zotoio

Guided workflow for launching and interpreting the cursor-top TUI. Covers process discovery, hierarchy expansion, log tail interpretation, and recommended flags for different scenarios. Use when the user wants to monitor every Cursor agent on their machine in real time, or to capture a snapshot for a report.

Writes .zoto/eval-system/config.yml from field values pre-collected by /z-eval-configure (command-owned askQuestion). Refuses bundled update.preserveUserAuthoredCases:false or update.writeMetaMarker:false (including nested payload mirrors) before any manifest read or config write. Validates against templates/schema/config.schema.json. Diffs the chosen config against the manifest snapshot (discovery_config.static.framework) to produce a cleanup_plan validated against templates/schema/cleanup-plan.schema.json, and stamps _meta.primitive_analysis.invalidate=true on every cached primitive analysis when the static framework changes. The unified LLM eval harness ships one JSON-first co-located eval per target, with no per-repo selector axis — only the static framework matters here. Never calls askQuestion — returns needs_user_input if validation cannot proceed without user clarification.

Scaffolds static pytest and LLM (@cursor/sdk) eval backends into a host repository, generates eval cases with _meta.generated markers for approved skills/commands/agents/hooks, merges eval scripts into package.json, and writes the persistent manifest plus append-only history. Expects the invoking command to pre-collect approved targets — does not call askQuestion.

Invocation reference for all eval-system CLI commands. Use this skill when you need to run eval scripts — never reference script paths directly; always invoke via the package.json aliases documented here.

Executes eval runs via the host repo's package.json scripts (pnpm run eval, eval:full, eval:llm, eval:judge). Forwards --model to the LLM runner via both a CLI flag and the ZOTO_EVAL_MODEL environment variable. After each run, calls eval:update --check and appends the drift status to the run report as a warn-only line. Does not call askQuestion — credential gaps use needs_user_input for the command.

Adversarial judge for eval runs. Identifies weak graders, under-covered assertions, verbosity spikes, and accuracy/confidence regressions. Produces an enriched llm.yml with soft-metric annotations. Does not call askQuestion — handoff to /z-eval-update is expressed as needs_user_input for the command to confirm via askQuestion and resume. Uses the configured judgeModel (default claude-opus-4-8[]).

Diff-aware eval updater. Detects drift between covered targets and generated eval cases for skills and central plugin eval files (commands/agents/hooks), classifies changes as critical or non-critical, and preserves user-authored cases verbatim. Apply-mode regeneration re-invokes the LLM analyser per drifted primitive and dispatches per-framework static stamping plus the single unified LLM regeneration (`regenerateLlm`) (CI defaults to cached analyser payloads unless `--with-analyser`). The `_meta.generated === true` (case) and `// _meta.generated\: true` (file) contracts are enforced at runtime AND compile time. Supports targeted mode, rediscovery mode, `--no-analyser` / CI cache reuse, and CI `--check` (exit 2 on critical drift).

Project-tailored help for the Eval System plugin. Loads plugins/zoto-eval-system/README.md as the source of truth, inspects current project state (.zoto/eval-system/config.yml, manifest.yml, .env*, evals/_runs/, package.json scripts), and composes an answer that is grounded in the chosen README section, tailored to the host repo's actual configuration and artefacts, and cited with `start:end:path` code references back to the README. Pre-collected `help_context` arrives from the /z-eval-help command (command-owned askQuestion). The skill itself never calls askQuestion — missing context is returned as `needs_user_input`.

Build a prioritised memory index from all memory files and reference trackers. Use when rebuilding the memory index, after memory CRUD operations, or when agents need a sorted discovery list.

Consolidate, promote, demote, and archive memories based on strength, usage patterns, and type transition rules. Use when running REM sleep, rebalancing memory strength, detecting conflicts, or cleaning up orphaned trackers.

Multi-purpose utility for CRUX compression workflows. Provides token estimation and checksum calculation. Use when estimating tokens for compression, comparing file sizes, or getting checksums for sourceChecksum tracking.

File-based coordination primitives for meditation: artefact filename grammar (18 rows including `init-suggestions-{ts}.yml`, `finalisation-enhancements.yml`, per-tree ensemble variants, and 4 follow-up artefact types), placeholders, prefix-glob polling rule, never-hard-code invariant, retrospective template, Branch & Leaf Index template (single-model + ensemble variants). Use whenever the `crux-cursor-meditation-guide` agent reads, writes, or links a working-directory artefact.

Ensemble Aggregation function for meditation: reads N model consolidations, writes `cross-model-synthesis.md`, performs K10 root cross-model reflection (step 3c), manages K10 layered cadence steps 3b–3f (per-tree `finalisation-enhancements.yml` reads + root combined YAML write with `cross_model_candidates` + `union_candidates`), returns single combined `needs_user_input`, dispatches resume-handler by `source` provenance, and hands off to the report skill for ensemble HTML+PDF generation. Use when the `crux-cursor-meditation-guide` agent is spawned with `ensembleAggregation: true`.

Quick-mode meditation protocol: 6-step parallel fan-out with optional deep-confirm hook, warn-only citation validation, upfront child derivation, no peer review, K10c reflection (same rubric, warn-only at every richness level per K7). Use when the `crux-cursor-meditation-guide` agent runs the Quick depth-0 manager or any Quick-mode child agent.

Mandatory paired HTML+PDF report generation for meditation: Comprehensiveness Level Mapping (12 dimensions × 4 levels), anti-homogenisation rules, Universal Contrast, light/dark mode + print TOC, Chart.js / D3 / calculator content minima with static fallbacks, Per-Branch Section Rule, Depth-3 Leaf Inclusion Rule, Peer-Review Surfacing Rule, Init-Suggestions Honour rules, K10b Per-Cheap-Type Rendering Contract (7 cheap types), and Report-Skill Respawn Protocol resume-handler. Use when the `crux-cursor-meditation-guide` agent runs report generation (step 12), when the ensemble aggregator generates the ensemble-level report, or when the report skill is respawned via Dim 13.

Research-mode meditation protocol: Phases A–G depth-first recursion, depth-0 manager steps 1–13 (incl. step 4b 4-mode `additional_focus_areas[]` reconciliation + `init-suggestions-{ts}.yml` write; step 8 K10c reflection writing `finalisation-enhancements.yml`; step 8b respawn-payload prep), facet registry lock, citations index, peer review file spec, comprehensiveness honouring at leaf depth. Use when the `crux-cursor-meditation-guide` agent runs the depth-0 manager or any Research-mode child agent.

Multi-purpose utility for CRUX compression workflows. Provides token estimation and checksum calculation. Use when estimating tokens for compression, comparing file sizes, or getting checksums for sourceChecksum tracking.

Guide for creating engineering plans through a structured workflow. Use when planning new features, coordinating multi-agent work, or breaking down complex initiatives.

Guide for executing engineering plans through coordinated subagent work. Use when executing existing plans from knowledge/plans/ directory.

Guide for creating a new package in the X-Fidelity monorepo. Use when adding new packages, setting up monorepo structure, or configuring workspace dependencies.

Guide for ensuring CLI and VSCode extension produce identical analysis results. Use when verifying CLI-Extension parity, debugging output differences, or setting up consistency checks.

Guide for creating a new X-Fidelity archetype configuration. Use when defining project templates, configuring rule sets, or setting up dependency requirements.

Guide for creating a new X-Fidelity plugin from the template. Use when creating plugins, adding new analysis capabilities, or extending the plugin system.

End-to-end guide for creating a new X-Fidelity analysis rule. Use when creating rules, adding new checks, or when the user asks about rule development.