q-reason

分类: 工具与效率 | 上传者: m0n0x41d | 下载: 0 | 版本: v1.0（最新）
建造之前要三思。当用户要求推理、分析、评估、比较选项、做出架构决策、在方法之间进行选择、思考问题或评估权衡时使用。当用户询问“我们为什么……”、“我们应该……”、“我们的选择是什么”、“这是正确的方法吗”或想要构建/重新构建问题时也可以使用。
更新日志: Source: GitHub https://github.com/m0n0x41d/quint-code
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SKILL.md

---
name: q-reason
description: "Think before building. Use when the user asks to reason about, analyze, evaluate, compare options, make an architecture decision, choose between approaches, think through a problem, or assess trade-offs. Also use when the user asks 'why did we...', 'should we...', 'what are our options', 'is this the right approach', or wants to frame/reframe a problem."
argument-hint: "[problem, decision, architecture question, trade-off, or 'what's stale?']"
---

# Quint Reasoning — Think Before You Build

This skill activates structured engineering reasoning powered by FPF (First Principles Framework) and Quint Code.

**When to use**: any non-trivial engineering question. Architecture choices, library selection, API design, data model changes, infrastructure decisions, process changes. Also: when the user asks to "think about", "reason about", "evaluate", or "compare" anything significant.

**When NOT to use**: obvious bug fixes, formatting, tiny refactors with clear acceptance.

---

## Context-aware entry — read what the user actually wants

**Before doing anything, assess the user's intent from context and arguments.** Do NOT always fall through into the full FPF cycle. There are three distinct paths:

### Path 1: Think and respond (no artifacts)
**Trigger:** "think about X", "what do you think about X", "analyze X", "is this the right approach?", "what are our options?"

The user wants structured thinking, not tool calls. Reason through the problem using FPF principles (weakest link, parity, distinguish object/description/carrier, etc.). Give a well-structured answer. **Do not call quint tools** unless the user explicitly asks to persist something.

### Path 2: Prepare for human-driven cycle (research + wait)
**Trigger:** "/q-reason [topic], prepare for framing", "let's think about X before deciding", "I want to reason through X"

The user wants to drive the cycle themselves. Gather context (read relevant code, search existing decisions, research). Present findings. **Stop and wait** for the user to decide the next step — they will call `/q-frame`, `/q-char`, etc. when ready.

### Path 3: Full autonomous cycle (agent drives)
**Trigger:** "/q-reason [topic] and implement", "figure out the best approach and do it", "fix everything", explicit delegation to agent

The user wants the agent to run the full cycle: frame → explore → decide → implement. Only in this mode does the agent drive without pausing.

**If unclear which path:** default to Path 2 (prepare and wait). Never default to Path 3. Ask: "Want me to think this through and present options, or drive the full cycle and implement?"

---

## What you have

### Quint tools (MCP) — persist reasoning as artifacts

| Tool | What it does | Slash command |
|------|-------------|---------------|
| `quint_note` | Record micro-decisions with rationale validation | `/q-note` |
| `quint_problem` | Frame problems, define comparison dimensions | `/q-frame`, `/q-char` |
| `quint_solution` | Explore variants, compare and identify Pareto front | `/q-explore`, `/q-compare` |
| `quint_decision` | Decide with full rationale, generate implementation brief | `/q-decide`, `/q-apply` |
| `quint_refresh` | Detect stale decisions, manage lifecycle | `/q-refresh` |
| `quint_query` | Search, status dashboard, file-to-decision lookup | `/q-search`, `/q-status` |

### FPF spec search — deep methodology reference

```bash
quint-code fpf search "<query>"        # keyword search
quint-code fpf search "<query>" --full # full section content
quint-code fpf section "<heading>"     # exact section
```

Use for formal FPF definitions, templates, aggregation rules, or conformance checklists.

---

## Feature maturity

Not all FPF concepts are at the same implementation depth. This matters — don't present tracked annotations as computed evaluations.

| Concept | Status | What Quint does |
|---------|--------|-----------------|
| Problem framing | **tracked** | Stores signal, constraints, targets, acceptance. You do the framing, Quint persists it. |
| Characterization | **tracked** | Stores comparison dimensions with scale/unit/polarity. You define them, Quint persists them. |
| WLNK | **tracked** | Required label on variants. After evidence is attached, WLNK summary shows min CL, freshness, supporting/weakening/refuting counts. |
| Parity | **textual** | Stored as rules text. Not enforced or verified. You ensure parity yourself. |
| Pareto front | **tracked** | You identify the non-dominated set, Quint stores and displays it. Not computed automatically. |
| Stepping stones | **tracked** | Boolean flag on variants, shown in summary table. |
| Refresh (valid_until) | **enforced** | All artifacts (decisions, problems, portfolios) with expired valid_until detected by scan. |
| Refresh triggers | **textual** | Stored in decision body. Only valid_until date is actually scanned. Text triggers are reminders, not automated checks. |
| CL (congruence) | **tracked** | Field on evidence items. Shown in WLNK summary (min CL across evidence chain). |
| F-G-R | **textual** | Formality field on evidence items. Stored, shown in WLNK summary when present. |
| NQD | **absent** | Multi-dimensional quality vectors are not implemented. Use comparison dimensions on ProblemCard instead. |
| Impact measurement | **tracked** | `quint_decision(action="measure")` records post-implementation findings against acceptance criteria. |
| Evidence attachment | **tracked** | `quint_decision(action="evidence")` attaches evidence items to any artifact with type/verdict/CL/carrier. |

**Key rule: don't describe textual features as if they compute something.** When you say "WLNK bounds quality," you mean "the user identified what bounds quality" — not that the system calculated it.

