ai Projects
------------------------|--------------------|-----------------------
Code execution          | Yes (terminal)     | No
File modification       | Direct             | Not possible
Version control         | Git-tracked        | None
Team collaboration      | Git + plugins      | Shared workspace
Document search         | Grep (exact match) | Semantic (uploaded docs)
Non-developer friendly  | No (CLI required)  | Yes (web browser)
Session persistence     | Session-scoped     | Saved threads
Auto-activation         | paths field        | Always-on

Where Claude.ai Projects Win

1. Knowledge file search across large document sets. Projects accept uploaded PDFs, code files, and documentation. Claude searches across these files with every query. For workflows centered on analyzing existing documents (contract review, research synthesis, documentation Q&A), Projects handle document ingestion natively. Skills would require you to set up local files and reference them.

2. Non-developer collaboration. Projects run in a web browser. Product managers, designers, and executives can participate in project conversations without installing CLI tools. Skills require Claude Code installation and terminal familiarity.

3. Persistent conversation threads. Project conversations are saved and accessible from any device. You can start a conversation on your laptop and continue on your phone. Claude Code session history is local to the machine (unless using the web app or remote control feature).

Where Claude Code Skills Win

1. Code execution and file modification. Skills can run tests, build projects, deploy code, and modify files. Projects can only discuss code – they cannot execute or modify anything.

2. Version control integration. Skills are git-tracked. Changes are reviewable, branch-specific, and auditable. Project custom instructions are web-editable with no version history.

3. Automatic activation. Skills with paths fields activate when relevant files are touched. Projects have no concept of file context – they are always-on for every conversation.

4. Open standard portability. Skills follow agentskills.io and work across multiple AI tools. Project custom instructions are Claude.ai-specific with no portability.

5. Dynamic context injection. Skills can inject live data (!git status, `!`npm outdated) at load time. Projects have static instructions that do not change between conversations.

Hybrid Use Case

Use Claude Code skills for development workflows: deployment, testing, code review, refactoring. Use Claude.ai Projects for knowledge-intensive workflows: API documentation Q&A, design spec discussions, research paper analysis.

Practical hybrid: your team maintains a Claude.ai Project with all API documentation uploaded as knowledge files. When a developer needs to implement an API endpoint, they check the Project for the specification, then switch to Claude Code where a skill generates the endpoint code following project conventions.

Common Problems and Fixes

Project instructions too long. Claude.ai Projects have a custom instructions length limit. If your instructions are a 3-page checklist, split into a shorter instruction (“follow these principles”) and upload the detailed checklist as a knowledge file.

Skill cannot access uploaded documents. Skills read local files only. If your reference documents are uploaded to a Claude.ai Project, they are not accessible from skills. Keep reference documents as local files in your repo’s docs/ or references/ directory for skill access.

Team using both without clear boundaries. Establish a rule: code-touching workflows go in skills, document-analysis workflows go in Projects. Without this boundary, the same procedure ends up in both places and diverges.

Production Gotchas

Claude.ai Projects and Claude Code share the same underlying Claude model but operate in completely separate environments. A skill loaded in Claude Code has no awareness of a Project’s custom instructions, and a Project conversation has no access to skills. They are parallel, non-integrated systems.

Claude Code’s web app (claude.ai/code) and Claude.ai’s Projects interface look similar but serve different purposes. The web app runs Claude Code in the browser with full filesystem access (via remote machine). Projects are a document-centric conversation workspace. Do not confuse the two.

Checklist