evals
claudeCreate fine-tuned LLM-as-a-judge evaluators on the Plurai platform
1 skill · 1 MCP server
Set up Plurai simulation for any AI agent.
Plugin plurai-simulation from marketplace plurai-plugins in plurai-ai/plurai-plugins. Commands read from the repo's manifest — yesterday.
This plugin runs code on your machine — its hooks fire automatically on events like tool use. The exact commands are listed below; read them before installing.
analyze-simulationQuality gate for a built simulation. Independent critic sub-agents rank root causes across scenarios, harness, evals and RAG; you fix suite-side ones and loop until a critic comes back clean. Driven by /simulation-generate-suite, or run directly. Not the agent-repair step (/simulation-fixes).
analyze-tracesGround the simulation in real production traces (one stage of `/simulate`; callable alone). The SDK exports them locally; the backend turns them into a brief. By default it then turns the brief's trace failures into trace scenarios. Optional; run after /simulation-scan-agent.
author-trace-adapterAuthor a declarative YAML adapter for a trace format the SDK converter does not know (session logs, custom exporter JSON, raw log lines). Saved under plurai_sim/plurai_adapters/. Run before /trace-to-scenarios for traces that are not LangSmith or LangGraph thread exports.
build-rag-corpusBuild a knowledge corpus for an agent's RAG or SQL tools. The SDK extracts chunks locally and uploads them; the backend builds the knowledge graph and test set. One corpus per tool. Run after /simulation-scan-agent for agents with retrieval or text2SQL tools.
edit-envEdit a generated mock environment or a built RAG corpus in place through a multi-turn backend session: change a tool's return shape, seed different world state, fix a stale fact. Run after /generate-mock-env or /build-rag-corpus.
edit-evalsIterate on the generated policies_config.yaml in a backend session: add, change or remove policies, thresholds and judge prompts. Run after /generate-evals.
edit-scenariosFix a scenario's grading ground truth in place (a wrong expected_answer, stale evidence quotes, a mis-stated target), one field per call. Not for persona, questions or world: regenerate for those.
extract-eval-intentWrite eval_intent.yaml, what the customer cares about, from the PRD and scenario variables after 3-4 questions. Optional. Run standalone before a suite build, never inside /simulation-generate-suite.
extract-scenario-variablesWrite scenario_variables.yaml, the per-agent context every scenario generation reads (purpose, tools, entities, user archetypes, complications). Run after /simulation-scan-agent and before /generate-scenarios. Internal building block.
generate-evalsGenerate policies_config.yaml by calling the backend eval generation service with the agent's artifacts. Run after /simulation-scan-agent and /extract-scenario-variables.
generate-mock-envGenerate and deploy the agent's mock environment with a backend job, then store its env_id and mock url. Normally invoked by /simulation-generate-suite; run alone to rebuild the world after /simulation-scan-agent.
generate-scenariosGenerate scenarios on the Plurai-hosted backend (no local LLM credentials required) and persist them as ground truth. The plugin writes only a one-line `plurai_sim/.scenario_set_id` reference; the actual scenarios live on the backend until you delete them.
ground-scenariosRoute real material (production conversations, real records, or both) to /trace-to-scenarios or /upload-scenario-bundle, then hand off to /generate-scenarios. Run after /simulation-scan-agent when scenarios should come from real data.
harness-setupLog in to Plurai through the browser, install the SDK, connect the Plurai tools and print what this harness needs. The Plurai commands run it themselves when a login or connection is missing. Run it directly to log in again or to see which account is saved.
list-scenariosList the scenario sets stored on the backend, or inspect one in detail. Read-only — does not run anything. Useful for sanity-checking what scenarios are available before launching a simulation.
manage-envsSave, switch between and list named simulation environments under plurai_sim/envs/. Triggered by natural language such as "save this as env <name>", "switch to env <name>" and "list envs"; there are no slash commands.
optimize-evalImprove one generated llm_as_judge policy: the backend rewrites its rubric or decomposes it into a hybrid judge and benchmarks the candidates; adopt one only on your explicit confirmation. Supports --revert. Run after /generate-evals.
plurai-diagnosePrint a bundle to send to Plurai support.
plurai-uninstallRemove what the Plurai plugin created in a project and in your home folder, after you confirm each part. Run it before removing the plugin itself.
record-regressionRecord a confirmed agent issue as a regression folder under plurai_sim/regressions/ that replays the conversation which exposed it. One backend scoring call measures how often it recurs, kept in replays.json. Run by /simulation-fixes and /simulation-generate-suite, or by hand.
refine-scenariosInteractively steer which scenario types the backend generates, review what changed, then materialize. Alternative to /generate-scenarios; run after /simulation-scan-agent and /extract-scenario-variables.
simulateSimulate your agent end to end (scan, traces, suite, run, fix plan) with one live overview page and feedback in chat. Use it for first and repeat runs; it asks one start question. User-only entry point; each stage is also callable alone.
simulation-diagnoseDiagnose one already-failed run directory with error.json files, isolating a local cause (simulate.py, scenarios, config) from a remote one (mock service, seed data). Used by /simulation-fixes; not for a general run-and-diagnose request.
