/rhetorical-structure-quality
(Proposal, unverified) Judge whether argumentative relations between unit-classification's rhetorical labels actually hold in a paper (e.g. is an AIM label adequately substantiated by BACKGROUND labels) — a second-order quality judgment over already-classified units, not raw
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill rhetorical-structure-quality --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
/rhetorical-structure-quality
Context preview
The summary Claude sees to decide when to auto-load this skill.
(Proposal, unverified) Judge whether argumentative relations between unit-classification's rhetorical labels actually hold in a paper (e.g. is an AIM label adequately substantiated by BACKGROUND labels) — a second-order quality judgment over already-classified units, not raw
SKILL.md
rhetorical-structure-quality.SKILL.mdname: rhetorical-structure-quality
description: (Proposal, unverified) Judge whether argumentative relations between unit-classification's rhetorical labels actually hold in a paper (e.g. is an AIM label adequately substantiated by BACKGROUND labels) — a second-order quality judgment over already-classified units, not raw text. Use this after unit-classification has labeled a paper's units with a rhetorical/argumentative label set, when the user wants to know if the paper's argument structure is actually sound, not just what role each sentence plays.
version: 1.0.0
category: paper-reading
type: sop
execution: subagent
prompt: ./prompt.md
input: 'classified_units (list of {unit_text, offset, label})'
output: 'argument_relations (list of {label_a, label_b, relation_holds, justification})'
dependencies:
sops:
- spawn-agentRhetorical Structure Quality (Proposal)
Second-order SOP: judges whether rhetorical/argumentative labels (from unit-classification) actually substantiate each other, e.g. AIM vs BACKGROUND. Fills a gap in the evaluative-stance × content-layer matrix (quality-judgment × argumentative-rhetorical-role) that no verified method covers — this is a design proposal, not a transcription of an established methodology.
Execution
Subagent — spawned via spawn-agent skill.
Proposal Status — Read Before Modifying
This SOP has no primary-source precedent (unlike CoreSC/AZ, which it consumes labels from). Its description explicitly says "(Proposal, unverified)" so it is never triggered with the same implied confidence as a verified method. Do not remove that qualifier from the description without re-validating the method against real usage first.
<!-- BEGIN available-tables (generated) -->
Available SOPs
| SOP | When to use | | --- | --- | | spawn-agent | Spawn a customized CC subagent with full MCP tool access. |
<!-- END available-tables (generated) -->
Read more
name: rhetorical-structure-quality
description: (Proposal, unverified) Judge whether argumentative relations between unit-classification's rhetorical labels actually hold in a paper (e.g. is an AIM label adequately substantiated by BACKGROUND labels) — a second-order quality judgment over already-classified units, not raw text. Use this after unit-classification has labeled a paper's units with a rhetorical/argumentative label set, when the user wants to know if the paper's argument structure is actually sound, not just what role each sentence plays.
version: 1.0.0
category: paper-reading
type: sop
execution: subagent
prompt: ./prompt.md
input: 'classified_units (list of {unit_text, offset, label})'
output: 'argument_relations (list of {label_a, label_b, relation_holds, justification})'
dependencies:
sops:
- spawn-agentRhetorical Structure Quality (Proposal)
Second-order SOP: judges whether rhetorical/argumentative labels (from unit-classification) actually substantiate each other, e.g. AIM vs BACKGROUND. Fills a gap in the evaluative-stance × content-layer matrix (quality-judgment × argumentative-rhetorical-role) that no verified method covers — this is a design proposal, not a transcription of an established methodology.
Execution
Subagent — spawned via spawn-agent skill.
Proposal Status — Read Before Modifying
This SOP has no primary-source precedent (unlike CoreSC/AZ, which it consumes labels from). Its description explicitly says "(Proposal, unverified)" so it is never triggered with the same implied confidence as a verified method. Do not remove that qualifier from the description without re-validating the method against real usage first.
<!-- BEGIN available-tables (generated) -->
Available SOPs
| SOP | When to use | | --- | --- | | spawn-agent | Spawn a customized CC subagent with full MCP tool access. |
<!-- END available-tables (generated) -->
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

