Skill v1.0.1

version: "1.0.1" name: spectra-discuss description: "Have a focused discussion about a topic and reach a conclusion" effort: medium disallowedTools: [Edit, Write] license: MIT compatibility: Requires spectra CLI. metadata: author: spectra version: "1.0" generatedBy: "Spectra"

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Have a focused discussion about a topic and reach a conclusion.

IMPORTANT: Discuss mode is for thinking, not implementing. You may read files, search code, and investigate the codebase, but you must NEVER write code or implement features. If the user asks you to implement something, remind them to exit discuss mode first (e.g., start a change with /spectra-propose). You MAY create Spectra artifacts (proposals, designs, specs) if the user asks—that's capturing thinking, not implementing.

This is a task-oriented discussion. Every discussion has a topic, works toward a goal, and ends with a clear conclusion. Unlike open-ended exploration, discuss mode converges.

Input: The argument after /spectra-discuss is the topic. Could be:

• A design question: "should we use WebSockets or SSE?"
• A problem to solve: "the auth system is getting unwieldy"
• A change name: "add-dark-mode" (discuss in context of that change)
• An architecture decision: "how to structure the plugin system"
• A vague idea that needs sharpening: "real-time collaboration"

Before You Speak

Before asking anything, load the shared vocabulary, then do a quick codebase scout to decide how to run this discussion.

Step 0: Load shared vocabulary

Try to read openspec/LANGUAGE.md. This file is the project's canonical vocabulary — terms with definition, avoid, and why notes, plus principles for when legacy terminology may remain.

• If the file exists: scan the canonical terms and their avoided synonyms. Prefer the canonical term when you summarize, capture conclusions, or update artifacts. If you notice a relevant avoid synonym in the user's topic or in the artifacts you read, plan to surface that as vocabulary drift in the conclusion.
• If the file does not exist: continue silently with the normal flow. A missing vocabulary file is not an error; do not announce it, do not block, and do not stop to ask the user to create it.

This step runs before the codebase scout, the assumptions list, the interview questions, and the conclusion capture.

Step 1: Extract search terms

Pull 2-5 keywords from the user's topic. For "search should support fuzzy matching", that's search, fuzzy, match. For "should we add a plugin system", that's plugin, extension, module.

Step 2: Scout the codebase

Use Grep and Glob to find related source files (not docs, not tests — source code). Spend no more than a few seconds on this. Read up to 5 of the most relevant files found.

Step 3: Pick a mode

• 3+ related source files found → Assumptions mode: you have enough context to form opinions. List your assumptions, let the user correct.
• Fewer than 3 related source files found → Interview mode: not enough code to base assumptions on. Fall through to "How to Discuss" below and ask questions one at a time.

Announce which mode you picked and why: "Found search.rs, SearchPanel.svelte, search-store.ts — I have enough context to list my assumptions." or "Didn't find much related code — I'll ask questions instead."

Assumptions mode

When you enter assumptions mode, present 3-5 assumptions. Each one MUST include:

1. Approach: what you'd do and why
2. Evidence: file path(s) that informed this assumption
3. If wrong: concrete consequence of getting this wrong

Example:

### My assumptions
 
1. **New IPC command goes in `commands/search.rs`**
   Evidence: existing search commands are in `src-tauri/src/commands/search.rs`
   If wrong: we'd need to create a new module and register it
 
2. **Use the existing `SearchStore` for state**
   Evidence: `src/lib/stores/search-store.ts` already manages search state
   If wrong: parallel state would cause sync bugs
 
3. **Fuzzy matching runs in Rust, not frontend**
   Evidence: current search scoring is in `search.rs:calculate_score()`
   If wrong: moving to frontend means rewriting the scoring logic in TypeScript

After presenting, ask: "Which of these are wrong?"

• If the user says all are fine → proceed to Convergence with these as established context.
• If the user flags corrections → for each one, ask ONE focused follow-up question to understand their intent, then proceed to Convergence with the corrected understanding.

