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mcp/skillhub

Agent Skill

Frontend To Backend Requirements skill

frontend-to-backend-requirementssoftaworks/agent-toolkitskills/frontend-to-backend-requirements/SKILL.md

Document frontend data needs for backend developers. Use when frontend needs to communicate API requirements to backend, or user says 'backend requirements', 'what data do I need', 'API requirements', or is describing data needs for a UI.

2.6kMIT

always on

54 tokname + description

once used

1,250 tokSKILL.md body

bundled files

15 KB

repo stars

2.6kGitHub

Install the Frontend To Backend Requirements skill

Skills CLI (Claude Code, Codex, Cursor and others)

npx skills add https://github.com/softaworks/agent-toolkit --skill frontend-to-backend-requirements

Claude Code, by hand (all projects)

git clone --depth 1 https://github.com/softaworks/agent-toolkit.git /tmp/agent-toolkit
mkdir -p ~/.claude/skills
cp -R /tmp/agent-toolkit/skills/frontend-to-backend-requirements ~/.claude/skills/frontend-to-backend-requirements

For one project only, copy the folder into .claude/skills/ in that project instead. The agent picks it up when a task matches its description.

What it costs your context

Agent Skills load in three steps. Tokens counted with the o200k tokenizer; your model's count will differ a little.

WhenWhat loadsCost
Every sessionName and description54 tok
When the agent uses itThe SKILL.md instructions1,250 tok
Only if opened1 bundled files (5 KB)varies

Until it is used, frontend-to-backend-requirements costs about 25× less than the median MCP server we measured (1,363 tokens on every turn). Installing all 43 skills from softaworks/agent-toolkit would load 2,462 tokens of descriptions. Skills vs MCP study

Checks

Our checks found nothing to flag: it follows the Agent Skills specification's naming and size guidelines and doesn't pipe downloads into a shell.

Checked 2026-10-22 · method

What's inside

The headings of its SKILL.md. Read the full file on GitHub.

  • Backend Requirements Mode
  • The Point
  • What You Own vs. What Backend Owns
  • Workflow
  • Step 1: Describe the Feature
  • Step 2: List Data Needs
  • Step 3: Surface Uncertainties
  • Step 4: Leave Room for Discussion
  • Output Format
  • Good vs. Bad Requests
  • Bad (Dictating Implementation)
  • Good (Describing Needs)
  • Bad (Assuming Structure)
  • Good (Describing Relationship)
  • Bad (No Context)
  • Good (With Context)
  • Encouraging Pushback
  • Rules
  • After Backend Responds

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