ghostpaw-questlog
OfficialClick on "Deploy 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., "@ghostpaw-questlogcapture a task to review the release notes, due Friday"
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.
@ghostpaw/questlog
A unified task and calendar model for Node.js, built on SQLite.
Questlog treats tasks, events, deadlines, recurring commitments, and loose intake as one coherent data model instead of separate systems. It ships as a single prebundled blob with zero runtime dependencies, designed for two audiences at once: human developers working directly in code, and LLM agents operating through a structured tool facade.
MCP server
Every client below starts the same stdio server: npx -y @ghostpaw/questlog mcp.
Data lives in ~/.ghostpaw/questlog.db unless the GHOSTPAW_QUESTLOG_DB
environment variable (absolute path) or --db <path> says otherwise.
Claude Code
claude mcp add ghostpaw-questlog -- npx -y @ghostpaw/questlog mcpor as a plugin, which also installs the skill:
/plugin marketplace add GhostPawJS/questlog
/plugin install ghostpaw-questlog@ghostpaw-questlogCodex CLI (~/.codex/config.toml)
[mcp_servers.ghostpaw-questlog]
command = "npx"
args = ["-y", "@ghostpaw/questlog", "mcp"]Cursor (.cursor/mcp.json), Claude Desktop (claude_desktop_config.json)
or a project .mcp.json:
{
"mcpServers": {
"ghostpaw-questlog": {
"command": "npx",
"args": ["-y", "@ghostpaw/questlog", "mcp"]
}
}
}Claude Desktop users can also install server.mcpb from the
latest GitHub release.
A Dockerfile is included for container hosts:
docker build -t ghostpaw-questlog . && docker run -i --rm -v questlog:/data ghostpaw-questlog.
The server speaks MCP 2026-07-28 (stateless, server/discover) and the
initialize-based revisions 2025-11-25, 2025-06-18, 2025-03-26 and 2024-11-05.
Related MCP server: TaskPilot MCP Server
CLI
npx -y @ghostpaw/questlog tools
npx -y @ghostpaw/questlog call capture_rumor '{"title":"Review release notes"}'
npx -y @ghostpaw/questlog call search_questlog '{"query":"release notes"}'Install globally for the ghostpaw-questlog binary: npm i -g @ghostpaw/questlog.
ghostpaw-questlog mcp starts the stdio server.
Agent Skill
SKILL.md (repo root) and skills/questlog/SKILL.md follow the
Agent Skills format and ship in the npm package.
Copy skills/questlog/ into your agent's skills folder, or print it:
npx -y @ghostpaw/questlog skill > SKILL.mdInstall
npm install @ghostpaw/questlogRequires Node.js 24+ (uses the built-in node:sqlite module).
Quick Start
import { DatabaseSync } from 'node:sqlite';
import { initQuestlogTables, read, write } from '@ghostpaw/questlog';
const db = new DatabaseSync(':memory:');
initQuestlogTables(db);
// Capture incoming work as a rumor before committing to shape
const rumor = write.captureRumor(db, {
title: 'Legal says the vendor terms changed',
details: 'Need to understand pricing delta and termination clause.',
});
// Settle the rumor into real work once the shape is clear
write.settleRumor(db, rumor.id, {
settledAt: Date.now(),
questline: {
title: 'Vendor Renewal',
description: 'Commercial, legal, and approval work.',
},
quests: [
{ title: 'Collect redlines', objective: 'Obtain the latest legal markup.' },
{ title: 'Review pricing delta', objective: 'Compare current vs. proposed cost.' },
],
});
// Drive the day from derived views, not from memory
const available = read.listAvailableQuests(db);
const dueSoon = read.listDueSoonQuests(db, 7 * 24 * 60 * 60 * 1000);
const results = read.searchQuestlog(db, 'vendor');The Model
Seven concepts, strict separation of concerns:
Concept | Purpose |
Rumor | Incoming signal that may or may not become real work |
Questline | Shared context and rollup for a group of related quests |
Quest | One concrete commitment with lifecycle, timing, and outcome |
Repeatable Quest | Recurring template that spawns fresh quests on a schedule |
Unlock | Hard prerequisite: quest B stays blocked until quest A succeeds |
Reward | Descriptive outcome attached to completed work, with a claim lifecycle |
Tag | Cross-cutting label for filtering and reporting |
The unified model means one entity type covers every temporal intention:
What it looks like | What it actually is |
A todo item | A quest with no temporal metadata |
A deadline | A quest with |
A calendar event | A quest with |
A recurring commitment | A repeatable quest with an RRULE |
A completed action | A quest resolved via |
State is derived, not toggled. A quest's availability comes from its lifecycle, timing fields, and unlock graph — computed at read time, never stored as a status flag.
Lifecycle at a glance
Questlog computes WoW-style markers on every read. They change as work moves through its lifecycle:
Intake
$\color{Goldenrod}{\textsf{❗}}$
Legal says the vendor terms changed
rumor · open↓   settle into questline + quests
Quest progression
$\color{Goldenrod}{\textsf{❗}}$
Review pricing delta
open · available$\color{Gray}{\textsf{❓}}$
Review pricing delta
in progress$\color{Goldenrod}{\textsf{❓}}$
Review pricing delta
done · reward unclaimed  ✓  
Review pricing delta
done · reward claimedOther markers
$\color{CornflowerBlue}{\textsf{❗}}$
Weekly standup notes
repeatable · due$\color{Gray}{\textsf{❗}}$
Plan Q3 roadmap
open · deferred$\color{Gray}{\textsf{❓}}$
Obtain finance approval
open · blocked
Marker IDs are semantic strings (attention.available, progress.complete, ...) computed at read time, never stored. The markers namespace maps each to its symbol, color, label, and CSS class for consistent rendering across HTML, TTY, and plain text.
