progress-observability

Plugin progress-observability from marketplace progress-observability in observability-oss/progress-observability-plugin. Commands read from the repo's manifest — 23 days ago.

Skills (7)

• cost-report

  Report and explain LLM spend and usage on the Progress Observability Platform. Use when the user asks "what's driving my LLM costs", "how much am I spending", "cost by model/app", "am I close to my quota", "why did spend spike", or wants a cost/usage summary or a cheaper-model recommendation.

• coverage-gaps

  Find which of an AI system's behaviors are running in production but have no evaluation measuring them, using the Progress Observability Platform. Use when the user asks "what should I evaluate next", "what's my eval coverage", "which behaviors aren't tested", "where are my eval gaps", or wants to p

• generate-eval

  Generate a research-grounded LLM-as-a-Judge evaluator prompt for an AI system. Use when the user wants to build an eval, judge, scorer, or grader for their LLM app or agent — especially grounded in real production traces from the Progress Observability Platform. Triggers on "write an eval", "build a

• health-check

  Verify that a project's Progress Observability setup is wired up correctly — connection, key scope, whether traces are flowing, and how deep the instrumentation goes. Use when the user asks "is my observability set up right", "why am I seeing no traces", "check my connection", "is my data flowing",

• instrument-agent

  Add Progress Observability instrumentation to an existing AI agent or LLM app — Python, TypeScript/JavaScript, or .NET, including LangChain, LangGraph, LlamaIndex, CrewAI, OpenAI Agents, Haystack, MCP servers and Microsoft.Extensions.AI — with the smallest possible diff, then hand off with where to

• scaffold-agent

  Scaffold a new .NET AI agent project with Progress Observability already wired up, starting from the observability-oss dotnet-agent-starter template. Use when the user wants to create, scaffold, bootstrap, or start a new agent — "build me an agent that…", "scaffold a .NET agent", "new agent project

• trace-triage

  Investigate why an AI agent run failed, stalled, or misbehaved by walking its trace on the Progress Observability Platform. Use when the user asks "why did this run fail/error", "why was my agent slow", "what happened in this trace", "find the bottleneck", or wants to root-cause a bad tool call or a

Slash commands (8)

• /progress-observability:cost-report

  Summarize and explain LLM spend and quota usage from the Progress Observability Platform.

• /progress-observability:coverage-gaps

  Find production behaviors that have no evaluation measuring them, and prioritize which judges to build.

• /progress-observability:eval-from-scratch

  Build an LLM-as-a-Judge eval from a pasted system prompt or a description — no observability data needed.

• /progress-observability:eval-from-trace

  Build an LLM-as-a-Judge eval grounded in real traces from the Progress Observability Platform.

• /progress-observability:health-check

  Check that your Progress Observability setup is wired up correctly — connection, key scope, whether traces are flowing, and instrumentation depth.

• /progress-observability:instrument-agent

  Add Progress Observability instrumentation to an existing agent (Python, TypeScript, or .NET), then hand off with where to confirm the traces.

• /progress-observability:scaffold-agent

  Scaffold a new .NET AI agent with Progress Observability already wired up, from the dotnet-agent-starter template.

• /progress-observability:trace-triage

  Root-cause a failed or slow agent run by walking its trace on the Progress Observability Platform.

MCP servers (1)

• progress-observability

  connects to: https://mcp.observability.progress.com/mcp

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