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概要と使いどころ

post

無料

OS post-exploitation after a stable host foothold: quiet host recon, host-native persistence (Windows Run/tasks/services/COM/WMI and Linux SSH/cron/systemd/SUID), long-term C2 (Sliver primary, Mythic/Havoc optional), targeted collection and exfil, and engagement cleanup. Does not own AD/cloud/K8s native persistence, Ligolo pivoting, LSASS dumping, or EDR bypass. Operator selects objectives; success is a live callback, verified persistence, delivered loot, or restored host — not generating an unused implant.

日本語の概要は準備中です。原文の説明を表示しています。

pale-knight/redteam-skill512026年8月23日 更新

Builds revolving securitization models with replenishment criteria, early amortization triggers, and portfolio composition limits. Use when modeling revolving structures, analyzing credit card ABS, or evaluating asset purchase criteria.

日本語の概要は準備中です。原文の説明を表示しています。

CaseMark/skills442026年10月15日 更新

Builds default probability and recovery rate models with industry data, structural analysis, and loss-given-default estimation. Use when modeling credit losses, estimating recovery values, or analyzing default scenarios.

日本語の概要は準備中です。原文の説明を表示しています。

CaseMark/skills442026年10月15日 更新

Structures official committee operations with financial advisor engagement, investigation scope, and plan negotiation strategy. Use when supporting creditor committees, coordinating committee advisors, or analyzing committee positions.

日本語の概要は準備中です。原文の説明を表示しています。

CaseMark/skills442026年10月15日 更新

Creates debt offering memoranda with credit overview, financial analysis, industry section, and risk factors for investor marketing. Use when preparing debt OMs, writing credit marketing materials, or structuring lender presentations.

日本語の概要は準備中です。原文の説明を表示しています。

CaseMark/skills442026年10月15日 更新

Evaluates secondary-focused credit facilities with leverage terms, borrowing base mechanics, and portfolio pledging requirements. Use when analyzing secondary lending, structuring portfolio leverage, or evaluating fund finance options.

日本語の概要は準備中です。原文の説明を表示しています。

CaseMark/skills442026年10月15日 更新

Evaluates structured product tranche pricing with spread analysis, yield attribution, and comparable structure benchmarking. Use when assessing tranche value, comparing structured product pricing, or analyzing spread components.

日本語の概要は準備中です。原文の説明を表示しています。

CaseMark/skills442026年10月15日 更新

Assesses underlying asset pools with stratification, concentration analysis, historical performance, and credit quality distribution. Use when analyzing collateral pools, stratifying asset characteristics, or evaluating pool quality.

日本語の概要は準備中です。原文の説明を表示しています。

CaseMark/skills442026年10月15日 更新

Evaluates MBS structures with prepayment modeling (CPR/CDR), collateral analysis, and tranche-level credit risk assessment. Use when analyzing MBS, modeling prepayment scenarios, or evaluating residential mortgage pools.

日本語の概要は準備中です。原文の説明を表示しています。

CaseMark/skills442026年10月15日 更新

Evaluates ISDA Master Agreement provisions with close-out netting, termination events, and credit support annexes. Use when reviewing ISDA terms, analyzing CSA provisions, or assessing documentation risk.

日本語の概要は準備中です。原文の説明を表示しています。

CaseMark/skills442026年10月15日 更新

Evaluates uptier exchanges, drop-down transactions, and covenant-stripping maneuvers as aggressive liability management tools. Use when analyzing LMTs, evaluating creditor-on-creditor violence, or assessing cooperation agreement strategies.

日本語の概要は準備中です。原文の説明を表示しています。

CaseMark/skills442026年10月15日 更新

Evaluates make-whole premium claims in bankruptcy with contract interpretation, present value disputes, and secured status analysis. Use when analyzing make-whole claims, evaluating redemption disputes, or assessing premium recovery.

日本語の概要は準備中です。原文の説明を表示しています。

CaseMark/skills442026年10月15日 更新

Evaluates mezzanine structures with PIK toggle, equity kickers, and intercreditor subordination mechanics. Use when analyzing mezzanine financing, comparing subordinated debt terms, or modeling layered capital structures.

日本語の概要は準備中です。原文の説明を表示しています。

CaseMark/skills442026年10月15日 更新

Evaluates distressed debt opportunities with recovery analysis, liquidity assessment, and potential restructuring outcomes. Use when screening distressed situations, analyzing stressed credits, or evaluating workout scenarios.

日本語の概要は準備中です。原文の説明を表示しています。

CaseMark/skills442026年10月15日 更新

Detect, validate, and generate Schema.org structured data. JSON-LD format preferred. Use when user says "schema", "structured data", "rich results", "JSON-LD", or "markup".

日本語の概要は準備中です。原文の説明を表示しています。

mits-pl/wove422026年6月20日 更新

Feed actual task results back into agent memory for calibration. Compares predicted vs actual outcomes, records accuracy scores, and tracks estimation quality, prediction quality, and decision quality over time to improve future agent performance.

日本語の概要は準備中です。原文の説明を表示しています。

oimiragieo/agent-studio422026年7月14日 更新

Verify fix commits address security findings without introducing new bugs or regressions. Analyzes diffs for anti-patterns like removed validation, weakened access control, reduced error handling, reordered external calls, and changed integer operations. Generates structured FIX_REVIEW_REPORT with finding status tracking.

