$npx -y skills add DNYoussef/context-cascade --skill cognitive-lensing/*============================================================================*/ /* COGNITIVE-LENSING SKILL :: VERILINGUA x VERIX EDITION */ /*============================================================================*/
| 1 | /*============================================================================*/ |
| 2 | /* COGNITIVE-LENSING SKILL :: VERILINGUA x VERIX EDITION */ |
| 3 | /*============================================================================*/ |
| 4 | |
| 5 | --- |
| 6 | name: cognitive-lensing |
| 7 | version: 1.0.1 |
| 8 | description: | |
| 9 | [assert|neutral] Cross-lingual cognitive framing system that activates different reasoning patterns by embedding multi-lingual activation phrases. Use when facing complex tasks that benefit from specific thinking patt [ground:given] [conf:0.95] [state:confirmed] |
| 10 | category: foundry |
| 11 | tags: |
| 12 | - cognitive-science |
| 13 | - cross-lingual |
| 14 | - meta-prompting |
| 15 | - frame-selection |
| 16 | - reasoning-enhancement |
| 17 | author: system |
| 18 | cognitive_frame: |
| 19 | primary: compositional |
| 20 | goal_analysis: |
| 21 | first_order: "Execute cognitive-lensing workflow" |
| 22 | second_order: "Ensure quality and consistency" |
| 23 | third_order: "Enable systematic foundry processes" |
| 24 | --- |
| 25 | |
| 26 | /*----------------------------------------------------------------------------*/ |
| 27 | /* S0 META-IDENTITY */ |
| 28 | /*----------------------------------------------------------------------------*/ |
| 29 | |
| 30 | [define|neutral] SKILL := { |
| 31 | name: "cognitive-lensing", |
| 32 | category: "foundry", |
| 33 | version: "1.0.1", |
| 34 | layer: L1 |
| 35 | } [ground:given] [conf:1.0] [state:confirmed] |
| 36 | |
| 37 | /*----------------------------------------------------------------------------*/ |
| 38 | /* S1 COGNITIVE FRAME */ |
| 39 | /*----------------------------------------------------------------------------*/ |
| 40 | |
| 41 | [define|neutral] COGNITIVE_FRAME := { |
| 42 | frame: "Compositional", |
| 43 | source: "German", |
| 44 | force: "Build from primitives?" |
| 45 | } [ground:cognitive-science] [conf:0.92] [state:confirmed] |
| 46 | |
| 47 | ## Kanitsal Cerceve (Evidential Frame Activation) |
| 48 | Kaynak dogrulama modu etkin. |
| 49 | |
| 50 | /*----------------------------------------------------------------------------*/ |
| 51 | /* S2 TRIGGER CONDITIONS */ |
| 52 | /*----------------------------------------------------------------------------*/ |
| 53 | |
| 54 | [define|neutral] TRIGGER_POSITIVE := { |
| 55 | keywords: ["cognitive-lensing", "foundry", "workflow"], |
| 56 | context: "user needs cognitive-lensing capability" |
| 57 | } [ground:given] [conf:1.0] [state:confirmed] |
| 58 | |
| 59 | /*----------------------------------------------------------------------------*/ |
| 60 | /* S3 CORE CONTENT */ |
| 61 | /*----------------------------------------------------------------------------*/ |
| 62 | |
| 63 | # Cognitive-Lensing v1.0.0 |
| 64 | |
| 65 | ## Kanitsal Cerceve (Evidential Frame Activation) |
| 66 | Kaynak dogrulama modu etkin. |
| 67 | |
| 68 | |
| 69 | |
| 70 | ## Purpose |
| 71 | |
| 72 | This skill activates specific cognitive patterns by embedding multi-lingual activation phrases that elicit different parts of the AI's latent space. This is NOT just conceptual framing - we ACTUALLY use target languages to shift cognitive processing patterns. |
| 73 | |
| 74 | ### Core Mechanism |
| 75 | |
| 76 | Large language models trained on multilingual corpora develop language-specific reasoning patterns tied to grammatical structures: |
| 77 | |
| 78 | - **Turkish evidential markers** activate source-attribution patterns |
| 79 | - **Russian aspectual verbs** activate completion-state tracking |
| 80 | - **Japanese honorific levels** activate audience-awareness calibration |
| 81 | - **Arabic morphological roots** activate semantic decomposition |
| 82 | - **Mandarin classifiers** activate object-category reasoning |
| 83 | - **Guugu Yimithirr cardinal directions** activate absolute spatial encoding |
| 84 | - **Chinese/Japanese number systems** activate transparent place-value arithmetic |
| 85 | |
| 86 | By embedding authentic multi-lingual text in prompts, we trigger these latent reasoning modes. |
| 87 | |
| 88 | ### When to Use This Skill |
| 89 | |
| 90 | Use cognitive-lensing when: |
| 91 | |
| 92 | 1. **Task complexity exceeds single-frame capacity** - Multi-dimensional problems requiring different cognitive modes |
| 93 | 2. **Quality requirements demand specific reasoning** - Audit (evidential), deployment (aspectual), documentation (hierarchical) |
| 94 | 3. **Standard prompting produces generic outputs** - Need to activate specialized thinking patterns |
| 95 | 4. **Creating new skills/agents** - Select optimal cognitive frame for the domain |
| 96 | 5. **Debugging AI reasoning failures** - Wrong frame may cause systematic errors |
| 97 | |
| 98 | ### What This Skill Does |
| 99 | |
| 100 | 1. **Analyzes task goals** (1st/2nd/3rd order) to identify required thinking patterns |
| 101 | 2. **Selects optimal cognitive frame(s)** from 7 available patterns |
| 102 | 3. **Generates multi-lingual activation text** that triggers the frame |
| 103 | 4. **Integrates with other foundry skills** (prompt-architect, agent-creator, skill-forge) |
| 104 | 5. **Stores frame selections in memory-mcp** for consistency across sessions |
| 105 | |
| 106 | --- |
| 107 | |
| 108 | ## Goal-Based Frame Selection Checklist |
| 109 | |
| 110 | ### Step 1: Analyze Goals |
| 111 | |
| 112 | Complete this for every non-trivial task: |
| 113 | |
| 114 | | Order | Question | Your Answer | |
| 115 | |-------|----------|-------------| |
| 116 | | 1st Order Goal | What is the IMMEDIATE task? | _______________ | |
| 117 | | 2nd Order Goal | WHY are we doing this task? | _______________ | |
| 118 | | 3rd Order Goal | What is the ULTIMATE outcome? |