HIPAA Safe Harbor Coverage Audit
maziyarpanahi/openmed
Checks OpenMed de-identified clinical text against the 18 HIPAA Safe Harbor identifier categories and reports gaps and residual re-identification risk.
Agent skill
by yogsoth-ai in yogsoth-ai/de-anthropocentric-research-engine
Characterize what blocks a research target: readiness dimensions, obstacles, bottlenecks, resource gaps, causal constraints, dependencies, conflicts, removability, and mitigation pathways.
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-constraints-readiness -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install yogsoth-ai/de-anthropocentric-research-engine analyze-constraints-readiness --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engine.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/analyze-constraints-readiness .claude/skills/analyze-constraints-readiness && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "analyze-constraints-readiness" agent skill from https://github.com/yogsoth-ai/de-anthropocentric-research-engine/tree/main/skills/analyze-constraints-readiness into .claude/skills/analyze-constraints-readiness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-constraints-readiness", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/yogsoth-ai/de-anthropocentric-research-engine/tree/main/skills/analyze-constraints-readinessType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-constraints-readiness -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install yogsoth-ai/de-anthropocentric-research-engine analyze-constraints-readiness --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engine.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/analyze-constraints-readiness .agents/skills/analyze-constraints-readiness && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "analyze-constraints-readiness" agent skill from https://github.com/yogsoth-ai/de-anthropocentric-research-engine/tree/main/skills/analyze-constraints-readiness into .agents/skills/analyze-constraints-readiness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-constraints-readiness", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-constraints-readiness -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install yogsoth-ai/de-anthropocentric-research-engine analyze-constraints-readiness --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engine.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/analyze-constraints-readiness .cursor/skills/analyze-constraints-readiness && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "analyze-constraints-readiness" agent skill from https://github.com/yogsoth-ai/de-anthropocentric-research-engine/tree/main/skills/analyze-constraints-readiness into .cursor/skills/analyze-constraints-readiness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-constraints-readiness", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/yogsoth-ai/de-anthropocentric-research-engine.git --path skills/analyze-constraints-readiness--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-constraints-readiness -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install yogsoth-ai/de-anthropocentric-research-engine analyze-constraints-readiness --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engine.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/analyze-constraints-readiness .gemini/skills/analyze-constraints-readiness && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "analyze-constraints-readiness" agent skill from https://github.com/yogsoth-ai/de-anthropocentric-research-engine/tree/main/skills/analyze-constraints-readiness into .gemini/skills/analyze-constraints-readiness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-constraints-readiness", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install yogsoth-ai/de-anthropocentric-research-engine analyze-constraints-readinessInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-constraints-readiness -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engine.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/analyze-constraints-readiness .github/skills/analyze-constraints-readiness && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "analyze-constraints-readiness" agent skill from https://github.com/yogsoth-ai/de-anthropocentric-research-engine/tree/main/skills/analyze-constraints-readiness into .github/skills/analyze-constraints-readiness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-constraints-readiness", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-constraints-readiness -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install yogsoth-ai/de-anthropocentric-research-engine analyze-constraints-readiness --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engine.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/analyze-constraints-readiness .opencode/skills/analyze-constraints-readiness && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "analyze-constraints-readiness" agent skill from https://github.com/yogsoth-ai/de-anthropocentric-research-engine/tree/main/skills/analyze-constraints-readiness into .opencode/skills/analyze-constraints-readiness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-constraints-readiness", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
analyze-constraints-readinessCharacterize what blocks a research target: readiness dimensions, obstacles, bottlenecks, resource gaps, causal constraints, dependencies, conflicts, removability, and mitigation pathways.
Analyze Constraints Readiness is an agent skill from yogsoth-ai/de-anthropocentric-research-engine. Characterize what blocks a research target: readiness dimensions, obstacles, bottlenecks, resource gaps, causal constraints, dependencies, conflicts, removability, and mitigation pathways. Depth selects lightweight triage, readiness assessment, or causal/TOC-style constraint analysis.
Its SKILL.md is about 3.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Legal & Compliance, covering Audit readiness. The repository describes itself as: 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… The licence is Apache-2.0.
