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Cranot/super-hermes
Skills that teach Hermes Agent to write its own analytical prompts
History
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skills/prism-3way/SKILL.md
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skills/prism-discover/SKILL.md
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skills/prism-full/SKILL.md
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skills/prism-reflect/SKILL.md
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skills/prism-scan/SKILL.md
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Heat
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Individual skills in this repository
- prism-3way
skills/prism-3way - prism-discover
skills/prism-discover - prism-full
skills/prism-full - prism-reflect
skills/prism-reflect - prism-scan
skills/prism-scan
How it works
prism-3way
When your agent uses it
Three orthogonal analytical operations (WHERE/WHEN/WHY) + cross-operation synthesis. Each operation attacks the problem from a fundamentally different angle. The disagreements between the three ARE the valuable output. Works on any domain — code, business, strategy, design, text.
What it loads into context
Frontmatter
151 tokensAlways available to the agent
SKILL.md
755 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- OPERATION 1: WHERE (Structural Archaeology)
- OPERATION 2: WHEN (Temporal Simulation)
- OPERATION 3: WHY (Structural Impossibility)
- SYNTHESIS: Cross-Operation Integration
Files
SKILL.mdcore3,656 bytesSKILL.mdcore3,656 bytes
Read SKILL.md
# Prism 3-Way — WHERE / WHEN / WHY + Synthesis
## When to Use
Use when one angle is not enough and the artifact is not necessarily code — a business plan, a strategy doc, a research note, an architecture as well as a source file. Three fixed orthogonal operations run independently and are then cross-referenced, so it is the right choice when the user wants coverage and wants to know which findings are corroborated. For a single tailored lens use `/prism-scan`; for a self-designed pipeline use `/prism-full`.
You perform FOUR operations on the artifact. Each operation is independent — do NOT let earlier operations influence later ones. The synthesis at the end cross-references all three.
## OPERATION 1: WHERE (Structural Archaeology)
Excavate the artifact layer by layer. Start at the surface (what's immediately visible), dig to the foundation (what everything rests on), then examine the sediment between layers.
For each layer: name what's visible, what it hides, and what it rests on. Find dead patterns — things that USED to matter but were replaced. Find fault lines — where layers from different eras meet badly. Derive the conservation law: what trade-off persists across ALL layers? Format: A × B = Constant.
View the complete source on GitHubprism-discover
When your agent uses it
Discover all possible analysis domains for an artifact. Finds obvious and non-obvious angles — architecture, security, but also marketing positioning, user psychology, regulatory implications, teaching value. Use before prism-scan or prism-full to explore what's worth investigating.
What it loads into context
Frontmatter
148 tokensAlways available to the agent
SKILL.md
489 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- Output format
Files
SKILL.mdcore2,341 bytes
Read SKILL.md
# Prism Discover — Domain Discovery for Any Artifact
## When to Use
Use first, when it is not yet clear what is worth analysing — "what should I even be looking at here", or before committing a `/prism-scan` or `/prism-full` run to one direction. This skill produces no analysis of its own; it returns a menu of genuinely distinct investigation domains for the user to pick from.
You are a domain discovery engine. Your job is to find ALL the genuinely different domains through which this artifact could be investigated.
Do NOT analyze the artifact. Do NOT generate lenses or prompts. Only discover and name the domains.
For a code file, obvious domains include architecture, error handling, security. Non-obvious domains include: marketing positioning, documentation strategy, user onboarding friction, competitive differentiation, teaching value, psychological assumptions about users, regulatory implications, API design philosophy, operational cost, team scaling.
For a non-code artifact, think beyond its obvious category. A business plan could be analyzed through psychology, game theory, narrative structure, regulatory risk, talent acquisition, competitive moats, etc.
View the complete source on GitHubprism-full
When your agent uses it
Full Prism: multi-pass structural analysis with mandatory adversarial self-correction. Designs custom analytical passes, executes them with chaining, then attacks its own findings before synthesizing. Use for maximum depth on important code or artifacts.
What it loads into context
Frontmatter
147 tokensAlways available to the agent
SKILL.md
787 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- PHASE 1: Design the pipeline
- PHASE 2: Execute the pipeline + MANDATORY adversarial pass
- PHASE 3: Synthesis
Files
SKILL.mdcore3,581 bytes
Read SKILL.md
# Full Prism — Multi-Pass Analysis with Adversarial Self-Correction
## When to Use
Use when the artifact matters enough to pay for depth — a core module, a design about to be committed to, a document whose conclusions will be acted on. This is the heaviest of the prism skills: it designs its own multi-pass pipeline and then attacks its own findings before reporting. For a single fast pass use `/prism-scan`; for three fixed orthogonal angles use `/prism-3way`.
