preflight
OfficialClick on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@preflightfix the auth bug"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
✈️ preflight
Stop burning tokens on vague prompts.
A 24-tool MCP server for Claude Code that catches ambiguous instructions before they cost you 2-3x in wrong→fix cycles — plus semantic search across your entire session history, cross-service contract awareness, and 12-category scorecards.
Quick Start · How It Works · Tool Reference · Configuration · Scoring
What's New in v3.2.0
Unified
preflight_checkentry point — one tool that triages every prompt and chains the right checks automaticallySmart triage classification — routes prompts through a decision tree (trivial → ambiguous → multi-step → cross-service)
Correction pattern learning — remembers past mistakes and warns you before repeating them
Cross-service contracts — extracts types, interfaces, routes, and schemas across related projects
.preflight/config directory — team-shareable YAML config for triage rules and thresholdsTrend & comparative scorecards — weekly/monthly trend lines, cross-project comparisons, radar charts, PDF export
Cost estimator — estimates token spend and waste from corrections
Related MCP server: MCP DevTools Server
The Problem
We built this after analyzing 9 months of real Claude Code usage — 512 sessions, 32,000+ events, 3,200+ prompts, 1,642 commits, and 258 sub-agent spawns across a production Next.js/Prisma/Supabase app. The findings were brutal:
41% of prompts were under 50 characters — things like
fix the tests,commit this,remove themEach vague prompt triggers a wrong→fix cycle costing 2-3x tokens
~33K characters/day duplicated from repeated context pastes
124 corrections logged — places where Claude went the wrong direction and had to be steered back
94 context compactions from unbounded session scope blowing past the context window
Estimated 30-40% of tokens wasted on avoidable back-and-forth
The pattern is always the same: vague prompt → Claude guesses → wrong output → you correct → repeat. That's your money evaporating.
The Solution
24 tools in 5 categories that run as an MCP server inside Claude Code:
Category | Tools | What it does |
✈️ Preflight Core | 1 | Unified entry point — triages every prompt, chains the right checks automatically |
🎯 Prompt Discipline | 12 | Catches vague prompts, enforces structure, prevents waste |
🔍 Timeline Intelligence | 4 | LanceDB vector search across months of session history |
📊 Analysis & Reporting | 4 | Scorecards, cost estimation, session stats, pattern detection |
✅ Verification & Hygiene | 3 | Type-check, test, audit, and contract search |
Before / After
❌ "fix the auth bug"
→ Claude guesses which auth bug, edits wrong file
→ You correct it, 3 more rounds
→ 12,000 tokens burned
✅ preflight intercepts → clarify_intent fires
→ "Which auth bug? I see 3 open issues:
1. JWT expiry not refreshing (src/auth/jwt.ts)
2. OAuth callback 404 (src/auth/oauth.ts)
3. Session cookie SameSite (src/middleware/session.ts)
Pick one and I'll scope the fix."
→ 4,000 tokens, done right the first timeQuick Start
Option A: npx (fastest — no install)
claude mcp add preflight -- npx -y preflight-dev-serveWith environment variables:
claude mcp add preflight \
-e CLAUDE_PROJECT_DIR=/path/to/your/project \
-- npx -y preflight-dev-serveOption B: Clone & configure manually
git clone https://github.com/TerminalGravity/preflight.git
cd preflight && npm installAdd to your project's .mcp.json:
{
"mcpServers": {
"preflight": {
"command": "npx",
"args": ["tsx", "/path/to/preflight/src/index.ts"],
"env": {
"CLAUDE_PROJECT_DIR": "/path/to/your/project"
}
}
}
}Restart Claude Code. The tools activate automatically.
Option C: npm (global)
npm install -g preflight-dev
claude mcp add preflight -- preflight-dev-serveNote:
preflight-devruns the interactive setup wizard.preflight-dev-servestarts the MCP server — that's what you want in your Claude Code config.
