900+ pure-markdown skills for autonomous AI research, organized as 9 freely-composable packages over a 4-layer hierarchy (Campaign → Strategy → Tactic → SOP). Non-linear orchestration with backtracking, 6 MCP integrations. The AI is the researcher — you set the direction.
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
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.
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
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.
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
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.
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
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.
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
The optimizer brain for the ladder-foundry pretraining loop. Runs the two-level nested batch loop, delegates gating to gateeval, attributes a failing batch to one weight (attribute-first), and recovers from disk after compaction. Control flow is fully scripted; only the backprop attribution is a judgment call.
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
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.
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Tactic: Label every sentence of one paper with its rhetorical role using Argumentative Zoning. Use when fixed rhetorical labels and cross-paper alignment matter.
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Judge, per atomic content unit, whether a target text (summary, abstract, or other candidate text) contains it — binary present/absent (ACU) or ternary support/partialsupport/notsupport (Nugget), per caller's value domain. Use this after atomic-unit-writing has produced the reference units, as the matching step before…
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Aggregate per-unit ACU/Nugget match judgments into a final recall score — normalized length-penalized recall for ACU, or Vstrict/Astrict (+ run-level ranking, with an explicit per-topic-unreliability caveat) for Nugget. Use this as the final step of the atomic-unit chain, after atomic-unit-matching; this SOP's…
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Extract (ACU-style) or freshly author (Nugget-style) a list of atomic content units from a paper, optionally tagged vital/okay for importance. Use this as the first step whenever building a reference set of atomic facts for later recall-checking a summary or abstract against the paper — always precedes…
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Judge a three-way SUPPORTS/REFUTES/NOINFO label for an atomic claim, based only on its selected rationale sentences (SciFact's final classification step). Use this after rationale-selection has produced the evidence sentences — this is the terminal step of the SciFact chain, producing the complete (claim, abstract…
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Blind-rewrite a citing sentence (citance) from another paper into a single atomic, independently-verifiable claim (SciFact's annotation protocol) — never looking at the cited paper's content while rewriting. Use this when you have a specific citing sentence and want it decomposed into checkable atomic claims, as the…
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Fold raw signalling-question answers into domain-level judgments for RoB2, ROBINS-I, or QUADAS-2, per each tool's own lookup rules — the first of two aggregation levels these tools define. QUADAS-2 is dual-axis (risk-of-bias AND applicability-concern per domain, D1-D3) and terminates here with no further rollup…
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Run one of the ML/CS reproducibility checklists (ML Reproducibility Checklist, REFORMS, NeurIPS Paper Checklist, Model Cards, Datasheets for Datasets) against a paper as a reader-side audit, producing a category (Yes/No/NA) plus free-text reason per item. Use this whenever the user wants a reproducibility/completeness…
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
(Proposal, unverified) Grade reproducibility-relevant engineering configuration items (hyperparameter search range, compute budget, seed handling, dataset splits) on a complete/partial/none scale, requiring the grader to first define what "complete" means per item before judging against it. Use this after…
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Keshav's first pass over one paper — a 5-10 minute skim of title, abstract, headings, figures, and conclusion only, producing skim notes and a read-deeper judgment. Use this as the first step whenever a paper is being read via the Keshav three-pass method; always precedes second-pass-grasp and never reads section…
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Tactic: Read one paper by Keshav's three-pass method — a shallow skim, a contribution-grasping full read, then a deep virtual re-implementation. Use when the goal is understanding a paper rather than extracting a fixed schema.
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Run a multi-stage extraction cascade (mention detection, document-level coreference clustering, optional saliency judgment, N-ary relation/triple extraction) directly over a paper's full text — covers SciERC, SciREX, and NLP Contribution Graph. Use this whenever cross-sentence or document-level entity/relation…
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Retrieve one specified academic paper (by title, arXiv ID, DOI, URL, or a local .md/.txt/.pdf path the caller already has) and land it on disk as source.md plus a source.meta.json carrying a line-number section index. Checks context/papers/ for an existing copy first; local files and direct PDF URLs are read directly…
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Tactic: Fill a six-slot QALMRI worksheet for one paper: Question, Alternatives, Logic, Method, Results, and Inference. Use for a structured reading worksheet rather than a graded evaluation.
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Produce a six-slot QALMRI worksheet (Question, Alternatives, Logic, Method, Results, Inference) as free-text notes on one paper — a structured note-taking format, not a scored evaluation. Use this whenever the user wants a QALMRI-style reading worksheet for a specific paper.
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Answer a specific question about a paper, grounding the answer in exact quoted evidence spans from the text (QASPER-style question-driven QA with span-level evidence, no schema categorization). Use this whenever the user asks a specific factual question about a paper and wants the answer traceable to exact text spans.
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Run CASP (8 study-type variants), JBI (6 variants), or AMSTAR-2 quality-appraisal checklists — each ending in the tool's own required integrated judgment, not just item tallies. Also runs a proposal "rhetorical-completeness-check" mode (entrymode="completenesscheck") that instead diffs unit-classification's rhetorical…
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Fill a slot-based question-framing schema (PICO, PECO, or SPIDER) from a paper's stated research question. Use this whenever the user wants a paper's research question structured into one of these standard clinical/qualitative-research question frames; this frames what question is being asked, it does not read or…