Systemprompt Tools

systemprompt.io Free Tools

Six agent-callable tools hosted at systemprompt.io. All are deterministic rule engines with instant JSON responses. No authentication beyond a self-chosen agent identifier.

API contract

• Manifest with full input schemas: GET https://systemprompt.io/api/v1/tools
• Every request must carry an X-Agent-Id header (or agent_id body field): free-form, 1-64 chars. Pick a stable name for your agent and reuse it.
• Rate limit: 60 requests/hour per (IP, agent_id).
• Interactive UIs live at https://systemprompt.io/tools/{slug} with a #reference section documenting the underlying rules.

Tools

EU AI Act risk classifier

Walk the Annex III decision tree. Send {"answers": []} to get the first question; append one 0-based option index per answer and resend until you receive a classification with risk class, cited articles, obligations, and an evidence checklist.

curl -s -X POST https://systemprompt.io/api/v1/tools/eu-ai-act/run \
  -H 'Content-Type: application/json' -H 'X-Agent-Id: my-agent' \
  -d '{"answers": []}'

CLAUDE.md scorer

curl -s -X POST https://systemprompt.io/api/v1/tools/claude-md-scorer/run \
  -H 'Content-Type: application/json' -H 'X-Agent-Id: my-agent' \
  -d "$(jq -n --rawfile c CLAUDE.md '{content: $c}')"

Returns a score out of 100, grade, and per-rule pass/fail with recommendations. Useful as a CI gate for CLAUDE.md quality.

llms.txt / AGENTS.md generator and validator

Validate: {"mode": "validate", "content": "<file text>", "target": "llms"} (or "agents"). Generate: {"mode": "generate", "fields": {"site_name": ..., "description": ..., "sections": [{"title": ..., "links": [{"label": ..., "url": ...}]}]}}. Endpoint: POST https://systemprompt.io/api/v1/tools/llms-txt/run.

GitHub Actions permissions generator

{"tasks": ["checkout", "push-commits", ...]} to POST .../tools/github-actions-permissions/run returns a minimal GITHUB_TOKEN permissions block with fork and GitHub App caveats. Valid task ids are listed in the manifest.

AI ROI calculator

{"team_size", "seat_cost_monthly", "adoption_pct", "hours_saved_per_week", "loaded_hourly_cost", "implementation_cost?"} to POST .../tools/ai-roi-calculator/run returns monthly cost, value, net ROI, break-even months, and a 0.5x-1.5x sensitivity range.

AI deep review (email-gated)

The CLAUDE.md scorer and llms.txt tools also offer an LLM deep review at POST .../tools/{tool}/deep-review. These require an email field in the body and are limited to 5 requests/hour per (IP, agent_id). Only use with an email the user has provided for this purpose.

MCP alternative

Prefer MCP? The same tools are served over anonymous streamable HTTP by systemprompt.io itself (no OAuth, no key):

claude mcp add --transport http systemprompt-tools https://systemprompt.io/api/v1/mcp/systemprompt-tools/mcp

MCP tool names: classify_eu_ai_act_risk, score_claude_md, validate_llms_txt, generate_llms_txt, generate_github_actions_permissions, calculate_ai_roi.

Workflow ideas

• Classify a product under the EU AI Act during design review and attach the evidence checklist to the ticket (high-risk obligations enforce from 2026-08-02).
• Score CLAUDE.md in CI on every PR that touches it; fail below a threshold.
• Generate llms.txt and AGENTS.md for a site you are building, then validate on deploy.
• Compute minimal workflow permissions when authoring GitHub Actions instead of defaulting to write-all.