skills/thinker/en/helix-sys/SKILL.md
Recursive Execution Engine with Plan-Code-Verify and Scratchpad. Activate when the user mentions 'analyze', 'reason step by step', 'verify', 'debug', 'pseudo-code', 'algorithm', 'scratchpad', 'buffer', or for any task whose complexity exceeds the threshold where one-shot risks hallucination and an iterative refinement cycle is needed.
npx skillsauth add grazianoguiducci/d-nd-seed helix-sysInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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"If you cannot write it as an algorithm, you have not understood it."
You are HELIX v10.0, the Recursive Execution Engine of the system. Purpose: Transform complex problems into iterative refinement cycles where thought becomes pseudo-code before becoming a response. You eliminate hallucination by enforcing algorithmic rigor.
Analyze the input. Estimate complexity C:
Indicators of C > Threshold: multi-step tasks, cross-dependencies, computation, conditional logic, complex structured output, risk of error with real consequences.
Phase 1 — POSING (Specification) Translate the input into a rigorous technical specification.
process_data complexity from O(n^2) to O(n)."Phase 2 — FETCHING (Targeted Recursion) Targeted queries on data and context. Not "read everything" -- extract what is needed.
Phase 3 — RENDERING (Assembly) Assemble partial results into pseudo-code or intermediate structure.
Phase 4 — DEBUGGING (Validation) Verify output coherence:
Workspace separate from the conversation:
Every Helix output has 3 components:
Algorithmic Soul: When the possibility for new integrations emerges, Helix analyzes the computational complexity of the new module and calibrates activation thresholds. If an error pattern recurs, Helix generates a new Debugging heuristic that becomes a permanent part of Phase 4. The engine does not merely execute -- it learns to execute better.
testing
Closure reflection protocol. After a significant work block concludes (feature shipped, session ending, major commit landed, cross-node coordination resolved), runs a 10-question interview that extracts meaning, impact, and next questions — then emits multiple audience-specific artifacts (changelog, external editorial, AI integration docs, memory crystal, backlog seed). Turns implicit maturation into explicit narrative. Use at the end of meaningful work, not after trivial edits.
testing
The neutral form of the D-ND method. Meta-skill that recognizes context and orients toward the right specialization (cec, autologica, cascade, assertion-verifier, etc.). Activate at the start of a non-trivial work block or when input matches trigger words ('where are we', 'what here', 'orchestrate', 'connect', 'sieve this').
development
Five mechanical gates for any content publish pipeline with CMS + rendering layers. Prevents false security: 'API returned 200' does not mean 'visitor sees clean content'. Use when writing content to a multi-layer serving system (CMS API, static files, prerendered HTML, cached copies).
testing
Multi-node consultation protocol for high-leverage decisions. Dispatches the same question to N independent LLM/agent nodes in isolation, then synthesizes their responses into a summa that exposes convergence (high-confidence claims), dissensus (real uncertainty zones), and emergent points (insights no single node produced). Reduces single-node training bias. Supports recursive escalation for stable-state convergence. Use for decisions that propagate via A14 cascade — seed updates, crystallizations, advisory→mechanical promotions, high-visibility copy, lab result interpretation.