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Add conversational blueprint agent flow#23

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Abby263 merged 1 commit into
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codex/conversational-blueprint-agent
May 8, 2026
Merged

Add conversational blueprint agent flow#23
Abby263 merged 1 commit into
mainfrom
codex/conversational-blueprint-agent

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@Abby263

@Abby263 Abby263 commented May 8, 2026

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Summary

  • add a schema-aware Blueprint Agent panel available from project creation, overview, intake, and artifacts
  • create agent proposals with assumptions, follow-up questions, touched domains, confidence, and review-before-apply behavior
  • add repository agent rules, Cursor rules, Copilot instructions, spec templates, and runtime docs
  • update README and SETUP for the local agent/runtime contract

Verification

  • npm run typecheck
  • npm run build
  • Codex in-app browser smoke check: created an agent-assisted project from a rough Azure RAG idea, auto-generated a proposal, applied it as draft, checked mobile viewport and console errors

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Project Deployment Actions Updated (UTC)
product-dev-blueprint Ready Ready Preview, Comment May 8, 2026 1:29am

@Abby263 Abby263 merged commit fb32320 into main May 8, 2026
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@chatgpt-codex-connector chatgpt-codex-connector Bot left a comment

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💡 Codex Review

Here are some automated review suggestions for this pull request.

Reviewed commit: e9b196c757

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function detectSignals(input: string): Signals {
const text = input.toLowerCase();
const has = (...words: string[]) => words.some((w) => text.includes(w));
const isAI = has("ai", "agent", "rag", "llm", "chatbot", "copilot", "model", "prompt");

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P1 Badge Match AI intent on token boundaries

The AI detector uses text.includes("ai"), which matches unrelated words like “paid” or “email” and flips isAI to true for non-AI ideas. That cascades into AI-specific defaults (model provider, RAG assumptions, compliance/security posture, etc.), so users can get materially incorrect proposals from ordinary product descriptions. Use word-boundary/token-based matching for short keywords like ai.

Useful? React with 👍 / 👎.

Comment on lines +513 to +515
if (isPlainObject(current) && isPlainObject(value)) {
expanded[key] = deepMerge(current, value);
} else {

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P1 Badge Apply proposals against latest project state

This expands each proposal into a full top-level object using the project snapshot captured at generation time; if the user edits fields in that same domain before clicking apply, updateProject later replaces the domain with stale values and silently loses those newer edits. This is reproducible whenever proposal generation and manual edits happen in the same session before apply. Keep proposal patches sparse and merge against the latest store state at apply time.

Useful? React with 👍 / 👎.

["market.", "market"],
["experience.", "experience"],
["platform.", "platform"],
["functional.", "functional"],

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P2 Badge Map feature updates to the features step

Because domainFromPath matches functional. first and there is no explicit mapping for functional.features, feature proposals are classified as functional rather than features. In focused modes on the Features step (focusStep === "features"), those updates get filtered out, and touched-domain progress will also miss the Features domain. Add a specific functional.features mapping before the generic functional. rule.

Useful? React with 👍 / 👎.

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