How It Works
The Triage Decision Tree
Every prompt flows through a classification engine before any work begins. This is the actual decision tree from src/lib/triage.ts:
flowchart TD
A[Prompt Arrives] --> B{Skip keyword?}
B -->|Yes| T1[✅ TRIVIAL]
B -->|No| C{Multi-step indicators?}
C -->|Yes| MS[🔶 MULTI-STEP]
C -->|No| D{Cross-service keywords?}
D -->|Yes| CS[🔗 CROSS-SERVICE]
D -->|No| E{always_check keyword?}
E -->|Yes| AM1[⚠️ AMBIGUOUS]
E -->|No| F{"< 20 chars + common cmd?"}
F -->|Yes| T2[✅ TRIVIAL]
F -->|No| G{"< 50 chars, no file refs?"}
G -->|Yes| AM2[⚠️ AMBIGUOUS]
G -->|No| H{Vague pronouns or verbs?}
H -->|Yes| AM3[⚠️ AMBIGUOUS]
H -->|No| CL[✅ CLEAR]
style T1 fill:#2d6a4f,color:#fff
style T2 fill:#2d6a4f,color:#fff
style CL fill:#2d6a4f,color:#fff
style AM1 fill:#e9c46a,color:#000
style AM2 fill:#e9c46a,color:#000
style AM3 fill:#e9c46a,color:#000
style CS fill:#457b9d,color:#fff
style MS fill:#e76f51,color:#fffEach level triggers different tool chains:
Level | What fires | Example prompt |
Trivial | Nothing — pass through |
|
Clear | File verification only |
|
Ambiguous | Clarify intent + git state + workspace priorities |
|
Cross-service | Clarify + search related projects + contracts |
|
Multi-step | Clarify + scope + sequence + checkpoints |
|
Additionally, correction pattern matching can boost any triage level. If your prompt matches 2+ keywords from a previously logged correction, it's bumped to at least ambiguous — even if it would otherwise pass through.
Data Flow
flowchart LR
A[User Prompt] --> B[Triage Engine]
B --> C[Tool Chain]
C --> D[Response]
B -.-> E[".preflight/\nconfig.yml\ntriage.yml"]
B -.-> F["Patterns\nLog"]
C -.-> G["LanceDB\n(per-project)"]
C -.-> H["Contracts\n(per-project)"]
G -.-> I["~/.claude/projects/\n(session JSONL)"]
style A fill:#264653,color:#fff
style B fill:#2a9d8f,color:#fff
style C fill:#e9c46a,color:#000
style D fill:#e76f51,color:#fffSession Data Structure
Claude Code stores session data as JSONL files:
~/.claude/projects/<encoded-path>/
├── <session-uuid>.jsonl # Main session
├── <session-uuid>/
│ └── subagents/
│ └── <sub-uuid>.jsonl # Sub-agent sessionsEach JSONL line is an event. The session parser extracts 8 event types:
Event Type | Source | What it captures |
|
| What the dev typed |
|
| Claude's text response |
|
| Tool invocations (Read, Write, Bash, etc.) |
| Task/dispatch_agent tool_use | When Claude delegates to a sub-agent |
|
| Detected via negation patterns (no, wrong, actually, undo…) |
|
| Context was compressed (session hit token limit) |
|
| Failed operations |
| git log integration | Commits made during session |
LanceDB Schema
Events are stored in per-project LanceDB databases with vector embeddings for semantic search:
~/.preflight/projects/<sha256-12-char>/
├── timeline.lance/ # LanceDB vector database
├── contracts.json # Extracted API contracts
└── meta.json # Project metadata
Table: events
├── id: string (UUID)
├── content: string (event text)
├── content_preview: string (first 200 chars)
├── vector: float32[384] (Xenova/all-MiniLM-L6-v2) or float32[1536] (OpenAI)
├── type: string (event type from above)
├── timestamp: string (ISO 8601)
├── session_id: string (session UUID)
├── project: string (decoded project path)
├── project_name: string (short name)
├── branch: string (git branch at time of event)
├── source_file: string (path to JSONL file)
├── source_line: number (line number in JSONL)
└── metadata: string (JSON — model, tool name, etc.)The project registry at ~/.preflight/projects/index.json maps absolute paths to their SHA-256 hashes.
Contract Extraction
The contract extractor scans your project for API surfaces:
Pattern | What it finds |
| TypeScript type definitions |
| Next.js API routes |
| Express route handlers |
| Prisma models and enums |
OpenAPI/Swagger specs | Routes and schema components |
| Manual contract definitions |
Contracts are stored per-project and searched across related projects during cross-service triage.
