Skip to main content
Glama
kunwarVivek

mcp-github-project-manager

by kunwarVivek

AI Generation

ai_generate

Generate, enhance, or parse PRDs and turn feature ideas into prioritized tasks with complexity analysis, next-task guidance, expansion, and traceability matrices.

Instructions

AI-powered generation: generate/enhance/parse PRDs, add features, get next tasks, analyze complexity, expand tasks, create traceability matrices. Use the action field to select the operation.

Input Schema

NameRequiredDescriptionDefault
limitNo
tasksNo
actionYesThe AI generation operation to perform
authorNo
agentIdNo
assigneeNo
featuresNo
maxDepthNo
maxTasksNo
timelineNo
featureIdNo
projectIdNo
targetPRDNo
taskTitleNo
complexityNo
focusAreasNo
prdContentNo
teamSkillsNo
autoApproveNo
descriptionNo
featureIdeaNo
labelPrefixNoLabel prefix for materialized issues (e.g. "ai-generated")
maxSubtasksNo
projectIdeaNo
projectNameNo
projectTypeNo
requestedByNo
targetUsersNo
addToProjectNoWhether to add created issues to the specified projectId
autoEstimateNo
contextLevelNo
currentPhaseNo
includeRisksNo
stakeholdersNo
expandToTasksNo
maxComplexityNo
targetProjectNo
autoPrioritizeNo
excludeBlockedNo
projectContextNo
sprintCapacityNo
targetAudienceNo
teamExperienceNo
createLifecycleNo
currentEstimateNo
enhancementTypeNo
improveExistingNo
includeAnalysisNo
includeResearchNo
includeSubtasksNo
includeUseCasesNo
industryContextNo
taskDescriptionNo
validateQualityNo
includeBreakdownNo
includeEstimatesNo
targetComplexityNo
currentComplexityNo
addMissingElementsNo
enhancedGenerationNo
includeDependenciesNo
validateCompletenessNo
businessJustificationNo
autoDetectDependenciesNo
includeBusinessContextNo
includeRecommendationsNo
includeCoverageAnalysisNo
includeTechnicalContextNo
createTraceabilityMatrixNo
includeTraceabilityLinksNo
includeAcceptanceCriteriaNo
includeImplementationGuidanceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv3.0.0

TDQS

C2.3/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotations already declare this is not read-only, is open-world, non-idempotent, and non-destructive. The description adds no behavioral context about what each action creates or changes, whether AI calls are costly or slow, or what side effects accompany actions like add_feature and materialize_tasks. For a nine-action mutation tool, this leaves major gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the operation list, and has no filler. It is concise, though that concision comes at the cost of substantial under-specification for such a large action space.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 72-parameter, nine-action tool with no output schema, the description is far too thin. It does not explain how parameters map to actions, what each action returns, or what side effects to expect, leaving the agent without enough information to invoke it confidently.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 4%, with 72 parameters, so the description must compensate. It does not: it only mentions the action field, and even that adds no meaning beyond the enum and schema description. The remaining 69 parameters are undocumented in both schema and description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific capability bundle (AI-powered generation) and lists many operations, so the agent can tell it is a multi-action AI tool. However, it does not distinguish this from sibling AI tools like ai_plan or ai_analyze, and the main prose omits the materialize_tasks action that appears in the enum.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The only guidance is 'Use the action field to select the operation.' There is no when-to-use guidance, no when-not-to-use guidance, no alternatives among siblings, and no prerequisites or per-action selection advice.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.