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area/docs-sitedocs/src/content (Starlight), README, doc generation.docs/src/content (Starlight), README, doc generation.area/package-authoringapm pack/unpack, plugin authoring, vendoring guidance, bundle format.apm pack/unpack, plugin authoring, vendoring guidance, bundle format.status/acceptedDirection approved, safe to start work.Direction approved, safe to start work.status/triagedInitial agentic triage complete; pending maintainer ratification (silence = approval).Initial agentic triage complete; pending maintainer ratification (silence = approval).type/docsDocumentation change (prose, examples, generated reference).Documentation change (prose, examples, generated reference).
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APM Feedback — CM Labs (Wanda)
Team name: CM Labs
Project: Wanda — AI Data Engineer for Microsoft Fabric
Repo: https://github.com/Timbermitch/wanda/blob/main/apm.yml
Submitter: Timbermitch
What we used APM for
We used APM as the manifest layer for Wanda — an agent that investigates failed Microsoft Fabric pipelines. The
apm.ymldescribes:AGENTS.md)mcp.json) which exposes 4 Fabric toolssrc/wanda.py)This let us co-locate the agent's identity, tools, runtime, and permissions in one declarative file alongside the source code.
What worked
apm.ymlschema was easy to write by hand. Clear separation between metadata, runtime config, capabilities, and permissions.AGENTS.mdandmcp.jsonfrom a single manifest is great — it keeps the agent's persona, tools, and runtime co-located.What could be improved
apm.ymlis still light. We had to look at examples in the APM repo to figure out the expected fields.permissionsare enforced at runtime or just declarative metadata.apiVersion: apm.github.com/v1) — we copied this from examples but couldn't find a definitive reference.apm.ymlwhile you write it would be a big win.apm.ymldirectly to discover MCP servers and persona, instead of needing separate config.Overall
Useful piece of the puzzle. The single-manifest approach is the right idea — it makes agents portable and reproducible. Mostly needs more docs and tooling around the schema to feel production-ready. We'd use it again.