cranot/super-hermes

prism-reflect

Constraint transparency: analyzes an artifact structurally, then analyzes what its own analysis concealed.

First seen Apr 20, 2026

Installation

$ npx skills add cranot/super-hermes --skill prism-reflect

Summary

  • 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.

Similar popular skills

Related neighbors and high-traction skills in the same topics — useful to compare before installing.

Also in this package

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 424
License LICENSE
Default branch master
Open issues 0
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Version1.0.0
LicenseMIT
Allowed toolsWrite, Read
More 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"}

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 4,502 B
  • docs SUMMARY.md 306 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 74 installs

SKILL.md

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.