/campaign-selection
Structured questioning SOP to determine which campaigns to include, emphasize,
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill campaign-selection --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
/campaign-selection
Context preview
The summary Claude sees to decide when to auto-load this skill.
Structured questioning SOP to determine which campaigns to include, emphasize,
SKILL.md
campaign-selection.SKILL.mdname: campaign-selection
description: Structured questioning SOP to determine which campaigns to include, emphasize,
or skip. Used during spec generation.
execution: sequential
Campaign Selection
Ask the user 2-3 questions about which campaigns to include in the research pipeline.
Context
Before asking, you have already read `research-catalog` and know all available campaigns. Present the default pipeline as a starting point.
Questions (select 2-3 most relevant)
1. **Default Pipeline Review**
- Present the 7-stage default pipeline:
1. Knowledge Acquisition (lit-survey)
2. Deep Insight (gap-analysis + insight)
3. Hypothesis Formation
4. Creative Ideation (2-3 campaigns)
5. Convergence (scoring + steel-manning)
6. Stress Test (red-teaming + failure-anticipation)
7. Experiment Design- "Does this pipeline fit your needs, or would you adjust it?"
- Options: (A) Looks good as-is (B) I want to skip some stages (C) I want to emphasize certain stages (D) I have a different structure in mind
2. **Emphasis Selection** (if user wants to emphasize)
- "Which stages should get extra depth?"
- Options: list the 7 stages, allow multi-select
3. **Ideation Campaign Preference** (if reaching ideation stage)
- "For creative ideation, any preference on approach?"
- Options: (A) Let CC choose based on topic (B) I want cross-domain/biomimicry focus (C) I want systematic methods (TRIZ/morphological) (D) I want divergent methods (SCAMPER/lateral)
Rules
- Ask ONE question at a time
- Default pipeline is the starting assumption — user only needs to specify deviations
- Record selections for pipeline composition
Read more
name: campaign-selection description: Structured questioning SOP to determine which campaigns to include, emphasize, or skip. Used during spec generation. execution: sequential
Campaign Selection
Ask the user 2-3 questions about which campaigns to include in the research pipeline.
Context
Before asking, you have already read `research-catalog` and know all available campaigns. Present the default pipeline as a starting point.
Questions (select 2-3 most relevant)
1. **Default Pipeline Review**
- Present the 7-stage default pipeline:
1. Knowledge Acquisition (lit-survey)
2. Deep Insight (gap-analysis + insight)
3. Hypothesis Formation
4. Creative Ideation (2-3 campaigns)
5. Convergence (scoring + steel-manning)
6. Stress Test (red-teaming + failure-anticipation)
7. Experiment Design- "Does this pipeline fit your needs, or would you adjust it?"
- Options: (A) Looks good as-is (B) I want to skip some stages (C) I want to emphasize certain stages (D) I have a different structure in mind
2. **Emphasis Selection** (if user wants to emphasize)
- "Which stages should get extra depth?"
- Options: list the 7 stages, allow multi-select
3. **Ideation Campaign Preference** (if reaching ideation stage)
- "For creative ideation, any preference on approach?"
- Options: (A) Let CC choose based on topic (B) I want cross-domain/biomimicry focus (C) I want systematic methods (TRIZ/morphological) (D) I want divergent methods (SCAMPER/lateral)
Rules
- Ask ONE question at a time
- Default pipeline is the starting assumption — user only needs to specify deviations
- Record selections for pipeline composition
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.
Repo: yogsoth-ai/de-anthropocentric-research-engine
Other skills on de-anthropocentric-research-engine.
- /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 block in your reply. Do not execute the research.
Open 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. Replaces the generic spec-writing step.
Open 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 per-axis pressure. Judge enactment of the card, never whether the research is good.
Open 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 harness computes the order and the ladder verdicts. Judge quality difference, never against academic standards.
Open 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 one weight (attribute-first), and recovers from disk after compaction. Control flow is fully scripted; only the
Open 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 checks; cannot run without a target summary.
Open skill