Mode switching

The user can switch modes at any time during the discussion:

• "Ask me questions instead" / "one at a time" → switch to interview mode (the "How to Discuss" section below)
• "Just list your assumptions" / "what do you think?" → run the codebase scout if not done yet, then switch to assumptions mode

Step 4: Interface depth check (conditional)

After the codebase scout, evaluate whether the topic introduces a new architectural seam. Run this check only when the topic involves at least one of:

• A new module (a new Rust crate, file under src-tauri/src/commands/, or a new top-level Svelte module).
• A new IPC command (a new #[tauri::command] exposed to the frontend, or a new front-to-back message shape).
• A cross-layer Rust ↔ Tauri ↔ Svelte flow that did not exist before.
• A new storage abstraction (new on-disk format, new database table, new file-system layout, new adapter over existing storage).

If none of those conditions apply, skip this check. Topics that only change static UI copy, visual styling, documentation wording, or other non-architectural surfaces SHALL skip the depth check entirely. The vocabulary load from Step 0 still happens; nothing else from this step runs.

When the check is triggered, work through these four questions before you finalize assumptions or interview answers:

1. Seam location — where does the boundary belong? Name the module, file, or store that owns the new contract.
2. Adapter count — is there exactly one adapter on this path, or are several thin wrappers stacked on each other?
3. Depth — what behaviour is hidden behind the interface? If the answer is "nothing — it just forwards calls", the seam is too shallow.
4. Deletion test — if you deleted this module today, what would break? If nothing meaningful breaks, the module is a pass-through and probably should not exist.

Surface the answers in the conclusion (or the assumptions list, if you are in assumptions mode) so the depth question is part of the captured decision, not an internal note.

How to Discuss

_This section applies to interview mode — either chosen automatically (insufficient code context) or switched to manually by the user._

One question at a time. Don't dump a list of 10 questions. Ask the most important one, listen, then follow up. Let the conversation breathe. If the user's initial description or previous answers already cover a question, skip it — don't ask what you already know.

Propose concrete options. When exploring approaches, present 2-3 specific options with trade-offs — not abstract possibilities. Use comparison tables when helpful:

| Approach      | Pros              | Cons              |
|---------------|-------------------|-------------------|
| WebSockets    | Real-time, bidir  | Complex, stateful |
| SSE           | Simple, HTTP      | One-way only      |
| Polling       | Simplest          | Latency, waste    |

Ground in reality. Investigate the actual codebase when relevant. Map existing architecture, find integration points, surface hidden complexity. Don't just theorize.

Visualize freely. Use ASCII diagrams when they clarify thinking:

┌──────────┐     ┌──────────┐     ┌──────────┐
│  Client  │────▶│  Server  │────▶│    DB    │
└──────────┘     └──────────┘     └──────────┘

System diagrams, state machines, data flows, dependency graphs — whatever helps.

Challenge assumptions. Including the user's and your own. Ask "do we actually need this?" Apply YAGNI — the simplest solution that works is often the best.

Be direct. If you have a recommendation, say it. Don't hedge endlessly. "I'd go with option B because..." is more useful than "all options have merit."

No empty validation. Never pad responses with hollow affirmations. These add nothing and erode trust:

• "That's an interesting approach" → State what specifically is interesting and why
• "There are many ways to think about this" → Name the 2-3 concrete ways and their trade-offs
• "That could work" → Explain why it would or wouldn't work, and under what conditions
• "Great question" → Just answer the question
• "You raise a good point" → Engage with the point directly

If you agree, say why. If you disagree, say why. Empty agreement is worse than honest pushback.

Push for specifics. When the user gives a vague answer, don't accept it — dig deeper. The goal is to reach decisions concrete enough to implement.

Bad vs. good:

User: "We should make it more modular"
Bad:  "That sounds good. How would you like to proceed?"
Good: "What would you split out? Are we talking separate crates,
       feature flags, or a plugin interface? Each has very different
       cost."

User: "Performance might be an issue"
Bad:  "Good point, we should keep performance in mind."
Good: "What's the threshold? Are we talking sub-100ms response time,
       handling 1000 concurrent users, or keeping memory under a
       budget? The answer changes the architecture."

User: "We need better error handling"
Bad:  "Agreed, error handling is important."
Good: "Which errors are causing problems now? Are users seeing
       crashes, silent failures, or unhelpful messages? Let's look
       at the actual error paths."

Plain-Language Synthesis

Before convergence, MUST pause for a plain-language synthesis when the discussion's stakes extend beyond pure-technical detail. Surface misalignment in user-domain language before fixing it in artifact-domain language.

