Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill combinatorial-creativitygit clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engineWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/combinatorial-creativity)<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/combinatorial-creativity"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/combinatorial-creativity/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/combinatorial-creativity"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/combinatorial-creativity.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 142 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00037 | $0.02034 |
| Opus 5 | $0.00018 | $0.01017 |
| Sonnet 5 | $0.00007 | $0.00407 |
| Haiku 4.5 | $0.00004 | $0.00203 |
Grade A, and why
combinatorial-creativity scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Combinatorial Creativity
Produce emergent concepts via concept blending, multi-level bisociation, and function combination (Fauconnier-Turner).
Strategy Routing
| Strategy | Signal Keywords |
|---|---|
| concept-blending | blend, Fauconnier, Turner, 4-space, input space, generic space, blended space |
| multi-level-bisociation | bisociation, abstraction levels, multi-level, collision, Koestler |
| design-space-exploration | parametric, constraint satisfaction, combinatorial search, design space |
| function-combination | TRIZ, function, recombination, redistribution, function model |
| emergent-property-hunting | emergence, non-additive, synergy, novel property, combination effect |
Manifest
Strategies
| Strategy | Description |
|---|---|
| concept-blending | Fauconnier-Turner 4-space model: Generic + Input1 + Input2 → Blended Space |
| multi-level-bisociation | Simultaneous concept collision at multiple abstraction levels |
| design-space-exploration | Parametric variation + constraint satisfaction combinatorial search |
| function-combination | TRIZ function analysis: function-level recombination and redistribution |
| emergent-property-hunting | Seek properties that emerge from combination (non-additive) |
Tactics
| Tactic | Description |
|---|---|
| combination-mapping | Systematically enumerate parameter dimensions and generate viable combinations (shared) |
| blend-construction | Construct complete 4-space blends with emergent structure |
| emergence-detection | Detect and validate emergent properties from combinations |
SOPs
| SOP | Description |
|---|---|
| input-space-construction | Build input spaces for two source concepts |
| generic-space-extraction | Extract shared abstract structure from two input spaces |
| blend-composition | Compose new connections in blended space |
| blend-completion | Complete blend with background knowledge |
| blend-elaboration | Run blend as mental simulation |
| vital-relation-mapping | Map 15 vital relations between concepts |
| abstraction-ladder | Perform bisociation at multiple abstraction levels |
| function-redistribution | Redistribute functions across different components |
| emergent-property-identification | Identify non-additive properties from combinations |
| combinatorial-synthesis | Synthesize all combinatorial creativity outputs |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 192 lines · 37 tokens per session scan A 3996210ca6c7
combinatorial-creativity is a skill published in the GitHub repository yogsoth-ai/de-anthropocentric-research-engine (464 stars, last pushed today), licensed Apache-2.0. It adds 37 tokens to every session and 2,034 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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