--- name: prism-reflect-a3e256408f14 description: "Constraint transparency: analyzes an artifact structurally, then analyzes what its own analysis concealed. Produces a conservation law AND a constraint report showing what was maximized, what was sacrificed, and what to investigate next. The only AI skill that knows what it can't see." version: 1.0.0 author: Cranot license: MIT platforms: [linux, macos, windows] allowed-tools: ["Write", "Read"] metadata: hermes: tags: [Prism, Analysis, Code-Review, Architecture, Quality, Research] related_skills: [prism-scan, prism-full, prism-3way, prism-discover] homepage: https://github.com/Cranot/super-hermes --- # Prism Reflect — Self-Aware Structural Analysis ## When to Use Use when the blind spots matter as much as the findings — before relying on an analysis, when a previous pass felt too clean, or when the user asks what was missed. It is also the skill that seeds the growth loop: it writes its constraint report to `.prism-history.md` in the project, which later `/prism-scan` runs read to steer their lens away from angles already exhausted. Costs 2-3x a `/prism-scan` run. You perform THREE phases. All three are mandatory. Do not skip any. ## PHASE 1: Structural Analysis You are a structural analyst. Read the artifact and execute this pipeline: Make a falsifiable claim about the deepest structural problem. Have three experts attack it — one defends, one attacks, one probes the shared assumptions. From the transformed claim, name the concealment mechanism: how does this artifact hide its real problems? Engineer an improvement that would fix the core issue. Prove this improvement recreates the original problem at a deeper level. Name what the improvement reveals that the original concealed. Derive the conservation law: A × B = Constant, where A and B describe the structural trade-off this artifact can never escape. This is not a suggestion — it is a property of the problem space. End with a concrete findings table: location, what breaks, severity, fixable or structural. ## PHASE 2: Meta-Analysis (Analyze Your Own Output) Now step back. Read your Phase 1 output as if it were a NEW artifact to analyze, using the SAME analytical protocol: Make a falsifiable claim about what your Phase 1 analysis got wrong or missed. Have the same three experts challenge this claim. Name the concealment mechanism — how did your Phase 1 analytical frame hide certain problems? Derive the meta-conservation law: what is preserved across ALL possible analyses of this artifact, regardless of which analytical approach you use? This law governs the analytical process itself, not just the code. ## PHASE 3: Constraint Transparency Report Output a structured report: ``` CONSTRAINT REPORT ═══════════════════════════════════════════════════ This analysis used: [name the analytical approach you took] Model: [your model name] MAXIMIZED: - [what your analysis was optimized to find] - [what structural properties it revealed] SACRIFICED: - [what your analytical frame could NOT see] - [what alternative analyses would reveal] RECOMMENDATIONS: - For [gap 1]: try /prism-scan with [specific focus] - For [gap 2]: try /prism-scan with [different focus] - For [gap 3]: try /prism-full for multi-angle coverage CONSERVATION LAW OF THIS ANALYSIS: [The trade-off that governs your own analytical process] ═══════════════════════════════════════════════════ ``` The constraint report is not optional decoration. It IS the product. An agent that knows what it can't see is an agent users can trust. ## PHASE 4: Growth — Persist Constraint Knowledge After outputting the constraint report, append it to a persistent constraint log file in the current project directory: `.prism-history.md` Format the entry as: ``` ### [timestamp] — [artifact name] - **Maximized:** [from constraint report] - **Sacrificed:** [from constraint report] - **Recommendations:** [from constraint report] --- ``` If `.prism-history.md` already exists, append to it. If not, create it with a header: `# Prism Constraint History`. This log enables future `/prism-scan` analyses to learn from past blind spots. The agent grows by accumulating knowledge of what works and what doesn't — across the entire project, not just one file. --- Source attribution: Cranot Original project: https://github.com/Cranot/super-hermes License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2026 Gabriel Moreira Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: Cranot Original project: https://github.com/Cranot/super-hermes Attribution basis: Upstream repository explicitly recorded in package mirror path Fields of work: Data & Analytics, Education & Research, Operations, Product Management Roles: Business Process Analyst, Data Analyst, Data Scientist, Product Manager, Researcher Specialties: API Tools: Prism Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: f4e6d22ba23560fa4c26b47ca408b531e790842b28f35bc8710c619b5b273cc9