- Builders looking for reusable agent skills
- Teams standardizing repeated AI workflows
- Researchers comparing skill-based agent architectures
Skills
MDA
Markdown superset that compiles agent-facing documents such as SKILL.md, AGENTS.md, MCP-SERVER.md, and CLAUDE.md.
0.6K Stars
Apache-2.0 License
sno-ai Maintainer
2026-06-05 Verified
Overview
What is MDA?
MDA is an open-source agent skill resource focused on markdown superset that compiles agent-facing documents such as skill.md, agents.md, mcp-server.md, and claude.md.
Reusable skill packaging
MDA treats repeated agent behavior as reusable files or workflows rather than one-off prompts.
Reusable packaging is the difference between a clever demo and an operational agent workflow.Source-backed adaptation
The public repository gives teams a concrete starting point for forking, pruning, and adapting skills to their own standards.
Agent skills often need local conventions, so editable source is more valuable than a static prompt.Useful for capability mapping
The project helps OpenAgent readers see which skill categories are emerging around coding, security, design, marketing, research, and operations.
A good skill directory should help builders understand the shape of the ecosystem, not only collect links. Use cases
What MDA is built for
01
Build an internal skill library
Use MDA as a reference when deciding how to organize reusable agent instructions and procedures.
02
Compare agent capability coverage
Check whether the repository covers the task areas your agents repeatedly perform.
03
Fork and localize workflows
Adapt the skills to your engineering standards, tools, terminology, and review process before using them on private work.
Comparison
How it stacks up
When to choose MDA
Choose it when its official repository shows the workflow, license, and integration model you need more directly than a broad framework.
FAQ
Frequently asked questions
Is MDA open source?
Yes. The linked GitHub repository lists Apache-2.0 licensing information; verify the current license before production use.
Who should evaluate MDA?
Builders looking for reusable agent skills
Decision brief
JSON
Should you use MDA?
- Teams that need a fully managed closed product with no repository review
- Workflows that cannot tolerate experimental community-maintained skill packs
- Verified 2026-06-05
- License: Apache-2.0
- Repo: sno-ai/mda
- Open-source signal
Deployment
cloud
Permission surface
shell/files, external services
Decision signals
MCP
Agent packet
Structured decision data for MDA
This packet is the compact machine-readable view agents should use before following source links or taking action.
Capabilities
agent skill, mcp
Constraints
open source, mcp compatible
Deployment
cloud
Permission surface
shell/files, external services
Recommended workflows
Coding agent workflow, Connector or protocol layer, Reusable skill workflow
Overview
What MDA does
What it is
MDA is an open-source agent skill project tracked by OpenAgent.bot. MDA is an open-source agent skill resource focused on markdown superset that compiles agent-facing documents such as skill.md, agents.md, mcp-server.md, and claude.md.
Why it matters
MDA matters because the agent ecosystem is moving from one-off prompts to reusable skills, instructions, and workflow packs. It gives builders a source-backed way to inspect, adapt, and compare task-specific agent capability instead of reinventing the same prompt structure every time.
How to evaluate it
Open the official repository first, review setup instructions, verify the license, then test the project with non-sensitive data before connecting real accounts or production workflows.
Facts
Known metadata and operating surface
These fields are separated from editorial interpretation so agents can reason over facts and missing checks.
Resource type skill
Category Skills
Maturity active
Difficulty Unknown
License Apache-2.0
Pricing open source
Verified 2026-06-05
Source confidence medium
Risk level elevated
Fit matrix
Where MDA fits in an agent stack
strong
Coding agent workflow
MDA has multiple signals for coding agent workflow, including matching tags, capabilities, category, or positioning.
- Run a small repository change and inspect the diff, tests, and rollback path.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
strong
Connector or protocol layer
MDA has multiple signals for connector or protocol layer, including matching tags, capabilities, category, or positioning.
- Connect one low-risk service, then inspect schemas, auth scope, errors, and logs.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
strong
Reusable skill workflow
MDA has multiple signals for reusable skill workflow, including matching tags, capabilities, category, or positioning.
- Run one skill end to end and check whether it produces evidence or structured output.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
weak
Browser automation
MDA is not primarily positioned for browser automation in the current metadata.
- Run one non-sensitive website task and inspect clicks, waits, retries, and changed URLs.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
weak
Evaluation and observability
MDA is not primarily positioned for evaluation and observability in the current metadata.
- Add one repeatable test case and confirm results can run again in review or CI.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
weak
Local or private AI stack
MDA is not primarily positioned for local or private ai stack in the current metadata.
- Verify hardware requirements, data path, storage, and whether all calls stay in your environment.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
Inputs and outputs
What an agent should inspect
Likely inputs
- Repositories, files, issues, terminal output, and test results
- Tool schemas, API requests, service resources, and auth scopes
- Official setup instructions and a small real workflow
Likely outputs
- Diffs, commits, explanations, test results, or review notes
- A decision on whether this resource fits the target workflow
Evidence
Sources, claims, and missing checks
Claims are marked separately from source links so future crawlers and reviewers can update them without rewriting the page.
MDA is listed as open source.
License metadata: Apache-2.0MDA has a recorded GitHub repository: sno-ai/mda.
Resource facts and GitHub source link.MDA supports these recorded deployment modes: cloud.
OpenAgent decision signal metadata.MDA is tagged with agent skill, mcp capabilities.
OpenAgent capability taxonomy.- Dedicated docs link is missing.
- Repository freshness has not been recorded.
Next action
How to start evaluating MDA
Inspect repository
Check license, recent activity, issues, examples, and security-sensitive code paths.
Open source Compare
Alternatives and nearby resources
Use related resources to compare category fit, license, deployment model, and first-workflow behavior.
FAQ
Common questions about MDA
Is MDA open source?
Yes. The linked GitHub repository lists Apache-2.0 licensing information; verify the current license before production use.
Who should evaluate MDA?
Builders looking for reusable agent skills