---

## How to reason

### 1. Frame the problem BEFORE solving it

The bottleneck is **problem quality**, not solution speed. Don't just fill in fields — drive a diagnostic conversation.

**Framing protocol — ask these questions before recording:**

1. **"What observation doesn't fit?"** — the signal, not the assumed cause. "Webhook retries hit 15%" not "we need a new queue."
2. **"What have you already tried?"** — avoids re-treading known dead ends.
3. **"Who owns this problem?"** — establishes the principal. Not "the team" — a specific person with authority.
4. **"What would solved look like?"** — forces measurable acceptance, not vague "it should be better."
5. **"What constraints are non-negotiable?"** — hard limits that no variant can violate.
6. **"How reversible is this? What's the blast radius?"** — determines mode (tactical vs standard vs deep).
7. **"What should we watch but NOT optimize?"** — Anti-Goodhart indicators that prevent reward hacking.

Only after these are answered, persist the ProblemCard:

- **Signal**: the anomalous observation (from question 1)
- **Constraints**: hard limits (from question 5)
- **Optimization targets**: 1-3 max (from question 4)
- **Observation indicators**: monitor-only metrics (from question 7)
- **Blast radius / reversibility**: from question 6
- **Acceptance**: measurable "done" criteria (from question 4)

**Persist with**: `quint_problem(action="frame", ...)`

**Goldilocks check**: When multiple problems are active, use `quint_problem(action="select")` to see them with blast radius and reversibility signals. Pick the problem in the growth zone — not too trivial (low impact), not too impossible (exceeds current capacity).

> RAG: `quint-code fpf search "problem card PROB"`

### 2. Characterize before comparing

Define the **characteristic space** before evaluating options. Without explicit dimensions, comparisons are arbitrary.

- State the **selection policy BEFORE seeing results**
- Ensure **parity** — same inputs, same scope, same budget across all options (you enforce this, Quint stores your parity rules)
- Keep it **multi-dimensional** — never collapse to a single score unless the fold is explicit

**Persist with**: `quint_problem(action="characterize", ...)`

> RAG: `quint-code fpf search "characterization CHR"`

### 3. Generate genuinely distinct variants

- **≥2 variants** that differ in **kind**, not degree (3+ preferred)
- Each variant gets a **weakest link** label — what you judge bounds its quality
- Mark **stepping stones** — options that open future possibilities even if not optimal now

**Persist with**: `quint_solution(action="explore", ...)`

> RAG: `quint-code fpf search "NQD variant quality"`

### 4. Compare and select

- Identify the **non-dominated set** — variants not strictly worse on all dimensions
- Apply the pre-declared selection policy
- Record what was compared, what won, and why

Note: Quint stores your comparison results and Pareto front. It does not compute them for you — you (or the agent doing analysis) determine which variants are non-dominated.

**Persist with**: `quint_solution(action="compare", ...)`

> RAG: `quint-code fpf search "selection policy SEL Pareto"`

### 5. Decide with full rationale

The decision record should contain:
- **Invariants** — what MUST hold at all times
- **Pre/post-conditions** — checklists for implementation
- **Admissibility** — what is NOT acceptable
- **Rollback plan** — when and how to reverse
- **Refresh triggers** — when to re-evaluate (set valid_until date for automatic detection)
- **Weakest link** — your assessment of what bounds reliability

**Persist with**: `quint_decision(action="decide", ...)`

### 6. Detect staleness and refresh

All artifacts (decisions, problems, portfolios) with expired `valid_until` dates are automatically detected by `/q-status` and `/q-refresh`. This includes stale ProblemCards — problem framings can go stale too when context changes.

Text-based refresh triggers (e.g., "re-evaluate if throughput >80k/s") are stored as reminders but not automatically checked — you or the agent must notice when conditions change.

When reopening a stale decision, the new ProblemCard inherits lineage: prior characterization, failure reason, and evidence references from the previous cycle.

**Persist with**: `quint_refresh(...)`

---

## Depth calibration

| Mode | When | Flow |
|------|------|------|
| **note** | Micro-decisions during coding | `/q-note` — done |
| **tactical** | Reversible, <2 weeks blast radius | `/q-frame` → `/q-explore` → `/q-decide` |
| **standard** | Most architectural decisions | `/q-frame` → `/q-char` → `/q-explore` → `/q-compare` → `/q-decide` |
| **deep** | Irreversible, security, cross-team | All standard + rich parity, runbook, refresh triggers |

**Default is tactical.** Escalate when: hard to reverse, multiple teams affected, or problem framing is unclear.

---

## Key distinctions (always maintain)

- **Object ≠ Description ≠ Carrier** — the system, its spec, and its code are three things
- **Plan ≠ Reality** — a model is not the thing it models
- **Target system ≠ enabling system** — what must work vs who builds/maintains it
- **Design-time ≠ run-time** — Quint stores your reasoning artifacts (design-time). It does not measure, test, or verify your system (run-time). Don't confuse stored claims with validated evidence.