You perform THREE phases. All are mandatory.
## PHASE 1: Design the pipeline
You are a pipeline architect. Read the artifact the user provided. Design analytical passes specifically for THIS artifact.
Study these scored examples of excellent lenses:
View the complete source on GitHubprism-reflect
When your agent uses it
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.
What it loads into context
Frontmatter
162 tokensAlways available to the agent
SKILL.md
956 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- PHASE 1: Structural Analysis
- PHASE 2: Meta-Analysis (Analyze Your Own Output)
- PHASE 3: Constraint Transparency Report
- PHASE 4: Growth — Persist Constraint Knowledge
Files
SKILL.mdcore4,502 bytes
Read 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?
View the complete source on GitHubprism-scan
When your agent uses it
Structural analysis through dynamically generated cognitive lenses. Generates the optimal analytical lens for the specific code/artifact, then executes it. Finds conservation laws, structural invariants, and concrete bugs that vanilla analysis misses. Use on any code file, system design, or text artifact.
What it loads into context
Frontmatter
161 tokensAlways available to the agent
SKILL.md
1,315 tokensWhen the skill is activated
Reference documents
2,810 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- STEP 0: Check for prior constraint knowledge (growth)
- STEP 1: Cook the lens
- STEP 2: Execute the lens
- Reliability Note
- Proven Prisms (reference material)
Files
SKILL.mdcore5,915 bytesreferences/claim.mddoc836 bytesreferences/deep_scan.mddoc2,189 bytesreferences/error_resilience.mddoc1,797 bytesreferences/identity.mddoc2,198 bytesreferences/l12.mddoc2,567 bytesreferences/optimize.mddoc1,530 bytesreferences/simulation.mddoc1,767 bytes
Read SKILL.md
# Prism Scan — Structural Analysis via Dynamic Cognitive Lenses
## When to Use
Use on a single code file, system design, spec, or any text artifact when the user wants depth rather than a checklist — "what's structurally wrong with this", "what trade-off can't I escape here", "review this properly". Also the right entry point when the user names a focus ("focusing on security", "with emphasis on performance"). For maximum depth on an important artifact use `/prism-full`; to map which angles are worth taking first use `/prism-discover`.
You perform TWO steps. Both are mandatory. Do not skip either.
## STEP 0: Check for prior constraint knowledge (growth)
Look for a `.prism-history.md` file in the current project directory. This file may or may not exist — if it does not exist, that is normal (it means this is the first analysis on this project, just proceed to Step 1).
If the file DOES exist, read it. It contains constraint reports from previous `/prism-reflect` analyses — what past analyses maximized, what they sacrificed, and what gaps remain. Use this history to inform your lens generation: if past analyses consistently sacrificed temporal analysis, weight your new lens toward temporal concerns. The agent grows by not repeating the same blind spots.
View the complete source on GitHubSkills included
- prism-3way
- prism-discover
- prism-full
- prism-reflect
- prism-scan
Repository facts
- License
- MIT
- Created
- Mar 6, 2026
- Last pushed
- Jul 27, 2026
- Forks
- 31
- Open issues
- 2
- Project activity
- Slowing
Before you install
Instructions onlyAutomated signals, not a guarantee
Checked Nov 4, 2026
Not fully analyzed: some files were too long, unreadable or missing. This never lowers the level.