Two Audiences
Human developers
Use the read and write namespaces for direct-code access to every domain operation:
import { read, write } from '@ghostpaw/questlog';
write.createQuest(db, { title: 'Ship release notes', objective: 'Draft and publish.' });
write.startQuest(db, questId);
write.finishQuest(db, questId, 'Published to blog and changelog.');
const blocked = read.listBlockedQuests(db);
const overdue = read.listOverdueQuests(db);See HUMAN.md for the full human-facing guide with worked examples.
LLM agents
Use the tools, skills, and soul namespaces for a structured runtime surface designed to minimize LLM cognitive load:
import { tools, skills, soul } from '@ghostpaw/questlog';
// 12 intent-shaped tools with JSON Schema inputs and structured results
const allTools = tools.questlogTools;
const searchTool = tools.getQuestlogToolByName('search_questlog')!;
const result = searchTool.handler(db, { query: 'vendor', mode: 'browse' });
// 25 reusable workflow skills for common multi-step scenarios
const allSkills = skills.questlogSkills;
// Thinking foundation for system prompts
const prompt = soul.renderQuestlogSoulPromptFoundation();Every tool returns a discriminated result with outcome: 'success' | 'no_op' | 'needs_clarification' | 'error', structured entities, next-step hints, and actionable recovery advice. No thrown exceptions to parse, no ambiguous prose.
See LLM.md for the full AI-facing guide covering soul, tools, and skills.
Tools
Twelve tools shaped around operator intent, not raw storage operations:
Tool | What it does |
| Cross-entity full-text search |
| Filtered list views (available, overdue, due soon, ...) |
| Detailed inspection of any single entity |
| Record incoming work before committing to shape |
| Create quests, questlines, settle rumors into structure |
| Set timing: due dates, defer dates, scheduled windows |
| Start, finish, abandon, log effort |
| Move quests between questlines, manage questline lifecycle |
| Create and maintain recurring quest templates |
| Classify quests and repeatables with tags |
| Attach, update, claim, or remove rewards |
| Soft-delete or archive things that should leave the active surface |
Each tool exports runtime metadata — name, description, JSON Schema, input descriptions, side-effect level — so agent harnesses can wire them without reading docs.
The run_quest tool refuses to start a quest with unmet unlock prerequisites and returns the blocking quests with inspection hints. Set force: true to start anyway with a warning. The library startQuest function remains permissive.
Key Properties
Zero runtime dependencies. Only
node:sqlite(built into Node 24+).Single prebundled blob. One ESM + one CJS entry in
dist/. No subpath exports, no code splitting.Pure SQLite storage. FTS5 full-text search, CHECK-constrained state transitions, trigger-maintained indexes. Bring your own
DatabaseSyncinstance.Derived state. Availability, blocking, deferral, overdue, and markers are computed at read time from fields and relationships, never stored as flags.
Intention-shaped writes.
captureRumor,settleRumor,startQuest,finishQuest,abandonQuest— operations that say what happened, not generic CRUD.RFC 5545 recurrence. Standard RRULE strings for recurring work. No custom recurrence format.
WoW-style markers. Semantic marker IDs (
attention.available,progress.complete, ...) computed on every read, renderable to any channel.Colocated tests. Every non-type module has a colocated
.test.tsfile. The behavior described in docs is backed by executable coverage.
Performance
Measured with npm run bench on Node 24.14.0, Linux, Intel Xeon (shared
cloud vCPU), 10,000 quests in a file-backed database:
Operation | p50 | p95 |
| 0.06 ms | 0.07 ms |
MCP | 0.07 ms | 0.08 ms |
| 0.07 ms | 0.08 ms |
| 26.6 ms | 41.9 ms |
| 0.22 ms | 0.69 ms |
The library search returns every match with a highlighted snippet, so a query
that matches the whole log pays for building all of those rows. Cold start
(process spawn to first response, median) is about 30 ms for --version and
the MCP server.
Package Surface
import {
initQuestlogTables, // schema setup
read, // all query functions
write, // all mutation functions
tools, // LLM tool definitions + registry
skills, // LLM workflow skills + registry
soul, // thinking foundation for system prompts
markers, // marker derivation and lookup
} from '@ghostpaw/questlog';All domain types are also available at the root for TypeScript consumers:
import type {
QuestlogDb,
QuestState,
QuestDetail,
CreateQuestInput,
QuestlogSearchResult,
QuestlogToolDefinition,
QuestlogSkill,
QuestlogSoul,
} from '@ghostpaw/questlog';Documentation
Document | Audience |
Human developers using the low-level | |
Agent builders wiring tools, skills, and soul into LLM systems | |
Architecture overview: model, invariants, lifecycle, markers | |
Per-entity manuals with exact public API listings |
Development
npm install
npm test # node:test runner
npm run typecheck # tsc --noEmit
npm run lint # biome check
npm run build # ESM + CJS + declarations via tsupThe repo is pinned to Node 24.14.0 via .nvmrc / .node-version / .tool-versions / mise.toml / Volta. Use whichever version manager you prefer.
Support
If this package helps your project, consider sponsoring its maintenance:
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Maintenance
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