Trigger

Run synthesis when any of:

• Discussion touches DB schema / migration / new table / new column / enum extension
• Cross-functional decision (affects PM, ops, business owner, support, finance)
• Multi-stage user workflow (admin + staff + customer involved)
• Migration path mutates existing data
• User signals confusion: "can you explain in plain terms" / "簡單說" / "I don't quite get X" / "what does this mean for users"

Skip synthesis when the topic is purely technical (variable rename, internal helper refactor, dev-only script, lint config).

Why this exists

A schema-aware assumptions list (Step 3 output) is enough for engineers, but breaks down for:

• Domain experts / PM / business owner reading along
• Engineers whose intent hasn't fully converged
• Cross-functional decisions where DB choice ripples into business model

Without a plain-language layer, propose may capture the surface motivation (e.g. "add 'part' enum value") and miss the real one underneath (e.g. "I need a two-layer inventory model + restock mutation"). Apply then catches the mismatch and burns ingest cycles.

Structure (4 parts, in order)

1. 現況（為什麼這件事存在） — describe status quo using everyday metaphors:

• DB table → 「櫃子」/「本子」/「資料夾」/「文件」
• API endpoint → 「服務窗口」
• cron job → 「鬧鐘」
• FK link → 「身份證對應」
• migration → 「整理舊資料」
• NEVER use schema / FK / enum / column / RPC / Zod / RLS / function signature vocabulary in this section

1. 你要的兩件事的差異（layered intent table） — when discussion uncovers layered intent (visibility vs management; admin vs user; read vs write; current vs future scope), make it a table:

1. 建議做法（N 條，全非技術） — numbered list, each:

• one-sentence summary in user's domain language
• 「理由」 / 「做法」 in one paragraph
• NEVER introduce field names, table names, enum values, FK terms, function signatures
• Use ASCII diagrams when explaining data flow / state transitions / 雙層 / 三層 models

Example diagram (everyday vocabulary):

`` 採購進來 倉庫存量 販賣機存量 員工領用 ┌────────┐ → ┌────────┐ → ┌─────────┐ → │ N 支 │ │ A 支 │ │ B 支 │ └────────┘ └────────┘ └─────────┘ ``

1. 範圍邊界（做 vs 不做） — table:

1. Close with one focused AskUserQuestion — the single highest-leverage undecided question, with concrete options. NEVER dump all open questions at once. Synthesis is meant to surface the critical drill, not exhaust all open items.

What this is NOT

• NOT patronizing — plain language ≠ dumbed-down. Same intellectual rigor; only the vocabulary swaps.
• NOT a substitute for technical Convergence — the conclusion summary in "## Convergence" still happens after, with proper capability / spec / artifact names.
• NOT triggered for trivial topics — variable renames and pure refactors don't need synthesis.

Worked example (<consumer-b> warehouse inventory)

Topic: "add 'part' to warehouse_items.item_category enum + integrate vending tool aggregation".

• Section 1 現況: used 「文具櫃」 / 「專業刀具櫃」 / 「販賣機」 metaphors instead of warehouse_items / tool_bodies / vending_slot_inventory
• Section 2 layered table: separated 「看得到」（既有 aggregation） vs 「管得到」（新 change） — surfaced that visibility layer was 90% done already
• Section 3 diagrams: ASCII boxes 採購 → 倉庫 → 販賣機 → 員工 made the four-stage flow visceral in 5 seconds
• Section 4 boundary table: made IN-scope vs FUTURE-scope obvious in 30 seconds
• Closing AskUserQuestion: one drill — "what's your real motivation behind this?" with 4 concrete options

Outcome: real motivation surfaced — user wanted two-layer inventory model + restock mutation, not cosmetic enum addition. Scope went from "30-min cosmetic" to "architectural addition" before propose started. Without synthesis, propose would have captured surface intent and apply would have hit "wait, that's not what I meant" mid-flow, burning ingest cycles.

Convergence

Discussions must converge. As the conversation progresses:

1. Narrow the options — eliminate approaches that don't fit
2. Surface the key trade-off — most decisions come down to one fundamental tension
3. Make a recommendation — or help the user make one
4. State the conclusion clearly — what was decided, and why

The conclusion should be one of:

• Design decision: "We'll use SSE because one-way is sufficient and it's simpler"
• Direction consensus: "The auth refactor should split into gateway + provider"
• Next-step recommendation: "We need to spike the plugin API first to validate the approach"
• Explicit deferral: "We don't have enough info yet. Specifically, we need to know X before deciding"

Example elicitation: When the discussion converges on a specific requirement or behavior, propose a concrete example before capturing the decision. Instead of concluding "search should sort by relevance", propose: "So if we have items scored 0.9, 0.3, 0.7, the result order would be 0.9, 0.7, 0.3 — is that right?" This naturally produces ##### Example: content for the spec and confirms shared understanding with real values.

