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 analogy-extractiongit 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/analogy-extraction)<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/analogy-extraction"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/analogy-extraction/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/analogy-extraction"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/analogy-extraction.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00027 | $0.00376 |
| Opus 5 | $0.00014 | $0.00188 |
| Sonnet 5 | $0.00005 | $0.00075 |
| Haiku 4.5 | $0.00003 | $0.00038 |
Grade A, and why
analogy-extraction 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.
What it actually says
Analogy Extraction
Extract transferable structural principles from source domains.
Stages
Stage 1: Source Identification
Identify candidate source domains using domain-scanning SOP. Evaluate each for structural similarity depth (surface/structural/systemic).
Stage 2: Abstraction
For each promising source, extract the abstract principle using abstraction-extraction or biological-strategy-extraction SOP. Strip domain-specific details to reveal the transferable mechanism.
Stage 3: Structural Mapping
Map source structure to target domain. Identify: corresponding elements, missing elements (gaps), extra elements (opportunities). Use structural-mapping SOP.
Stage 4: Transfer Validation
Assess mapping quality: Is the analogy surface-level (shared labels) or deep (shared relational structure)? Use analogy-quality-assessment SOP. Only deep analogies warrant transfer.
Minimum Yield
| Metric | Floor |
|---|---|
| Source domains scanned | ≥5 |
| Abstractions extracted | ≥3 |
| Structural mappings completed | ≥3 |
| Validated deep analogies | ≥2 |
Available SOPs
| SOP | Role |
|---|---|
| domain-scanning | Stage 1 — find candidate source domains |
| web-search | Stage 1 — supplement domain search |
| paper-overview | Stage 1 — find academic analogies |
| abstraction-extraction | Stage 2 — extract abstract principles |
| structural-mapping | Stage 3 — map source→target structure |
| analogy-quality-assessment | Stage 4 — validate mapping depth |
| novelty-scoring | Post — score resulting ideas |
| idea-synthesis | Post — synthesize into coherent concepts |
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 · 51 lines · 27 tokens per session scan A a349332ad05e
analogy-extraction is a skill published in the GitHub repository yogsoth-ai/de-anthropocentric-research-engine (462 stars, last pushed 2d ago), licensed Apache-2.0. It adds 27 tokens to every session and 376 once invoked, about $0.0001 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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