日本語の概要は準備中です。原文の説明を表示しています。

oimiragieo/agent-studio422026年7月14日 更新

Design new proteins that bind a chosen surface, using BindCraft's AlphaFold2-guided hallucination or the RFdiffusion backbone plus ProteinMPNN sequence pipeline. Use this skill to specify a target epitope by hotspot residue, trim a receptor to the region worth designing against, set up a design campaign, and filter the output on the in-silico metrics that predict experimental success — interface predicted TM-score, predicted aligned error at the interface, buried surface area, and shape complementarity. Also trigger on BindCraft, RFdiffusion, ProteinMPNN, minibinder, hallucination, inverse folding, hotspot residue, epitope targeting, ipTM, or de novo binder.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/drug-discovery-agent-skills412026年10月12日 更新

tamarind

無料

Access a collection of open-source molecular design and structural biology tools on the Tamarind Bio platform, via its REST API or MCP server — no local GPUs required. Tamarind bundles popular open-source models for structure prediction (AlphaFold, Boltz, Chai, ESMFold), protein, binder, and de novo design (RFdiffusion, ProteinMPNN, BoltzGen), antibody and nanobody design and developability, protein-ligand docking (DiffDock, Autodock Vina), binding-affinity prediction, MSA generation, and molecular dynamics. Use when the user mentions Tamarind or tamarind.bio, wants to run any of these open-source tools in the cloud, references app.tamarind.bio/api or the x-api-key header, or needs to submit batches of sequences for structural or biophysical characterization.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/drug-discovery-agent-skills412026年10月12日 更新

pytdc

無料

Use Therapeutics Data Commons through the PyTDC Python package for registry discovery, approved dataset access, task-aware splits (scaffold, cold-start, temporal, combination), evaluator metrics, benchmark groups, and bounded molecular-oracle workflows. Use this skill to find which TDC datasets exist for a therapeutic task, load them with a split that does not leak, score predictions with the task's own official metric rather than a generic one, and run benchmark groups reproducibly. Also trigger on PyTDC, Therapeutics Data Commons, tdc.single_pred, tdc.multi_pred, ADMET Benchmark Group, scaffold split, get_split, or molecular oracles such as GSK3B, JNK3 and DRD2.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/drug-discovery-agent-skills412026年10月12日 更新

Turn a set of structures into absorption, distribution, metabolism, excretion, and toxicity estimates with ADMET-AI, and read them as a developability verdict rather than a table of numbers. Use this skill to run batch prediction over a library, interpret each endpoint against its DrugBank-approved percentile, and flag the liabilities that stop a series — hERG blockade, CYP inhibition, poor Caco-2 permeability, high clearance, and plasma protein binding. Also trigger on ADMET-AI, admet_ai, Chemprop-RDKit, hERG liability, CYP3A4 inhibition, Caco-2, bioavailability prediction, or developability triage.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/drug-discovery-agent-skills412026年10月12日 更新

pellicola

無料

Generate cinematic case study pages for films, documentaries, photography portfolios, and creative projects — film-frame hero images, structured crew credit grids, dark footage galleries, festival award sections, scroll-choreographed reveals via data-attribute animation orchestration. Warm cream palette with analog typography. Single-file HTML, zero build step. Triggers on film case study, documentary showcase, filmmaker portfolio, production company website, film credits page, creative project case study, director portfolio, photography case study.

日本語の概要は準備中です。原文の説明を表示しています。

tdimino/claude-code-minoan412026年10月16日 更新

Detects seven structural anti-patterns in Claude Projects that cause unpredictable output, ignored instructions, and degraded quality. Diagnoses Monolith, Orphan File, Echo Chamber, Phantom Conversation, Kitchen Sink, Misaligned Hierarchy, and Blurred Layers. Use when user says "what's wrong with my project," "Claude ignores my instructions," "diagnose my project," "why is output inconsistent," "review my project setup." Also trigger on symptom-phrased: "Claude doesn't follow my rules," "my instructions keep getting overridden," "my Project isn't behaving as designed." Use alongside rootnode-project-audit if available for deeper structural analysis. Activate whenever the user describes symptoms of unreliable, inconsistent, or degraded Claude Project output, even if they do not name a specific pattern. Do NOT use when the user's primary request is Memory-layer rebalancing (use rootnode-memory-optimization if available) or scoring a single prompt (use rootnode-prompt-validation if available).

日本語の概要は準備中です。原文の説明を表示しています。

drayline/rootnode-skills402026年9月14日 更新

Independent re-derivation gate for proposed changes during autonomous execution. Evaluates a change (code diff, config edit, engine evolution, schema change) against the work's authority matrix and a 4-check protocol: invariant compliance, scope authorization, detection narrowness, and regression risk. Returns structured JSON with pass/fail per check, an overall verdict (APPROVE / REQUEST_CHANGES / REJECT), and blockers. Profile-driven thresholds (strict for unattended runs, lenient for desk supervision). Use when an autonomous agent proposes an engine change, when reviewing a Claude Code-authored modification before merge, or when an unattended profile requires independent re-derivation. Trigger on: "review/approve this proposed change," "critic-gate this," "is this change safe," "is this safe to merge," "should I let this land," "run the critic." Do NOT use for handoff-readiness checks (use rootnode-handoff-trigger-check), general code review, or design-time correctness. Authority matrix required.

日本語の概要は準備中です。原文の説明を表示しています。

drayline/rootnode-skills402026年9月14日 更新