4 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit bdb3524. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Analyze Constraints Readiness loads about 3.6k tokens when it runs. Until then it costs about 79 tokens; SKILL.md has 1,375 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from yogsoth-ai/de-anthropocentric-research-engine at commit bdb3524, republished under its Apache-2.0 licence (© yogsoth-ai). 1,375 words, ~3,649 tokens.
.claude/skills/analyze-constraints-readiness/SKILL.md (or your agent's skills folder).Assess feasibility and readiness by identifying constraints, resources, dependencies, bottlenecks, and maturation gates.
mode_contracts:
obstacle-triage: &readiness_input
required: [candidate_or_plan, readiness_dimensions]
optional: [resource_estimates, dependencies, assumptions, target_gates]
constraints: [evidence_must_be_attached_to_each_scored_dimension]
readiness-assessment: *readiness_input
resource-envelope: *readiness_input
causal-constraint-analysis: *readiness_input
maturation-path: *readiness_inputDo not perform called SOP operations inline; each loaded SOP owns its contract and thresholds.
classify-constraint to classify each declared constraint.obstacle-triage, readiness-assessment, resource-envelope, causal-constraint-analysis, or maturation-path.score-object to score the selected dimensions with evidence. You MUST load skill identify-bottleneck to identify binding constraints and dependencies.assess-removability to test whether binding constraints can be removed. You MUST load skill design-mitigation to design removal or mitigation paths and return a readiness conclusion.
If several feasible responses must be balanced as a joint set, consider portfolio-optimization. If the target goal remains too broad to assess, consider decompose-research-goal. If external change dominates present readiness, consider analyze-future-scenarios. If several candidate paths are ready for comparative selection, rank-candidates may be the better next tactic.obstacle-triage: rapidly enumerate and severity-rank the obstacles that could block the target, preserving evidence status for each one. You MUST load skill identify-obstacles to enumerate the obstacles. You MUST load skill list-undesirable-effects to retain their observed consequences.readiness-assessment: score the required readiness dimensions with supporting evidence and identify the dimensions that keep the target from being ready. You MUST load skill assess-readiness-dimension to assess every required dimension.resource-envelope: estimate time, cost, and personnel bounds from analogies, then flag low-confidence estimates for investigation. You MUST load skill quantify-resource-gap to quantify the gap. You MUST load skill identify-critical-chain to expose the binding resource sequence.causal-constraint-analysis: trace how constraints interact through dependencies and conflicts to identify the binding cause rather than only its symptoms. You MUST load skill trace-causal-chain to trace constraint propagation. You MUST load skill extract-core-conflict to isolate the core conflict. You MUST load skill challenge-assumption to test the assumptions that sustain it.maturation-path: sequence stage gates and milestones that move the target from current readiness to the declared implementation threshold. You MUST load skill project-future-reality to project the proposed path. You MUST load skill apply-stage-gate to apply its stage gates.mode_contracts:
obstacle-triage: &constraint_output
produces: [constraint_register, bottlenecks, mitigation_paths]
delta_fields: [findings, decisions, uncertainties, open_questions, recommended_jumps]
readiness-assessment:
produces: [readiness_profile, bottlenecks]
delta_fields: [findings, decisions, uncertainties, open_questions, recommended_jumps]
resource-envelope:
produces: [resource_envelope, bottlenecks, mitigation_paths]
delta_fields: [findings, decisions, uncertainties, open_questions, recommended_jumps]
causal-constraint-analysis: *constraint_output
maturation-path:
produces: [readiness_profile, resource_envelope, stage_gates, mitigation_paths]
delta_fields: [findings, decisions, uncertainties, open_questions, recommended_jumps]Feasibility, maturity, constraint, resource, and maturation gates use declared dimension/evidence/constraint coverage ratios; record numerator, denominator, batch increment, stopping reason, and source references.
Preserve structural requirements: at least one hard constraint, one removal path per removable constraint, explicit stage gates, and a binding-constraint rule relative to the observed score distribution.
Feasibility dimensions >=5; blockers >=3 per candidate where source protocol applies.
Maturity diagnosis: >=5 dimensions, >=2 evidence items per dimension, >=1 bottleneck.