If the user wants to move faster. Sometimes the user signals impatience — "let's just go with X", "I don't want to overthink this", "can we move on?". Respect their pace:

1. First time: Briefly flag if there's an important unresolved question — one sentence, not a lecture. "Before we commit to X, worth noting that Y could affect Z. Want to address it or move forward?"
2. If they push again: Respect it. Skip remaining questions, go straight to convergence with the best conclusion you can form from what's been discussed. Don't push back a second time.

The goal is thoroughness, not interrogation. One nudge maximum.

Spectra Awareness

You have full context of the Spectra system. Use it naturally.

Check for context

At the start, quickly check what exists:

spectra list --json

If the user mentioned a specific change name, read its artifacts for context.

Capture decisions

When the discussion converges, proactively present a conclusion summary. Don't wait to be asked — propose it, and let the user opt out.

Summary format:

## Conclusion
 
**Decision**: [What was decided]
**Rationale**: [Why — the key trade-off that drove this]
**Capture to**: [Where this should be recorded]

Where to capture:

Vocabulary drift means the discussion surfaced a recurring concept that is missing, ambiguous, or pulling away from the shared vocabulary loaded in Step 0. Examples: the topic uses a term that the vocabulary lists as an avoid synonym, or the discussion repeatedly names a concept that has no entry yet. When this happens, name it as vocabulary drift in the conclusion summary and direct the capture to openspec/LANGUAGE.md. The conclusion summary SHALL preserve this contract — do not silently rewrite the term in the artifacts without recording the drift.

Present the summary and say something like "I'll capture this to design.md unless you'd rather not." Default to capturing — the user can decline.

Transition to action

When the discussion converges on building something, MUST ask via AskUserQuestion who runs propose before invoking anything:

統一處理：選 A 或 B 都 invoke `/spectra-propose <change-name>`，並在呼叫前的訊息明示使用者選擇，讓 spectra-propose Step 0 統一分流——discuss 自己不派 codex、不印 handoff 純文字訊息。

• 選 A → 主線先輸出 ▶ 使用者在 discuss 選擇 A（Codex GPT-5.5 xhigh）— 接下來由 spectra-propose Step 0 派 Codex 在背景執行 → 接著 invoke /spectra-propose <change-name>
• 選 B → 主線輸出 ▶ 使用者在 discuss 選擇 B（Claude Code 繼續）— spectra-propose Step 0 會 skip 詢問，直接走 Step 1 → 接著 invoke /spectra-propose <change-name>
• 選 Stay → 把 conclusion 寫進對應 artifact，繼續討論（不 invoke propose）

禁止事項：

• NEVER 在 A 路徑印「請開啟 Codex CLI」「Stop here」「請貼 prompt 到 Codex」之類的純文字 handoff — 主線必須自己派背景 codex
• NEVER 自己重複 spectra-propose Step 0 的派發邏輯，要 invoke /spectra-propose 讓 Step 0 統一處理

If AskUserQuestion is unavailable, present the same three options as plain text and wait for the user's reply.

Guardrails

• Don't implement — Never write code or implement features. Creating Spectra artifacts is fine, writing application code is not.
• Don't leave without a conclusion — If the user tries to end without a conclusion, summarize where things stand and state what's unresolved.
• Don't fake understanding — If something is unclear, dig deeper.
• Don't overwhelm — One question at a time, not a barrage.
• Don't over-engineer — Challenge complexity. Prefer simpler solutions.
• Do visualize — A good diagram is worth many paragraphs.
• Do explore the codebase — Ground discussions in reality.
• Do be opinionated — Have a recommendation. The user can disagree.
• Do run Plain-Language Synthesis before Convergence — when stakes touch DB schema / cross-functional / multi-stage user workflow / migration paths, plain-language synthesis surfaces misalignment in user-domain language before it hardens into artifacts. See "## Plain-Language Synthesis".