A
licenseNot graded
qualityB
maintenanceHelps AI agents decompose goals into costed execution plans, checkpoint progress with deviation tracking, and learn from past project data.
31 npm
MIT
taskguard-mcp
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- FlicenseNot gradedqualityDmaintenanceEnables persistent task and goal management with AI-powered decomposition, cross-session continuity, and fault-tolerant multi-agent pipelines.1-
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to decompose high-level goals into structured task plan DAGs with dependencies, acceptance criteria, and quality gates, and to validate or export those plans in multiple formats.MIT
- FlicenseNot gradedqualityDmaintenanceProvides AI agents with simplified task management through a 4-step workflow (create session, define tasks, execute, complete) that works with any LLM without requiring complex thinking patterns.-
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- AlicenseAqualityDmaintenanceProvides plan state management and phase gate enforcement for AI development loops. It tracks task progress and coordinates the lifecycle of agents by requiring specific evidence before advancing through development phases.10MIT
TDQS
A3.8/5.0
Scored across 12 tools
Disambiguation5/5
Every tool has a clearly distinct role: goal definition, checkpoint management, evidence, criteria, decisions, scope checks, blockers, verification, status, and session reset. No overlap or ambiguity.
Naming Consistency5/5
All tools follow a consistent pattern: 'taskguard_' + verb_noun (e.g., add_checkpoint, update_criterion, verify_done). Naming is uniform and predictable.
Tool Count5/5
12 tools is an ideal number for a task management server. Each tool serves a necessary function without redundancy or bloat.
Completeness5/5
The toolset covers the full task lifecycle: definition, execution tracking (checkpoints, evidence, blockers), verification, and status retrieval. No obvious gaps.
Maintenance
ActivityStale
ResponsivenessNo issues