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Spec-driven dev workflow. Invoke before implementing any feature or fixing any bug — spec lookup, clarifications, plan approval.
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Add conversion measurement to a live ChatGPT Ads campaign - choose between the OpenAI Conversions API (server-side) and the JavaScript Pixel (client-side), define the events that matter, and roll out without delaying launch. Use when setting up ChatGPT Ads tracking, CAPI vs pixel decisions, measuring leads/signups/purchases from ChatGPT Ads, or moving from CTR optimization to conversion-based optimization.
Build, review, and scale a ChatGPT Ads campaign from your existing Google/Meta/Microsoft text ads and website. Use when launching ChatGPT Ads, building a ChatGPT Ads campaign workbook, repurposing existing search/social ads for ChatGPT, writing context hints (not keywords), or scaling to 100+ upload-ready ads. Covers the full 9-step golden-path workflow with copy-paste prompts.
Comparing ad-platform performance with CRM; attribution gaps; 'ad platform shows conversions but CRM shows zero'; UTM/pixel issues; last-click vs data-driven. Covers data-source hierarchy and gap diagnosis.
Defining GTM metrics, pipeline efficiency, AI cost metrics, TTFV, CAC/LTV/NRR, magic number, attribution models, weekly review cadence.
Multi-platform product launches: Product Hunt, Hacker News, BetaList, AppSumo, waitlist, launch day, multi-channel rollout — pre-launch through post-launch.
SPEAR loop for any non-trivial agent task — Scope, Plan, Execute, Assess, Resolve. Prevents the strong-start-weak-finish failure mode by forcing an explicit MECE rubric and a Plan→Execute→Assess inner loop until the rubric passes.
| name | spec-driven-dev |
| description | Spec-driven dev workflow. Invoke before implementing any feature or fixing any bug — spec lookup, clarifications, plan approval. |
Check for an existing spec:
docs/specs/history/prs/YYYY-MM/PR-<number>.mddocs/specs/bugs/ledger.mddocs/specs/baseline/<capability>/If no spec exists, tell the user and create one from the template
at docs/specs/templates/pr-spec.md.
Evaluate the request:
If ANY box is unchecked, ask clarifying questions before proceeding.
Group your questions:
Behavior: What should happen when X? What's the output for Y? Scope: Should this affect Z? Is this limited to one component? Architecture: New agent tool or extend existing? DB migration needed? Testing: What assertions prove this works?
Create BHV-AREA-NNN entries in the spec file:
Check if this change affects system architecture:
If yes, check docs/specs/architecture/ for a relevant diagram.
Update it or create a new one using docs/specs/templates/architecture-diagram.md.
Existing diagrams:
system-context.md — top-level service mapagent-lifecycle.md — agent state machineauth-flows.md — login and signup pathsconn-oauth-flow.md — platform OAuth sequencebilling-credit-flow.md — credit allocation and consumptionws-multitenancy.md — workspace isolation ER diagramads-campaign-creation.md — campaign creation flowmcp-transport.md — MCP server transport architecturePresent:
Wait for explicit approval before writing code.
After coding:
git add docs/specs/...Say: "I want to build exactly what you need. Two quick questions to make sure I get it right." Then ask only the most critical clarification questions.
Part of the Synter free skills collection — open-source agent skills for advertising, PPC, and marketing automation.
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