Skill
formated-results
Closing skill for the research-executor, loaded as the last step of formated-specs. Summarize the design just produced into one research-result JSON fenced…
Automation
Skill
/analogy-chain
Chain analogies to deeper levels (3-5 layers). Each layer reveals new
Install
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill analogy-chain --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/analogy-chain
Context preview
The summary Claude sees to decide when to auto-load this skill.
Chain analogies to deeper levels (3-5 layers). Each layer reveals new
SKILL.md
analogy-chain.SKILL.mdname: analogy-chain description: Chain analogies to deeper levels (3-5 layers). Each layer reveals new aspects and insights not visible at the surface. execution: subagent prompt: ./prompt.md input: initial_analogy (string) dependencies: sops: - spawn-agent
Analogy Chain
Chain analogies to deeper levels (3-5 layers).
Execution
Subagent — spawned via subagent-spawning/spawn-agent skill.
Why Subagent
Analogy chaining requires sustained deepening of a single thread without distraction. Each layer builds on the previous, requiring unbroken focus on progressive abstraction and re-concretization.
<!-- BEGIN available-tables (generated) -->
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use | | --- | --- | | spawn-agent | Spawn a customized CC subagent with full MCP tool access. Used by SOPs that declare execution: subagent. |
<!-- END available-tables (generated) -->
Ships withde-anthropocentric-research-engine
The complete research orchestration system for AI-native science. What It Does Design Philosophy Architecture (v3.2.2) Quick Start Configuration Roadmap License DARE is not a tool that helps you do research. It is the researcher.
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Stars
36
Forks
Active
Maintenance
HTML
Language
Apache-2.0
License
3d ago
Last commit
7mo ago
Created
Repo: yogsoth-ai/de-anthropocentric-research-engine
Other skills on de-anthropocentric-research-engine.
Skill
formated-specs
Spec-slot skill for the research-executor. Emit the 4-layer DARE orchestration of the assigned topic as one research-graph JSON fenced block in your reply.…
Skill
injection-fidelity
Loss-1 judge (codex role). Given one sample's de-identified dialogue and its PolicyCard, decide axis-by-axis whether the user-simulator enacted the card's…
Skill
ladder-quality-order
Loss-2 judge (codex role). Over one topic's 6 shuffled research-design samples, pairwise-rank by quality using the D1–D5 standard. Emit the pairwise log; the…
Skill
optimization-loop
The optimizer brain for the ladder-foundry pretraining loop. Runs the two-level nested batch loop, delegates gating to gate_eval, attributes a failing batch to…
Skill
acu-nugget-recall
Tactic: Extract atomic units from one paper and score how much of a caller-supplied summary covers. Use for ACU-style binary or Nugget-style ternary recall…