Onboarding a Project
Run onboard_project to index a project's history. Here's what happens:
Discovers sessions — finds JSONL files in
~/.claude/projects/<encoded-path>/, including subagent sessionsParses events — extracts the 8 event types from each session file (streams files >10MB)
Extracts contracts — scans source for types, interfaces, enums, routes, Prisma models, OpenAPI schemas
Loads manual contracts — merges any
.preflight/contracts/*.ymldefinitions (manual wins on name conflicts)Generates embeddings — local Xenova/all-MiniLM-L6-v2 by default (~90MB model download on first run, ~50 events/sec) or OpenAI if
OPENAI_API_KEYis set (~200 events/sec)Stores in LanceDB — per-project database at
~/.preflight/projects/<sha256-12>/timeline.lance/Updates registry — records the project in
~/.preflight/projects/index.json
No data leaves your machine unless you opt into OpenAI embeddings.
After onboarding, you get:
🔎 Semantic search — "How did I set up auth middleware last month?" actually works
📊 Timeline view — see what happened across sessions chronologically
🔄 Live scanning — index new sessions as they happen
🔗 Cross-service search — query across related projects
Tool Reference
✈️ Preflight Core
Tool | What it does |
| The main entry point. Triages your prompt (trivial → multi-step), chains the right checks automatically, matches against known correction patterns. Accepts |
🎯 Prompt Discipline
Tool | What it does |
| Creates structured execution plans before coding starts |
| Gathers project context (git state, workspace docs, ambiguity signals) to disambiguate vague prompts |
| Enriches sub-agent tasks with file paths, patterns, and cross-service context |
| Resolves "fix it" / "do the others" to actual file targets |
| Detects waste patterns, grades your session A–F |
| Orders tasks by dependency, locality, and risk |
| Save game before compaction — commits + resumption notes |
| Monitors uncommitted files, time since commit, turn count |
| Tracks corrections and identifies recurring error patterns |
| Checks prompts against learned correction patterns — warns about known pitfalls |
| Generates handoff briefs for new sessions |
| Summarizes diffs since last checkpoint |
🔍 Timeline Intelligence
Tool | What it does |
| Indexes a project's session history + contracts into per-project LanceDB |
| Semantic search with scope: current project, related, or all indexed projects |
| Chronological view of events across sessions |
| Live scanning of active session data |
📊 Analysis & Reporting
Tool | What it does |
| 12-category report card — session, trend (week/month), or cross-project comparative. Radar chart SVG, PDF or markdown. |
| Token usage, dollar cost, waste from corrections, preflight savings |
| Lightweight session analysis — no embeddings needed |
| Gamified A–F grading on specificity, scope, actionability, done-condition |
✅ Verification & Hygiene
Tool | What it does |
| Runs type check + tests + build before declaring done |
| Finds stale/missing workspace docs vs git activity |
| Search API contracts, types, and schemas across current and related projects |
Usage Examples
Real prompts you'd type in Claude Code once preflight is installed. The tools fire automatically via preflight_check, or you can call them directly.
Catch a vague prompt before it wastes tokens
> fix the auth bug
preflight_check intercepts → clarify_intent fires:
"I found 3 auth-related recent changes:
1. JWT refresh logic in src/auth/jwt.ts (modified 2h ago)
2. OAuth callback route in src/routes/oauth.ts (3 open TODOs)
3. Session middleware in src/middleware/auth.ts (failing test)
Which one? Or describe the symptoms."Scope a multi-step task before starting
> refactor the database layer to use Drizzle instead of Prisma
preflight_check triages as MULTI-STEP → scope_work + sequence_tasks fire:
Phase 1: Install drizzle-orm, create schema (src/db/schema.ts)
Phase 2: Migrate queries in src/services/ (12 files)
Phase 3: Update tests (8 files reference prisma mocks)
Phase 4: Remove prisma dependencies, delete prisma/ dir
Estimated: 4 checkpoints, ~45 minSearch your session history
> use search_history to find how I set up the rate limiter
Searches LanceDB across your indexed sessions:
Found 3 relevant events (similarity > 0.82):
- Session abc123 (Jan 15): Added express-rate-limit to src/middleware/
- Session def456 (Jan 16): Configured per-route limits in src/routes/api.ts
- Session ghi789 (Feb 2): Fixed rate limit bypass via X-Forwarded-ForGrade your prompting habits
> use prompt_score on "update the thing"
Grade: D
- Specificity: 1/5 — no file paths, no identifiers
- Scope: 1/5 — "the thing" is completely ambiguous
- Actionability: 2/5 — "update" is vague (refactor? fix? add feature?)