Constraint identification: >=3 constraints per candidate; >=1 hard constraint; >=1 removal path per removable constraint.
Resource envelope: >=3 dimensions (time, cost, personnel) and >=2 analogies per estimate.
Maturation path: >=3 stage gates and >=2 milestones per stage.
Binding constraint threshold: sensitivity score >2* median.
Do not label a candidate ready with missing evidence, unclassified hard constraints, or an unbounded resource estimate. A conflict with no manageable injection remains blocked.
26 architecture old entries; readiness, feasibility, resource, obstacle, dependency, sensitivity, and maturation families are merged by mode. Missing aliases are listed in log.
Append dimension scores/evidence, constraint IDs, bottleneck rationale, resources, gates, and unresolved conflicts.
| source | source line | kind | source criterion |
|---|---|---|---|
| feasibility-assessment | 42 | numeric-table | \ |
| feasibility-assessment | 75 | numeric | \ |
| feasibility-assessment | 76 | numeric | \ |
| feasibility-assessment | 77 | numeric | \ |
| feasibility-assessment | 78 | numeric | \ |
| maturity-diagnosis | 23 | numeric | \ |
| maturity-diagnosis | 24 | numeric | \ |
| maturity-diagnosis | 25 | numeric | \ |
| maturity-diagnosis | 53 | textual | 1. Identify relevant dimensions for the candidate (minimum: technical, market, regulatory, resource, organizational) |
| maturity-diagnosis | 64 | numeric | overall_readiness: <1-9 TRL scale> |
| constraint-identification | 23 | numeric | \ |
| constraint-identification | 24 | numeric | \ |
| constraint-identification | 25 | numeric | \ |
| constraint-identification | 58 | numeric | 4. For constraints with removability score > 0.3, design removal-path |
| resource-envelope-estimation | 24 | numeric | \ |
| resource-envelope-estimation | 25 | numeric | \ |
| resource-envelope-estimation | 26 | numeric | \ |
| resource-envelope-estimation | 58 | numeric | 3. Identify >= 2 analogous projects and extract their actual resource consumption |
| resource-envelope-estimation | 61 | numeric | 6. Flag any estimates with confidence < 0.5 for further investigation |
| comparative-feasibility-ranking | 16 | textual | Purpose: Produce a defensible ranking of candidates by feasibility. Uses multi-dimensional radar charts to visualize relative strengths and a weighted feasibility index to collapse multiple dimensions into a single comparable score. |
| comparative-feasibility-ranking | 27 | numeric | \ |
| comparative-feasibility-ranking | 28 | numeric | \ |
| comparative-feasibility-ranking | 29 | numeric-table | \ |
| comparative-feasibility-ranking | 58 | numeric | 2. Normalize scores to a common scale (1-9 recommended) |
| maturation-pathway-design | 27 | numeric | \ |
| maturation-pathway-design | 28 | numeric | \ |
| maturation-pathway-design | 29 | numeric-table | \ |
| maturation-pathway-design | 37 | textual | \ |
| maturation-pathway-design | 62 | textual | 2. Define target readiness required for implementation |
| maturation-pathway-design | 76 | textual | target_readiness: <required score> |
| multi-dimensional-readiness-scan | 23 | textual | 3. Bottleneck Identification - Analyze the radar for dimensions significantly below the mean or below required thresholds. Deploy bottleneck-identification SOP on the radar data. |
| multi-dimensional-readiness-scan | 29 | numeric-table | \ |
| multi-dimensional-readiness-scan | 30 | numeric-table | \ |
| multi-dimensional-readiness-scan | 31 | numeric-table | \ |
| multi-dimensional-readiness-scan | 39 | numeric | - Each dimension should have at least 2 evidence items supporting the score |
| multi-dimensional-readiness-scan | 41 | textual | ## Minimum Yield |
| multi-dimensional-readiness-scan | 43 | numeric | - Complete radar with >= 5 dimensions scored |
