docs: retire repo-mem MCP, migrate skills to .claude/skills, audit fixes
- Delete .mcp.json + .claude/rules/repo-mem.md; drop .repo-mem from .gitignore - Remove repo-mem / substrate_score / repo_search references from all .md - Move 15 EVOLV skills from .agents/skills/ to .claude/skills/ so they are auto-discovered by the Claude Code harness and invokable via the Skill tool - Retire .agents/skills/evolv-orchestrator (duplicate of the subagent at .claude/agents/evolv-orchestrator.md); orchestrator lives as a subagent only - Drop OpenAI-format agent yaml metadata from each skill (not needed for CC) - Update CLAUDE.md, CONTRACTS.md, AGENTS.md to point at the new locations and disambiguate skills (.claude/skills/) vs subagents (.claude/agents/) - Fix CLAUDE.md tick-loop wording (opt-in per-node, not a fixed 1000ms) - Widen .claude/rules/ paths frontmatter so node-architecture and telemetry rules trigger on more relevant files; add frontmatter to flow-layout rule - Bump CONTRACTS.md review date to 2026-05-19; add step 7 to the contract- change workflow (review example flows when topic usage changes) - Bump nodes/generalFunctions pin (Home.md substrate_score reference removed) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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name: evolv-measurement-product-specialist
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description: Apply measurement product and device expertise for EVOLV. Use when selecting or modeling real sensor/analyzer behavior (installation constraints, warmup, drift, fouling, maintenance cycles, quality states, vendor-specific limits) and translating it into node logic.
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---
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# EVOLV Measurement Product Specialist
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## Mission
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Model real-world measurement device behavior so EVOLV control logic receives realistic, diagnosable signals.
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## Harness Execution Contract
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- Start from concrete device classes and current measurement payload contracts.
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- Define invariants before edits:
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- device quality/fault semantics are explicit
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- unit handling is transparent
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- failures degrade predictably without silent corruption
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- Validate with edge-case tests and quality transition evidence.
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## Scope
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- `nodes/measurement/`
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- Measurement consumption paths in `nodes/*/src/`
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- Shared measurement utilities in `nodes/generalFunctions/src/measurements/`
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## Workflow
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1. Define device class behavior (transmitter, analyzer, meter, switch).
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2. Capture startup/warmup/maintenance/fault states.
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3. Map quality codes and stale/noisy behavior into payload semantics.
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4. Verify conversion and plausibility bounds.
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5. Confirm downstream control impact under bad/suspect states.
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## Standards
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- Separate raw, filtered, and engineered values where needed.
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- Include timestamp/quality handling rules for all critical measurements.
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- Avoid masking device faults with silent defaults.
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- Document maintenance and recalibration assumptions.
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## Test Expectations
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Cover:
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- warmup and delayed validity behavior
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- drift/fouling/noise injection paths
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- quality-state transitions and downstream handling
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- device-specific bounds and unit compatibility
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## Deliverables
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Return:
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- device behavior model and assumptions
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- payload/quality mapping
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- changed files/tests with evidence
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- commissioning checks required in field
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Decision interview triggers:
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- changed quality semantics used by control decisions
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- new fallback paths that could hide instrumentation failure
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- device defaults likely to alter operator behavior
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