- Done-condition: 0/5 — no way to know when it's done
Suggestion: "Update the price formatter in src/utils/currency.ts
to handle JPY (zero-decimal currency)"Check session health mid-work
> use check_session_health
⚠️ 47 uncommitted files (last commit: 38 min ago)
⚠️ 23 turns since last checkpoint
💡 Consider running `checkpoint` before context compaction hitsGet a cost estimate
> use estimate_cost
This session: ~$2.40 (148K tokens)
Waste from corrections: ~$0.85 (3 wrong→fix cycles)
Preflight savings: ~$1.20 (4 vague prompts caught early)
Net: saving roughly 35% vs unchecked promptingThe 12-Category Scorecard
generate_scorecard evaluates your prompt discipline across 12 categories. Each one measures something specific about how you interact with Claude Code:
# | Category | What it measures | How it scores |
1 | Plans | Do you start sessions with a plan? | % of sessions where the first 3 prompts include file references and >100 chars |
2 | Clarification | Are your prompts specific? | % of user prompts containing file paths or specific identifiers |
3 | Delegation | Are sub-agent tasks well-defined? | % of sub-agent spawns with >200 char descriptions |
4 | Follow-up Specificity | Do follow-ups reference files? | % of follow-up prompts (after assistant response) with file refs or ≥50 chars |
5 | Token Efficiency | How many tool calls per file? | Ratio of tool_calls to unique files touched (ideal: 5-10 calls/file) |
6 | Sequencing | Do you stay focused or context-switch? | Topic switch rate — how often prompts jump between different directory areas |
7 | Compaction Management | Do you commit before compaction? | % of compaction events preceded by a commit within 10 messages |
8 | Session Lifecycle | Do you commit regularly? | % of sessions with healthy commit frequency (every 15-30 min) |
9 | Error Recovery | How quickly do you recover from mistakes? | Correction rate (% of messages) + recovery speed (within 2 messages) |
10 | Workspace Hygiene | Do you maintain workspace docs? | Baseline 75 + bonus for sessions referencing |
11 | Cross-Session Continuity | Do new sessions read context? | % of sessions where first 3 tool calls read project context docs |
12 | Verification | Do you test at the end? | % of sessions that ran tests/build/lint in the final 10% of events |
Report Types
Type | What you get |
Scorecard | Single-period snapshot with 12 categories, radar chart, best/worst highlights |
Trend | Weekly or monthly trend line, per-category movement, top 3 improvement areas, best/worst prompts |
Comparative | Side-by-side across multiple projects, cross-project pattern detection |
All three support PDF export (requires Playwright) and historical baselines that track your rolling averages over time.
Cross-Service Awareness
Preflight understands that microservices share contracts. When your prompt mentions a keyword from a related project, triage escalates to cross-service and searches those projects for relevant context.
Setup
Option 1: .preflight/config.yml (recommended — committed to repo)
# my-api/.preflight/config.yml
related_projects:
- path: /Users/jack/Developer/auth-service
alias: auth-service
- path: /Users/jack/Developer/notifications
alias: notifications
- path: /Users/jack/Developer/shared-types
alias: shared-typesOption 2: Environment variable (per-user)
PREFLIGHT_RELATED=/path/to/auth-service,/path/to/notificationsHow it works
You type:
"add rewards tier validation"Triage detects
rewardsmatchesalways_checkkeyword →ambiguousCross-service keywords (
auth,notification) don't match, but if you had typed"add rewards with auth check"→cross-servicePreflight searches related projects' LanceDB indexes and contract registries
Returns relevant types, interfaces, and routes from those projects
You get context like: "auth-service has
interface AuthToken { userId, tier, permissions }andPOST /api/validate-tier"
This prevents the common failure mode: changing a shared type in one service and forgetting the consumers.