simulation-fixesDiagnose a run's failures and write a ranked fix plan and fixes.md with evidence and code locations; never edits the agent. Records an accepted agent fix with /record-regression BEFORE applying the fix. Stage 5 of /simulate; run after /simulation-run. Optional --verify.
simulation-generate-suiteBuild the suite: mocked world, scenarios and evals, then iterate on quality until the simulation gives sharp signal, and render a report. Stage 3 of /simulate; run after /simulation-scan-agent.
simulation-runScore the agent: a simulated user plays every scenario against it on the mocked world and all evals are scored, optionally recorded as an experiment in LangSmith, Langfuse, Arize or Braintrust. Stage 4 of /simulate. It scores but does not diagnose (use /simulation-fixes).
simulation-scan-agentMap the agent and write its harness: decide which surfaces are mocked or real, show a topology diagram for approval, then generate simulate.py and plurai.config.yaml. Stage 1 of /simulate; run it first, with the path to the agent module.
simulation-setup-agentforceInternal phase of simulation setup for a hosted Salesforce Agentforce agent (LANG is agentforce). Reached only from simulation-setup Step 10. Never invoke directly; use simulation-setup.
simulation-setup-bridgeInternal phase of simulation setup for an agent not written in Python, run through a bridge (LANG is node). Reached only from simulation-setup Step 10. Never invoke directly; use /simulation-scan-agent.
simulation-setup-pythonInternal phase of simulation setup for a Python agent (LANG is python): simulate.py template, mock contract tests, smoke run. Reached only from simulation-setup Step 10. Never invoke directly; use /simulation-scan-agent.
simulation-setup-skillInternal phase of simulation setup for an agent that is a Claude Code plugin command or skill (LANG is claude-skill). Reached only from simulation-setup Step 10. Never invoke directly; use simulation-setup.
simulation-setupAnalyze an agent codebase and generate its simulation wrapper (simulate.py, plurai.config.yaml, simulation_prd.md). Use for "set up simulation", "set up plurai", "generate simulate.py". Internal building block; prefer /simulation-scan-agent.
trace-to-scenariosTurn conversation exports into scenarios that resume where the trace ended. You never read or parse a raw trace file. `--from-brief` (chained by /analyze-traces) turns a trace brief's failures into scenarios and reads the converter's own rendering of a trace, to choose the cut.
upload-doc-examplesUpload real example documents (invoices, forms, tickets, PDFs) so generated documents follow real formatting. Only chosen examples leave the machine. Run after /simulation-scan-agent when scenarios involve documents.
upload-scenario-bundleGround scenario preconditions in real records: pick records locally, one folder per scenario with a ROLES.md, and upload only those. /generate-scenarios then builds from the folders. Run after /simulation-scan-agent.
pluraiconnects to: ${PLURAI_URL:-https://sandbox.plurai.ai/v1}/mcp
python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude --bundle regen_gate,command_run_id,halt_gate
sh "${CLAUDE_PLUGIN_ROOT}/hooks/gate.sh" skill -- python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude flow_autoarm
sh "${CLAUDE_PLUGIN_ROOT}/hooks/gate.sh" -- python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude ask_guard
sh "${CLAUDE_PLUGIN_ROOT}/hooks/gate.sh" token -- python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude plugin_root
sh "${CLAUDE_PLUGIN_ROOT}/hooks/gate.sh" token -- python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude plugin_root
sh "${CLAUDE_PLUGIN_ROOT}/hooks/gate.sh" -- python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude cron_gate
sh "${CLAUDE_PLUGIN_ROOT}/hooks/gate.sh" -- python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude cron_gate
sh "${CLAUDE_PLUGIN_ROOT}/hooks/gate.sh" -- python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude shell_syntax_guard
python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude placeholder_guard
python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude regen_spent
sh "${CLAUDE_PLUGIN_ROOT}/hooks/gate.sh" -- python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude pending_register
sh "${CLAUDE_PLUGIN_ROOT}/hooks/gate.sh" -- python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude ask_answered
sh "${CLAUDE_PLUGIN_ROOT}/hooks/gate.sh" -- python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude failure_notice
python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude --bundle session_glossary,session_pin
sh "${CLAUDE_PLUGIN_ROOT}/hooks/gate.sh" prompt -- python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude --bundle flow_arm,pending_register,flow_heartbeat
python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude --bundle flow_cleanup,session_pin
sh "${CLAUDE_PLUGIN_ROOT}/hooks/gate.sh" -- python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude pending_register
sh "${CLAUDE_PLUGIN_ROOT}/hooks/gate.sh" -- python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude pending_register
sh "${CLAUDE_PLUGIN_ROOT}/hooks/gate.sh" -- python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude report_guard
sh "${CLAUDE_PLUGIN_ROOT}/hooks/gate.sh" -- python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude flow_interrupt
sh "${CLAUDE_PLUGIN_ROOT}/hooks/gate.sh" -- python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude denial_watch
sh "${CLAUDE_PLUGIN_ROOT}/hooks/gate.sh" -- python3 "${CLAUDE_PLUGIN_ROOT}/hooks/run.py" --harness claude failure_notice
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