Structured step-by-step problem decomposition and iterative analysis; explicit request only, never for regular coding tasks, and at most once per task.
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Use when a live-action beat becomes the 11-block cinematic prompt — lens, lighting, negatives. Triggers 'cinematic prompt', 'film-grade scene'. Animated → pixar-storyteller; 12-block → scene-expander.
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Use when modeling CAC, LTV, payback, contribution margin, or burn-multiple per customer — SaaS, marketplace, or transactional. Triggers on 'are we unit-economic', 'what is our LTV/CAC'.
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Use for multi-step / ambiguous / end-to-end work — refactor a whole module, drive a vague ticket to a verified result, plan+build+verify a migration; coordinates the reasoning chain across skills.
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Use when PHPStan, Rector, or ECS output appears — "phpstan says mixed", type errors, "fix code style", "run rector" — even when Eloquent/Laravel/model code is also mentioned.
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Translate an image brief into provider-specific prompt grammar per model. Use when writing or refining an image-generation prompt for Ideogram, Flux, Gemini, GPT Image 2, or Recraft.
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Use when tracing the root cause of a resolved incident or recurring bug — 5-whys chain, fishbone categorisation, contributing-factors split — even if the user says 'why does this keep breaking?'.
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Pre-spend contradiction gate for AI-video runs: checks every prompt in the batch, blocks on style / character / physics mismatch. Triggers 'validate the prompts', 'check the storyboard'.
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Use when authoring or rewriting a roadmap in agents/roadmaps/ — phases, goal, acceptance criteria, council notes; fires even on 'write a plan for X' / 'draft a roadmap'.
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Use when looking for project-specific documentation. Knows which docs exist in agents/reference/docs/ and agents/settings/contexts/ and maps work areas to relevant docs.
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Use when constructing base / upside / downside scenarios — three-statement modeling, sensitivity analysis, optionality reasoning. Triggers on 'model the scenarios', 'what if growth halves'.
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Use for deep React analysis: component tree, state flow, props flow, hooks usage, rendering behavior, and React-specific failure patterns.
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Use for deep Symfony project analysis: kernel/bootstrap, container wiring, routing/request flow, Doctrine, security, Messenger, and Symfony-specific failure patterns.
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Use when setting up React Native or Expo dev environments — Xcode, Android Studio, CocoaPods, EAS, Metro, New Architecture — even when the user just says 'my RN build won't start'.
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Use for deep Zend Framework or Laminas project analysis: bootstrap, config merge order, service manager, MVC flow, data layer, and migration-specific risks.
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Use for deep Laravel project analysis: boot flow, request lifecycle, container usage, Eloquent/data flow, async systems, and Laravel-specific failure patterns.
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Use before committing to a heavy or irreversible plan — imagine it's 6 months later and this failed; enumerate why, score each mode, derive early-warning signals and preventive guardrails.
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When processing code review feedback (bot or human) before changing anything — triages, verifies and pushes back with technical reasoning — even when the user just says 'fix the comments'.
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Use when reviewing data flows, support macros, refund templates for GDPR/CCPA/HIPAA fit — regime, consent, PII redaction (email, order-id), breach triage. Triggers 'is this GDPR-safe', 'PII redact'.
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Single-pass tech-stack detection with an agents/evidence/analysis/ write-up; explicit request only. Deep multi-pass audit → universal-project-analysis. Raw primitives → project-analysis-core.
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Use for deep Next.js analysis: server vs client boundaries, routing, data fetching, caching, rendering modes, and hydration/runtime issues.
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Use when surfacing and prioritising risk before commit — blast-radius framing, mitigations, residual-risk verdict — even if the user just says 'what could go wrong here?'.
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Use when ranking competing initiatives for a roadmap, breaking a tie between two features, or auditing a backlog for hidden low-value work via Reach × Impact × Confidence ÷ Effort.
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Use when a bug has multiple plausible causes across layers — competing hypotheses, validation loops, evidence-based conclusions — even when the user just says 'why is this happening?'.
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