Configuration Reference
.preflight/config.yml
Drop this in your project root. Every field is optional — defaults are sensible.
# Profile controls overall verbosity
# "minimal" — only flag ambiguous+, skip clarification detail
# "standard" — default behavior
# "full" — maximum detail on every non-trivial prompt
profile: standard # type: "minimal" | "standard" | "full"
# Related projects for cross-service awareness
related_projects: # type: RelatedProject[]
- path: /absolute/path/to/service # path: string (absolute)
alias: service-name # alias: string (used in output + triage matching)
# Behavioral thresholds
thresholds:
session_stale_minutes: 30 # type: number — warn if no activity for this long
max_tool_calls_before_checkpoint: 100 # type: number — suggest checkpoint after N tool calls
correction_pattern_threshold: 3 # type: number — min corrections to form a pattern
# Embedding configuration
embeddings:
provider: local # type: "local" | "openai"
openai_api_key: sk-... # type: string — only needed if provider is "openai".preflight/triage.yml
Controls the triage classification engine.
# Keywords that control routing
rules:
# Prompts containing these → always at least AMBIGUOUS
always_check: # type: string[] — default: [rewards, permissions, migration, schema]
- rewards
- permissions
- migration
- schema
# Prompts containing these → TRIVIAL (pass through)
skip: # type: string[] — default: [commit, format, lint]
- commit
- format
- lint
# Prompts containing these → CROSS-SERVICE
cross_service_keywords: # type: string[] — default: [auth, notification, event, webhook]
- auth
- notification
- event
- webhook
# How aggressively to classify
# "relaxed" — more prompts pass as clear
# "standard" — balanced
# "strict" — more prompts flagged as ambiguous
strictness: standard # type: "relaxed" | "standard" | "strict".preflight/contracts/*.yml
Manual contract definitions that supplement auto-extraction:
# .preflight/contracts/api.yml
- name: RewardsTier
kind: interface
description: Reward tier levels and their perks
fields:
- name: tier
type: string
required: true
- name: multiplier
type: number
required: true
- name: perks
type: string[]Environment Variables
Variable | Description | Default |
| Project root to monitor | Required |
| OpenAI key for embeddings | Uses local Xenova |
| Comma-separated related project paths | None |
|
|
|
|
|
|
Environment variables are fallbacks — .preflight/ config takes precedence when present.
💡 Ready-to-use examples: Copy
examples/.preflight/into your project root for a working starter config with detailed comments.
Embedding Providers
Provider | Setup | Speed | Dimensions | Quality | Privacy |
Local (Xenova) | Zero config | ~50 events/sec | 384 | Good | 100% local |
OpenAI | Set | ~200 events/sec | 1536 | Excellent | API call |
First run with local embeddings downloads the Xenova/all-MiniLM-L6-v2 model (~90MB). After that, everything runs offline.
Architecture
flowchart TB
CC[Claude Code] <-->|MCP Protocol| PS[preflight server]
PS --> PC[✈️ Preflight Core]
PS --> DT[🎯 Discipline Tools]
PS --> TL[🔍 Timeline Tools]
PS --> AN[📊 Analysis Tools]
PS --> VR[✅ Verify Tools]
PC --> TE[Triage Engine]
DT --> PL[Pattern Learning]
TL --> LDB[(LanceDB\nper-project)]
AN --> SCE[Scorecard Engine]
TE -.-> CFG[".preflight/\nconfig.yml\ntriage.yml\ncontracts/"]
LDB --> SP[Session Parser]
SP --> JSONL["~/.claude/projects/\n(session JSONL files)"]
style CC fill:#264653,color:#fff
style PS fill:#2a9d8f,color:#fff
style PC fill:#e76f51,color:#fff
style DT fill:#e9c46a,color:#000
style TL fill:#457b9d,color:#fff
style AN fill:#6a4c93,color:#fff
style VR fill:#2d6a4f,color:#fff
style LDB fill:#1d3557,color:#fffPer-Project Data Layout
~/.preflight/
├── config.json # Global config (embedding provider, indexed projects)
└── projects/
├── index.json # Registry: path → { hash, onboarded_at }
├── a1b2c3d4e5f6/ # SHA-256(project_path)[:12]
│ ├── timeline.lance/ # LanceDB vector database
│ ├── contracts.json # Extracted API contracts
│ ├── meta.json # Event count, onboard timestamp
│ └── baseline.json # Historical scorecard averages
└── f6e5d4c3b2a1/
└── ... # Another projectTroubleshooting
"Cannot find module 'vectordb'" or LanceDB import errors
LanceDB uses native binaries. If you see module resolution errors:
# Clean install with native deps rebuilt
rm -rf node_modules package-lock.json
npm install
# If still failing, check your Node version (20+ required)
node --versionOn Apple Silicon Macs, make sure you're running a native arm64 Node — not Rosetta. Check with node -e "console.log(process.arch)" (should print arm64).
