adynato-aimake_skill

This skill helps you integrate with aimake MCP to manage cards, boards, and AI-assisted work delivery across projects.

1

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill adynato/skills --skill adynato-aimake

  • SKILL.md7.6 KB

Overview

This skill integrates with aimake’s AI-powered delivery pipeline via the MCP (Model Context Protocol). It helps connect to aimake, use code/docs/kanban MCP tools, and work with card-based deliverables while leveraging card AI to co-author work. Use it when building integrations, automations, or agents that interact with aimake projects and workflows.

How this skill works

The skill communicates with aimake through MCP endpoints to fetch a manifest and call named tools (e.g., search_code_semantic, query_cards, spawn_cards). It inspects repository code, project docs, and kanban cards, then reads and updates card fields, searches for context, and moves cards between stages. Responses follow a simple JSON success/error pattern so integrations can parse results and react programmatically.

When to use it

  • Building an integration or agent that needs project context from code and docs
  • Automating card creation, triage, or routing using aimake’s kanban tools
  • Implementing AI-assisted authoring for specification, implementation, or docs
  • Querying project state to drive progress-tracking dashboards or reports
  • Creating a triage agent that synthesizes docs and code to spawn cards

Best practices

  • Fetch the MCP manifest first to discover available tools and their parameters
  • Use semantic code search for conceptual matches and text search for precise patterns
  • Keep cards atomic: spawn separate cards for independent deliverables
  • Let card AI suggest splits and validate readiness before moving stages
  • Always handle success=false responses and surface errors for human review

Example use cases

  • Triage agent: search docs and code, summarize a request, and spawn product or bug cards
  • Context retrieval: pull file trees, read files, and collect docs to provide an AI conversation with full context
  • Progress tracking: query cards across boards and stages to generate a real-time status dashboard
  • Developer assistant: search codebase for implementation details, update technicalNotes on cards, and move cards to review
  • Onboarding automation: create starter cards and populate acceptance criteria from templates

FAQ

Call the MCP endpoints with your instance base URL and include an Authorization header with a Bearer API key.

Which tool should I use to find where a feature is implemented?

Start with search_code_semantic for conceptual matches, then refine with search_code_text and read_file for exact locations.

Built by
VeilStrat
AI signals for GTM teams
© 2026 VeilStrat. All rights reserved.All systems operational