| constraint-drilling | 26 | numeric | 4. Removal Path Design - For constraints with removability > 0.3, design concrete steps to remove or mitigate them. Deploy removal-path SOP for each removable constraint. |
| constraint-drilling | 32 | numeric-table | \ |
| constraint-drilling | 33 | numeric-table | \ |
| constraint-drilling | 34 | numeric-table | \ |
| constraint-drilling | 35 | numeric-table | \ |
| constraint-drilling | 42 | numeric | - Stage 4 only runs for constraints with removability score > 0.3 |
| constraint-drilling | 45 | textual | ## Minimum Yield |
| constraint-drilling | 47 | numeric | - Classified constraint list with >= 3 constraints identified |
| constraint-drilling | 49 | numeric | - Removal paths for all constraints scoring removability > 0.3 |
| staged-gate-evaluation | 19 | textual | 1. Gate Criteria Definition - Define what must be true for a candidate to pass each gate. Deploy gate-criteria-definition SOP for each stage gate. |
| staged-gate-evaluation | 29 | numeric-table | \ |
| staged-gate-evaluation | 30 | numeric-table | \ |
| staged-gate-evaluation | 31 | numeric-table | \ |
| staged-gate-evaluation | 35 | numeric | - Stage 1 should define >= 3 gates (e.g., concept feasibility, technical feasibility, implementation readiness) |
| staged-gate-evaluation | 42 | textual | ## Minimum Yield |
| constraint-analysis | 44 | textual | ## HARD-GATE |
| constraint-analysis | 46 | textual | Before entering this campaign, the following must be true: |
| constraint-analysis | 78 | textual | ## Budget Gate |
| constraint-analysis | 94 | textual | ## Minimum Yield |
| constraint-analysis | 97 | numeric | - At least 1 binding constraint identified and characterized |
| constraint-analysis | 100 | numeric | - No unresolved conflicts between top-3 constraints |
| resource-constraint | 63 | textual | ## Budget Gate |
| assumption-constraint | 55 | numeric | - Top-5 fragile assumptions with validation paths |
| assumption-constraint | 58 | textual | ## Budget Gate |
| dependency-constraint | 60 | textual | ## Budget Gate |
| conflict-resolution | 66 | textual | ## Budget Gate |
| constraint-tree-building | 25 | textual | - Minimum 5 UDEs for a meaningful tree |
| constraint-tree-building | 42 | numeric | - When to escalate: If >10 UDEs found, prioritize top-5 by severity before tracing |
| constraint-tree-building | 43 | textual | - Quality gate: Every causal link must have a BECAUSE clause (the underlying assumption) |
| sensitivity-ranking | 25 | textual | - Express gaps in comparable units where possible |
| sensitivity-ranking | 43 | numeric | - When to skip: If only 1-2 constraints exist, ranking is trivial |
| sensitivity-ranking | 44 | numeric | - Threshold: Constraints with sensitivity score >2* the median are "binding" |
| constraint-breaking | 26 | textual | - If constraint is not a dilemma, reframe: "We need X" vs "We cannot have X because Y" |
| constraint-breaking | 29 | numeric | - Input: all assumptions from the EC (typically 8-15 assumptions across 4 arrows) |
| constraint-breaking | 35 | textual | - Injection must be: specific, actionable, within our control, and testable |
| constraint-breaking | 36 | numeric | - Generate 2-3 candidate injections |
| constraint-breaking | 43 | textual | - What conditions (prerequisites) must hold? |
Append dimension scores/evidence, constraint IDs, bottleneck rationale, resources, gates, and unresolved conflicts. | constraint-breaking | 54 | numeric | - Success criterion: At least one injection that resolves the conflict with <=2 manageable side effects |
© yogsoth-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/analyze-constraints-readiness of yogsoth-ai/de-anthropocentric-research-engine.