---

## Proactive agent behavior

When you have Quint tools available, use them **automatically** — don't wait for the user to ask.

### Auto-capture mode (always on)

**Record notes automatically when you observe decisions in conversation.** Don't ask "should I record this?" — just call `quint_note`. The validation will reject bad notes (no rationale) and warn on conflicts. Safe to call freely.

Examples of auto-capture triggers:
- Dev says "I'm going with Redis for this" → `quint_note(title="Redis for session cache", rationale="<extract from conversation>", affected_files=[...])`
- Dev says "let's use gRPC instead of REST" → `quint_note(title="gRPC over REST for payments API", rationale="<from conversation>")`
- Dev makes a config choice, picks a library, chooses an approach → capture it

**Do NOT auto-capture**: formatting choices, import ordering, variable naming (too trivial).

### Post-implementation ritual (after /q-decide → implement → commit)

After implementing a decision and committing code:
1. Call `quint_decision(action="baseline", decision_ref="<id>")` — snapshot file hashes
2. **Verify inductively** — at least one of:
   - Run tests (`go test`, `npm test`, `cargo test`) and confirm they pass
   - Read affected files and verify the implementation matches the decision
   - Ask the user to confirm implementation
3. Call `quint_decision(action="measure", decision_ref="<id>", findings="...", verdict="accepted")` — record verified results

**Calling measure from memory without verification is a FPF B.5:4.3 violation.** The tool will warn if no baseline exists. This is not ceremony — it's the difference between design-time claims and run-time evidence.

This closes the lemniscate. Without measure, the decision stays in "Pending Implementation" on `/q-status`.

### Proactive checks (at key moments)

- **At session start**: call `quint_query(action="status")` to surface stale decisions and active problems
- **When /q-status shows Pending Implementation decisions**: check if they were actually implemented. If the decision has a baseline and the code is in place — call `measure` to close the loop.
- **When scan shows "no baseline"**: do NOT assume "not implemented." "No baseline" means the measurement loop wasn't closed, not that the work wasn't done. Check git history for the affected files before reporting status. The scan output distinguishes "files changed since decision" from "files unchanged" — use this signal.
- **When scan shows drift**: do NOT summarize as "expected from development" without reading diffs. For each drifted decision: (1) read `git diff` for each modified file, (2) classify as cosmetic / incidental / material to the decision's invariants, (3) present classification to user. Skipping diff review is a FPF violation — treating description as evidence.
- **If status returns zero artifacts on a project with code**: suggest `/q-onboard`
- **When dev works on files**: call `quint_query(action="related", file="path")` to find linked decisions — mention them if relevant
- **When dev says "let's just do X" without rationale**: ask "why X?" before recording
- **When auto-captured note conflicts with an active decision**: surface the conflict clearly

### Escalation (user-triggered)

These require explicit user action — don't auto-trigger:
- `/q-frame` — full problem framing (diagnostic conversation)
- `/q-explore` — variant generation
- `/q-compare` — parity comparison
- `/q-decide` — formal decision record

### NavStrip interpretation

The `── Quint ──` strip appended to tool responses shows current state and available actions. Key rules:

- **"Available:" = menu for the user, not instructions for the agent.** Do not auto-execute these actions.
- **Mode determines flow shape** — tactical skips `/q-char` and `/q-compare`; standard includes them. The Available line reflects the current mode.
- **Fewer steps ≠ fewer checkpoints.** Tactical mode has fewer FPF steps but the same human consent requirement at each transition.
- **Path 3 override:** Only when the user has explicitly delegated full autonomy ("and implement", "fix everything") may the agent proceed through Available actions without pausing.

---

## RAG search reference

Use `quint-code fpf search` when you need formal FPF definitions, templates, aggregation rules, conformance checklists, or patterns (A.*/B.*/C.*/F.*).

```bash
quint-code fpf search "<query>"
quint-code fpf search "<query>" --full
quint-code fpf section "<heading>"
```

---

## Concept index (search terms)

**Problem design:** problem card, PROB, anomaly, characterization, CHR, problem portfolio, goldilocks, acceptance spec

**Solution design:** SoTA survey, strategy card, method family, solution portfolio, NQD, stepping stones

**Selection:** Pareto front, selection policy, SEL, parity plan, PAR, fair comparison

**Evidence:** evidence record, EVID, F-G-R, assurance level, corroboration, refutation

**Decisions:** decision record, DRR, rollback plan, rationale, constraints

**Invariants:** WLNK, MONO, IDEM, COMM, LOC, weakest link, cutset

**Reasoning:** ADI cycle, abduction, deduction, induction, lifecycle stages
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