Show HN: Spendict – a performance marketer's verdict for AI agents, over MCP

Spendict launches a deterministic AI tool that evaluates advertisements before any budget is spent, providing a run, fix_first, or kill verdict based on performance marketing expertise. The tool integrates via MCP, CLI, or REST and aims to reduce ad-spend waste by scoring hooks, angles, audience fit, and compliance against platform rules.

A deterministic run / fix first / kill verdict for every ad — before you spend on it, not after. MCP · CLI · Skill · REST · 100 free verdicts · about a penny a call after “Cut your ad-spend leak in 30 days.” “Unlock the AI advantage today ✨” “Founders: your CAC is lying to you.” “The 1 secret marketers don't want you to know” “We saved a DTC brand $42k in Q3.” “Meta CPMs up 34%. Here's what still works.” “Try our platform. It's really good.” “Your PMax is fighting your Search. Fix it.” “Stop A/B testing headlines. Start testing offers.” “Scale to $1M/mo with one weird trick” the whole batch, no cherry-picking — 3 run · 3 fix first · 4 killed before a cent of spend Drop in the Skill and your agent gates every ad automatically — or wire it up over MCP, the CLI, or plain REST. Same four tools, same verdict, same quota. Same SKILL.md works in Claude Code, Cursor, Codex, and Gemini. npx skills add spendict/skills The skill calls Spendict over MCP or the CLI — connect once see the MCP or CLI tab . Your agent now gets a run / fix first / kill on every ad before it recommends launching. Four tools, one deterministic verdict each. The budget only moves on ads that earned it. Scores hook, angle, clarity, audience fit, platform fit, CTA, and compliance — and names the single predicted failure mode before a cent is committed. Budget allocation, audience setup, bid strategy, measurement — checked against each platform's actual rulebook, before the structure fragments your spend. Feed it live metrics and it separates creative fatigue from structural problems — instead of guessing which lever to pull. Give it the product and the goal; it returns a structure-validated targeting strategy your agent can build from directly. The judgment inside comes from performance marketers with 10+ years in paid social — they directed the model's development and calibrated every verdict against real ads. Six AI-generated ad hooks, scored by the same engine that grades yours — each with the predicted failure mode attached, not just a number. “Unlock the AI advantage today ✨” Zero specificity, generic AI puffery “I switched from boosting posts to this and finally stopped guessing.” Named pain plus concrete outcome “Stop guessing. Start scaling your ad spend with confidence.” Vague CTA, no proof point “The future of marketing is here.” No product, no audience, no hook “3 signs your Meta campaign is bleeding budget and how to fix 2 today ” Specific plus curiosity plus a real fix “Transform your business with our revolutionary platform.” Buzzword salad, zero mechanism Four guardrails baked into every call — not settings you have to remember to turn on. Streamable HTTP — works in Claude, Cursor, Windsurf, n8n out of the box. Same verdicts, same key — one-for-one REST endpoints for any other stack. Every key is hashed server-side; bearer-token auth on every call. A maxed-out key never triggers a model call — and failed calls are refunded. Real performance reconciles against the tool's own earlier pre-flight call. Marketers with 10+ years in paid social directed the model's development — real ads, not scraped trend data.