First run is slow (~90MB model download)
The local embedding provider (Xenova/all-MiniLM-L6-v2) downloads a ~90MB model on first use. This is a one-time cost — subsequent runs use the cached model. If the download hangs behind a corporate proxy, switch to OpenAI embeddings:
export OPENAI_API_KEY=sk-...
export EMBEDDING_PROVIDER=openai"OpenAI API key required for openai embedding provider"
You set EMBEDDING_PROVIDER=openai (or embeddings.provider: openai in .preflight/config.yml) but didn't provide a key. Either:
Set
OPENAI_API_KEYin your environment, orSwitch back to local:
export EMBEDDING_PROVIDER=local
Tools not showing up in Claude Code
Make sure the MCP server is registered. Run
claude mcp list— you should seepreflight.If missing, re-add it:
claude mcp add preflight -- npx tsx /path/to/preflight/src/index.tsRestart Claude Code after adding.
CLAUDE_PROJECT_DIR not set
Some tools (onboarding, session search, contracts) need to know your project root. If they return empty results:
claude mcp add preflight \
-e CLAUDE_PROJECT_DIR=/path/to/your/project \
-- npx tsx /path/to/preflight/src/index.tsOr set it globally: export CLAUDE_PROJECT_DIR=/path/to/your/project
.preflight/config.yml parse errors
If you see warning - failed to parse .preflight/config.yml, your YAML is malformed. Common issues:
Tabs instead of spaces (YAML requires spaces)
Missing quotes around values with special characters
Incorrect indentation under
related_projects
Validate with: npx yaml-lint .preflight/config.yml or paste into yamllint.com.
No session data found during onboarding
onboard_project looks for JSONL files in ~/.claude/projects/<encoded-path>/. If nothing is found:
Make sure you've actually used Claude Code on the project (at least one session)
Check that
CLAUDE_PROJECT_DIRmatches the exact path Claude Code was opened inThe path encoding is URL-style —
/Users/jack/my-appbecomes%2FUsers%2Fjack%2Fmy-app
Ollama embeddings connection refused
If using Ollama as your embedding provider and getting connection errors:
# Make sure Ollama is running
ollama serve
# Pull the embedding model
ollama pull all-minilm
# Verify it works
curl http://localhost:11434/api/embed -d '{"model":"all-minilm","input":"test"}'Contributing
This project is young and there's plenty to do. Check the issues — several are tagged good first issue.
PRs welcome. No CLA, no bureaucracy. If it makes the tool better, it gets merged.
Development
git clone https://github.com/TerminalGravity/preflight.git
cd preflight
npm install
npm run build
npm testProject Structure
src/
├── index.ts # MCP server entry point
├── lib/
│ ├── triage.ts # Prompt classification engine
│ ├── session-parser.ts # JSONL session file parser
│ ├── timeline-db.ts # LanceDB operations
│ ├── contracts.ts # Contract extraction & search
│ ├── patterns.ts # Correction pattern learning
│ ├── config.ts # .preflight/ config loading
│ ├── embeddings.ts # Embedding provider abstraction
│ ├── state.ts # Persistent state (logs, patterns)
│ ├── git.ts # Git operations
│ └── files.ts # File discovery
└── tools/
├── preflight-check.ts # Unified entry point
├── generate-scorecard.ts # 12-category scoring + trends
└── ... # One file per toolLicense
MIT — do whatever you want with it.
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