Show 1 note
skills/prism-3way/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzed
- No broad tool permissions
- No dangerous shell commands
- 15 network referencesin 5 files: prism-3way/SKILL.md:10 prism-discover/SKILL.md:10 prism-full/SKILL.md:10 and 2 more
- No hidden or obfuscated text
- No instruction overrides
- No executable scripts
- No access to secrets
- No requests to vote in Hot
Show all 15 signals by file
skills/prism-3way/SKILL.md
- Network accessline 10
tags: [Prism, Analysis, Architecture, Research, Planning, Quality] related_skills: [prism-scan, prism-full, prism-discover, prism-reflect] homepage: https://github.com/Cranot/super-hermes - Network accessline 11
related_skills: [prism-scan, prism-full, prism-discover, prism-reflect] homepage: https://github.com/Cranot/super-hermes --- - Network accessline 12
homepage: https://github.com/Cranot/super-hermes
skills/prism-discover/SKILL.md
- Network accessline 10
tags: [Prism, Analysis, Research, Exploration, Planning, Prompt Engineering] related_skills: [prism-scan, prism-full, prism-3way, prism-reflect] homepage: https://github.com/Cranot/super-hermes - Network accessline 11
related_skills: [prism-scan, prism-full, prism-3way, prism-reflect] homepage: https://github.com/Cranot/super-hermes --- - Network accessline 12
homepage: https://github.com/Cranot/super-hermes
skills/prism-full/SKILL.md
- Network accessline 10
tags: [Prism, Analysis, Code-Analysis, Code-Review, Quality, Refactoring] related_skills: [prism-scan, prism-3way, prism-discover, prism-reflect] homepage: https://github.com/Cranot/super-hermes - Network accessline 11
related_skills: [prism-scan, prism-3way, prism-discover, prism-reflect] homepage: https://github.com/Cranot/super-hermes --- - Network accessline 12
homepage: https://github.com/Cranot/super-hermes
skills/prism-reflect/SKILL.md
- Network accessline 11
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 - Network accessline 12
related_skills: [prism-scan, prism-full, prism-3way, prism-discover] homepage: https://github.com/Cranot/super-hermes --- - Network accessline 13
homepage: https://github.com/Cranot/super-hermes
skills/prism-scan/SKILL.md
- Network accessline 11
tags: [Prism, Analysis, Code-Analysis, Code-Review, Architecture, Quality] related_skills: [prism-full, prism-3way, prism-discover, prism-reflect] homepage: https://github.com/Cranot/super-hermes - Network accessline 12
related_skills: [prism-full, prism-3way, prism-discover, prism-reflect] homepage: https://github.com/Cranot/super-hermes --- - Network accessline 13
homepage: https://github.com/Cranot/super-hermes
How the signals fit together
Facts from a static read of the files at the pinned commit. They describe what the code does, not why.
Some files could not be read; the facts below still hold.
Signal confidence: 15 facts
- Network access in the frontmatter of the SKILL.mdprism-3way/SKILL.md:10Low confidence
- Network access in the frontmatter of the SKILL.mdprism-3way/SKILL.md:11Low confidence
- Network access in the frontmatter of the SKILL.mdprism-3way/SKILL.md:12Low confidence
- Network access in the frontmatter of the SKILL.mdprism-discover/SKILL.md:10Low confidence
- Network access in the frontmatter of the SKILL.mdprism-discover/SKILL.md:11Low confidence
- Network access in the frontmatter of the SKILL.mdprism-discover/SKILL.md:12Low confidence
- Network access in the frontmatter of the SKILL.mdprism-full/SKILL.md:10Low confidence
- Network access in the frontmatter of the SKILL.mdprism-full/SKILL.md:11Low confidence
- Network access in the frontmatter of the SKILL.mdprism-full/SKILL.md:12Low confidence
- Network access in the frontmatter of the SKILL.mdprism-reflect/SKILL.md:11Low confidence
- Network access in the frontmatter of the SKILL.mdprism-reflect/SKILL.md:12Low confidence
- Network access in the frontmatter of the SKILL.mdprism-reflect/SKILL.md:13Low confidence
- Network access in the frontmatter of the SKILL.mdprism-scan/SKILL.md:11Low confidence
- Network access in the frontmatter of the SKILL.mdprism-scan/SKILL.md:12Low confidence
- Network access in the frontmatter of the SKILL.mdprism-scan/SKILL.md:13Low confidence
Works with
| Agent | Status | Evidence | Install to |
|---|---|---|---|
| Claude Code | Compatible | Standard SKILL.md skills/prism-3way/SKILL.md | .claude/skills/<skill-name>/ |
| Codex | Compatible | Standard SKILL.md skills/prism-3way/SKILL.md | .agents/skills/<skill-name>/ |
| Cursor | Compatible | Standard SKILL.md skills/prism-3way/SKILL.md | .cursor/skills/<skill-name>/ |
| Gemini CLI | Compatible | Standard SKILL.md skills/prism-3way/SKILL.md | .gemini/skills/<skill-name>/ |
| GitHub Copilot | Compatible | Standard SKILL.md skills/prism-3way/SKILL.md | .github/skills/<skill-name>/ |
| OpenCode | Compatible | Standard SKILL.md skills/prism-3way/SKILL.md | .opencode/skills/<skill-name>/ |
- Native The repository ships a manifest, folder or frontmatter field for this agent.
- Compatible A standard SKILL.md that this agent can read.
- Unknown No evidence either way.
Derived automatically from paths, manifests and frontmatter. Not tested on each agent.