Open the folder on GitHubat commit bdb3524
Analyze Constraints Readiness next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Analyze Constraints Readiness this skillyogsoth-ai/de-anthropocentric-research-engine | 505 | — | ~3.6k | Automated safety check: Pass | Apache-2.0 | |
| HIPAA Safe Harbor Coverage Auditmaziyarpanahi/openmed | 5.5k | — | ~1.7k | Automated safety check: Pass | Apache-2.0 | |
| ISO Standards Readiness EvidenceK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~4.6k | Automated safety check: Notes | MIT | |
| Iso42001Sushegaad/Claude-Skills-Governance-Risk-and-Compliance | 946 | 1 repos | ~3.7k | Automated safety check: Pass | MIT | |
| Fleet Triagegoogle-labs-code/jules-sdk | 137 | — | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| PCI DSS Compliancewshobson/agents | 40k | 11 repos | ~1.9k | Automated safety check: Pass | MIT |
maziyarpanahi/openmed
Checks OpenMed de-identified clinical text against the 18 HIPAA Safe Harbor identifier categories and reports gaps and residual re-identification risk.
K-Dense-AI/scientific-agent-skills
Organizes scope, controlled documents, risk files and traceability into draft evidence for human review against ISO 13485, 14971, 17025 and 15189.
Sushegaad/Claude-Skills-Governance-Risk-and-Compliance
Expert ISO 42001 AI Management System (AIMS) compliance advisor.
google-labs-code/jules-sdk
Cognitive triage of fleet audit findings. An agent skill from google-labs-code/jules-sdk.
wshobson/agents
Reference for building payment systems that meet PCI DSS: the 12 requirements, merchant levels, data that must never be stored, tokenization and encryption.
GRCEngClub/claude-grc-engineering
Builds and deploys a serverless trust center that publishes a company's compliance posture, with gated access to audit reports and an admin dashboard.
yogsoth-ai/de-anthropocentric-research-engine
Evaluate a fixed candidate, research path, or portfolio under one explicit scenario using stable criteria and return impact, tradeoffs, and failure triggers.
yogsoth-ai/de-anthropocentric-research-engine
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/de-anthropocentric-research-engine
Evaluate the value of staging, deferral, reversible commitment, and information-gathering options under uncertainty; return decision-relevant option value and trigger conditions.
yogsoth-ai/de-anthropocentric-research-engine
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/de-anthropocentric-research-engine
Run structured attack/defense/adjudication over a claim, candidate, criterion set, or current winner.
yogsoth-ai/de-anthropocentric-research-engine
Aggregate criterion or comparison results into an ordered recommendation under an explicit rule.
Categories
Characterize what blocks a research target: readiness dimensions, obstacles, bottlenecks, resource gaps, causal constraints, dependencies, conflicts, removability, and mitigation pathways. Analyze Constraints Readiness is an agent skill from yogsoth-ai/de-anthropocentric-research-engine. Characterize what blocks a research target: readiness dimensions, obstacles, bottlenecks, resource gaps, causal constraints, dependencies, conflicts, removability, and mitigation pathways.
Analyze Constraints Readiness fits situations like: tasks that involve Audit readiness.
Run `npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-constraints-readiness -a claude-code`. Or copy the skill folder (skills/analyze-constraints-readiness in yogsoth-ai/de-anthropocentric-research-engine) into .claude/skills/analyze-constraints-readiness in your project. Claude Code loads it when a task matches its description.
Run `npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-constraints-readiness -a codex`. Or copy the skill folder (skills/analyze-constraints-readiness in yogsoth-ai/de-anthropocentric-research-engine) into .agents/skills/analyze-constraints-readiness in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-constraints-readiness -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/analyze-constraints-readiness, .gemini/skills/analyze-constraints-readiness, .github/skills/analyze-constraints-readiness and .opencode/skills/analyze-constraints-readiness in your project.
SKILL.md names no scripts, command-line tools or credentials: Analyze Constraints Readiness is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Analyze Constraints Readiness is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.6k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Analyze Constraints Readiness: HIPAA Safe Harbor Coverage Audit (maziyarpanahi/openmed, 5.5k stars), ISO Standards Readiness Evidence (K-Dense-AI/scientific-agent-skills, 48k stars), Iso42001 (Sushegaad/Claude-Skills-Governance-Risk-and-Compliance, 946 stars) and Fleet Triage (google-labs-code/jules-sdk, 137 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
yogsoth-ai (a GitHub organization) maintains it in yogsoth-ai/de-anthropocentric-research-engine, which has 505 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on September 29, 2026.
Source: yogsoth-ai/de-anthropocentric-research-engine on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.