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 agentmods add skills/npc-worldwide/npcpy/knowledge_sememolution_skillnpx skills add NPC-Worldwide/npcpy --skill knowledge_sememolution_skillgit clone --depth 1 https://github.com/NPC-Worldwide/npcpyWhat 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 | $0.00366 | $0.00987 |
| Opus 5 | $0.00183 | $0.00494 |
| Sonnet 5 | $0.00073 | $0.00197 |
| Haiku 4.5 | $0.00037 | $0.00099 |
Grade A, and why
knowledge_sememolution_skill 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 3d 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
knowledge_sememolution_skill
Skill for population-based Knowledge Graph evolution via Sememolution. Use this when the user wants creative cross-domain synthesis, speculative reasoning, or when a single KG search might be too narrow.
Sememolution maintains a population of KG "individuals". Each individual has its own graph (different facts, concepts, links) and its own genome controlling how it searches and evolves.
Core genome parameters: - lambda_depth — Poisson rate for search traversal depth - lambda_breadth — Poisson rate for search breadth per step - sleep_ops — which refinement ops to apply during sleep - dream_probability — chance of speculative synthesis per cycle
Workflow: 1. Create a population: SememolutionPopulation(model, provider, population_size=100, sample_size=10) 2. Initialize: pop.initialize() 3. Assimilate text: pop.assimilate_text(chunk) — each individual absorbs it differently 4. Sleep cycle: pop.sleep_cycle() — each individual prunes/deepens independently 5. Query and rank: pop.query_and_rank(question) — sample individuals, each searches
its own graph with Poisson-sampled depth/breadth, generates a response,
and responses are ranked. Winners get fitness bumps.
6. Evolve: pop.evolve_generation() — tournament selection, crossover, mutation.
When to use this: - The user asks open-ended "what if" or "how might X relate to Y" questions - You need diverse perspectives on the same knowledge corpus - You want to discover non-obvious connections across domains - Standard KG search returns shallow or overly literal results
Important: this is computationally expensive. Only invoke after checking whether standard keyword/embedding/hybrid search is sufficient.
Inputs
name(default:'task')description(default:'initialize | assimilate | query_rank | evolve | sleep')name(default:'population_size')description(default:'Number of individuals (default 100)')name(default:'query_text')description(default:'Question to ask the population (for query_rank)')
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 57 lines · 366 tokens per session scan A 2901cd5c853d
knowledge_sememolution_skill is a skill published in the GitHub repository NPC-Worldwide/npcpy (1,494 stars, last pushed 8d ago), licensed MIT. It adds 366 tokens to every session and 987 once invoked, about $0.0018 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 2026-08-30.
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