Skill collection
yogsoth-ai/de-anthropocentric-research-engine agent skills
- skills
- 12
- GitHub stars
- 505
GitHub description: “A 267-skill research graph in pure markdown — 51 research operations built from 216 single-purpose steps, composed in any order with explicit backtracking. One npx install, no runtime, no MCP bindings. The AI is the researcher; you set the direction.”
- Stars
- 505 (42 forks)
- Licence
- Apache-2.0
- Last push
- Sep 2026
- Created
- Feb 2026
- academic-research
- deep-research
- literature-review
- mcp
- skill
- ai-scientist
- auto-research
- claude-code
- research-agent
- scientific-discovery
- autonomous-research
- research-orchestration
- semantic-scholar
- autoresearch
- codex
- agent-native-research-artifact
Install all skills
npx skills add yogsoth-ai/de-anthropocentric-research-engineAdd --skill <name> for a single skill and -a <agent> to choose the agent (see the agent guides).
Skills in yogsoth-ai/de-anthropocentric-research-engine, ranked
Ranked by score. Sort bymost stars,trending,newest,recently updated
| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | Evaluate a fixed candidate, research path, or portfolio under one explicit scenario using stable criteria and return impact, tradeoffs, and failure triggers. | yogsoth-ai/ | 505 | — | ~465 | Automated safety check: Pass | Apache-2.0 | 11 days ago |
| 2 | Aggregate a candidate, strategy, or portfolio across explicit scenarios under a declared robust-decision rule such as worst-case score, minimax regret, maximin, threshold survival, or pivot-trigger… | yogsoth-ai/ | 505 | — | ~478 | Automated safety check: Pass | Apache-2.0 | 11 days ago |
| 3 | Evaluate the value of staging, deferral, reversible commitment, and information-gathering options under uncertainty; return decision-relevant option value and trigger conditions. | yogsoth-ai/ | 505 | — | ~424 | Automated safety check: Pass | Apache-2.0 | 11 days ago |
| 4 | Move a scientific object up/down in abstraction or narrow/broaden selected scope dimensions (population, mechanism, context, outcome, timeframe, system boundary) until the representation has useful… | yogsoth-ai/ | 505 | — | ~584 | Automated safety check: Pass | Apache-2.0 | 11 days ago |
| 5 | Run structured attack/defense/adjudication over a claim, candidate, criterion set, or current winner. | yogsoth-ai/ | 505 | — | ~1.3k | Automated safety check: Pass | Apache-2.0 | 11 days ago |
| 6 | Aggregate criterion or comparison results into an ordered recommendation under an explicit rule. | yogsoth-ai/ | 505 | — | ~561 | Automated safety check: Pass | Apache-2.0 | 11 days ago |
| 7 | Abstract relational structure from source domains, map it to the target, validate depth, and instantiate transferable mechanisms. | yogsoth-ai/ | 505 | — | ~633 | Automated safety check: Pass | Apache-2.0 | 11 days ago |
| 8 | Characterize what blocks a research target: readiness dimensions, obstacles, bottlenecks, resource gaps, causal constraints, dependencies, conflicts, removability, and mitigation pathways. | yogsoth-ai/ | 505 | — | ~3.6k | Automated safety check: Pass | Apache-2.0 | 11 days ago |
| 9 | Interpret completed experimental outputs after host/runtime execution using pre-declared statistical tests, effect/uncertainty estimates, reproducibility checks, and calibrated synthesis. | yogsoth-ai/ | 505 | — | ~732 | Automated safety check: Pass | Apache-2.0 | 11 days ago |
| 10 | Construct and compare plausible future/competitive/temporal/stress scenarios and test whether the research path remains robust across them. | yogsoth-ai/ | 505 | — | ~853 | Automated safety check: Pass | Apache-2.0 | 11 days ago |
| 11 | Identify clinical, methodological, and statistical heterogeneity sources and prioritize subgroup/meta-regression/outlier investigation. | yogsoth-ai/ | 505 | — | ~446 | Automated safety check: Pass | Apache-2.0 | 11 days ago |
| 12 | Analyze how conclusions/performance change across scale and identify regime shifts, saturation, power-law/log-law behavior, or frontier transitions. | yogsoth-ai/ | 505 | — | ~502 | Automated safety check: Pass | Apache-2.0 | 11 days ago |
Questions, answered from the data.
What is the best skill in yogsoth-ai/de-anthropocentric-research-engine?
Evaluate Scenario Impact from yogsoth-ai/de-anthropocentric-research-engine ranks first of the 12 skills in yogsoth-ai/de-anthropocentric-research-engine listed here, with the highest score: its repository has 505 GitHub stars, its SKILL.md loads about 465 tokens and it passes the automated safety check with no findings. Next come Evaluate Scenario Robustness and Evaluate Optionality.
Are the skills in yogsoth-ai/de-anthropocentric-research-engine official?
None yet. All 12 skills in yogsoth-ai/de-anthropocentric-research-engine listed here come from community repositories; a skill counts as official when the product's own GitHub organization publishes it.
How do I install all skills from yogsoth-ai/de-anthropocentric-research-engine?
Run npx skills add yogsoth-ai/de-anthropocentric-research-engine in your project: the open-source skills CLI installs the repository's skills into your coding agent's skills folder. To install a single skill, open its page here for the exact command.
How are these skills ranked?
By Skill Navigator score, which combines the GitHub stars of the skill's repository (shared across that repo's skills and discounted for large collections), how many other GitHub owners carry a copy of the skill, and automated SKILL.md quality checks, minus penalties for safety-check warnings and for each further skill from the same repository. Skills that fail the safety check are not listed.