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✈️ 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.

TypeScript MCP License: MIT npm Node 18+

Quick Start · How It Works · Tool Reference · Configuration · Scoring


What's New in v3.2.0

  • Unified preflight_check entry point — one tool that triages every prompt and chains the right checks automatically

  • Smart 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 thresholds

  • Trend & 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 them

  • Each 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 time

Quick Start

Option A: npx (fastest — no install)

claude mcp add preflight -- npx -y preflight-dev-serve

With environment variables:

claude mcp add preflight \
  -e CLAUDE_PROJECT_DIR=/path/to/your/project \
  -- npx -y preflight-dev-serve

Option B: Clone & configure manually

git clone https://github.com/TerminalGravity/preflight.git
cd preflight && npm install

Add 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-serve

Note: preflight-dev runs the interactive setup wizard. preflight-dev-serve starts 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:#fff

Each level triggers different tool chains:

Level

What fires

Example prompt

Trivial

Nothing — pass through

commit

Clear

File verification only

fix null check in src/auth/jwt.ts line 42

Ambiguous

Clarify intent + git state + workspace priorities

fix the auth bug

Cross-service

Clarify + search related projects + contracts

add tiered rewards

Multi-step

Clarify + scope + sequence + checkpoints

refactor auth to OAuth2 and update all consumers

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:#fff

Session 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 sessions

Each JSONL line is an event. The session parser extracts 8 event types:

Event Type

Source

What it captures

prompt

user messages

What the dev typed

assistant

assistant messages

Claude's text response

tool_call

assistant tool_use blocks

Tool invocations (Read, Write, Bash, etc.)

sub_agent_spawn

Task/dispatch_agent tool_use

When Claude delegates to a sub-agent

correction

user messages after assistant

Detected via negation patterns (no, wrong, actually, undo…)

compaction

system messages

Context was compressed (session hit token limit)

error

tool_result with is_error

Failed operations

commit

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

export interface/type/enum

TypeScript type definitions

export function GET/POST/…

Next.js API routes

router.get/post/…

Express route handlers

model Foo { … }

Prisma models and enums

OpenAPI/Swagger specs

Routes and schema components

.preflight/contracts/*.yml

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:

  1. Discovers sessions — finds JSONL files in ~/.claude/projects/<encoded-path>/, including subagent sessions

  2. Parses events — extracts the 8 event types from each session file (streams files >10MB)

  3. Extracts contracts — scans source for types, interfaces, enums, routes, Prisma models, OpenAPI schemas

  4. Loads manual contracts — merges any .preflight/contracts/*.yml definitions (manual wins on name conflicts)

  5. Generates embeddings — local Xenova/all-MiniLM-L6-v2 by default (~90MB model download on first run, ~50 events/sec) or OpenAI if OPENAI_API_KEY is set (~200 events/sec)

  6. Stores in LanceDB — per-project database at ~/.preflight/projects/<sha256-12>/timeline.lance/

  7. 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

preflight_check

The main entry point. Triages your prompt (trivial → multi-step), chains the right checks automatically, matches against known correction patterns. Accepts force_level override: skip, light, full.

🎯 Prompt Discipline

Tool

What it does

scope_work

Creates structured execution plans before coding starts

clarify_intent

Gathers project context (git state, workspace docs, ambiguity signals) to disambiguate vague prompts

enrich_agent_task

Enriches sub-agent tasks with file paths, patterns, and cross-service context

sharpen_followup

Resolves "fix it" / "do the others" to actual file targets

token_audit

Detects waste patterns, grades your session A–F

sequence_tasks

Orders tasks by dependency, locality, and risk

checkpoint

Save game before compaction — commits + resumption notes

check_session_health

Monitors uncommitted files, time since commit, turn count

log_correction

Tracks corrections and identifies recurring error patterns

check_patterns

Checks prompts against learned correction patterns — warns about known pitfalls

session_handoff

Generates handoff briefs for new sessions

what_changed

Summarizes diffs since last checkpoint

🔍 Timeline Intelligence

Tool

What it does

onboard_project

Indexes a project's session history + contracts into per-project LanceDB

search_history

Semantic search with scope: current project, related, or all indexed projects

timeline

Chronological view of events across sessions

scan_sessions

Live scanning of active session data

📊 Analysis & Reporting

Tool

What it does

generate_scorecard

12-category report card — session, trend (week/month), or cross-project comparative. Radar chart SVG, PDF or markdown.

estimate_cost

Token usage, dollar cost, waste from corrections, preflight savings

session_stats

Lightweight session analysis — no embeddings needed

prompt_score

Gamified A–F grading on specificity, scope, actionability, done-condition

✅ Verification & Hygiene

Tool

What it does

verify_completion

Runs type check + tests + build before declaring done

audit_workspace

Finds stale/missing workspace docs vs git activity

search_contracts

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 min

Search 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-For

Grade 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 hits

Get 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 prompting

The 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 .claude/ or CLAUDE.md

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-types

Option 2: Environment variable (per-user)

PREFLIGHT_RELATED=/path/to/auth-service,/path/to/notifications

How it works

  1. You type: "add rewards tier validation"

  2. Triage detects rewards matches always_check keyword → ambiguous

  3. Cross-service keywords (auth, notification) don't match, but if you had typed "add rewards with auth check"cross-service

  4. Preflight searches related projects' LanceDB indexes and contract registries

  5. Returns relevant types, interfaces, and routes from those projects

  6. You get context like: "auth-service has interface AuthToken { userId, tier, permissions } and POST /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

CLAUDE_PROJECT_DIR

Project root to monitor

Required

OPENAI_API_KEY

OpenAI key for embeddings

Uses local Xenova

PREFLIGHT_RELATED

Comma-separated related project paths

None

EMBEDDING_PROVIDER

local or openai

local

PROMPT_DISCIPLINE_PROFILE

minimal, standard, or full

standard

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 OPENAI_API_KEY

~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:#fff

Per-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 project

Troubleshooting

"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 --version

On 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_KEY in your environment, or

  • Switch back to local: export EMBEDDING_PROVIDER=local

Tools not showing up in Claude Code

  1. Make sure the MCP server is registered. Run claude mcp list — you should see preflight.

  2. If missing, re-add it:

    claude mcp add preflight -- npx tsx /path/to/preflight/src/index.ts
  3. Restart 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.ts

Or 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_DIR matches the exact path Claude Code was opened in

  • The path encoding is URL-style — /Users/jack/my-app becomes %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 test

Project 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 tool

License

MIT — do whatever you want with it.

A
license - permissive license
-
quality - not tested
C
maintenance

Maintenance

Maintainers
20dResponse time
Release cycle
1Releases (12mo)
Commit activity
Issues opened vs closed

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MCP directory API

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