Results for “posture-assessment”

Run Azure compliance and security audits using azqr and Key Vault expiration checks, covering best-practice assessment, resource review, and security posture validation.

Assess the security posture of Kubernetes etcd clusters by evaluating encryption at rest, TLS configuration, access controls, backup encryption, and network isolation.

Train, evaluate, export, and run inference for pose classification models using ST-GCN on skeleton keypoint sequences.

Assess cloud infrastructure for security misconfigurations, IAM privilege escalation paths, S3 public exposure, open security group rules, and IaC security gaps across AWS, Azure, and GCP with MITRE ATT&CK mapping.

Evaluates automated metrics and vision-language models on identifying granular errors in detailed image descriptions and ranking paired descriptions against human judgments, using macro F1, pairwise accuracy, Spearman rank ρ, and Kendall's τ.

Guides statistical hypothesis testing with assumption checks, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting for research data.

Scores generated image captions against reference captions and source images using the Polos metric, which is trained to align with human judgments and probes hallucination robustness and open-vocabulary evaluation.

Perform a broad, authorized security audit across application, infrastructure, identity, dependencies, and operations. Use when the user needs a scoped security posture review; use the SAST, DAST, dependency-scanning, or threat-modeling skill when the request is limited to one specialist activity.

Every metric encodes an opinion about which mistake hurts.

Assess Active Directory security posture using PingCastle, BloodHound, and Purple Knight to identify misconfigurations, privilege escalation paths, and attack vectors.

Honestly evaluate AI work quality using a two-axis scoring system with mandatory devil's advocate reasoning and cross-session anti-inflation detection.

Establishes a two-party working posture where the user directs and the agent executes, surfacing every genuine fork as a batched single-select question with a recommended default.

日本語の生産性コーチングモード。明示的な依頼、反復失敗、受け身、検証不足、品質不満のときに、構造化トラブルシューティングと証拠ベースの完了確認を促す。

Give a decisive, project-grounded point of view in the subject's own shape: a graded verdict on an external-adoption question, a holistic take on a document, or a position on a user-supplied approach set. Use for a solo POV, a mid-session second opinion, a named-peer cross-check, any request to consult other models or reconcile their opinions, an `oracle` panel, or a correction-cost-gated proactive cross-check offer. Not for findings review (use ce-doc-review), neutral explainers, or generating options (use ce-ideate or ce-brainstorm).

Design prospective clinical studies by selecting and classifying endpoints, estimating sample size and power for two-arm designs, and scoring study plans for feasibility with phase-gate decisions.

Cloud security posture assessment for AWS, Azure, and GCP. Tests IAM privilege escalation paths, public storage exposure, serverless attack surface, database exposure, logging gaps, container registry security, and cloud-specific attacks. Both authenticated (with cloud credentials) and unauthenticated (external) modes. Uses nuclei cloud templates, Prowler, ScoutSuite, manual IMDS/metadata probing, and deep AWS/Azure/GCP CLI enumeration. Produces: cloud architecture diagram, attack path map, findings per category, compliance mapping (SOC 2, PCI DSS 4.0, HIPAA, CIS), PoCs for confirmed exploits. Chains into /gh-export for issue filing.

Evaluates the robustness and alignment with human judgment of reference-based and reference-free evaluation metrics for machine translation and summarization, particularly under adversarial conditions.

Continuously discover, classify, and score APIs based on risk while enforcing security policies across the API lifecycle.

Red-team a PRD, roadmap, or strategy by attacking its load-bearing assumptions before reality does, ranking failure modes by impact, likelihood, and cheapness to test.

Design and evaluate paid-ad experiments with hypotheses, randomization, sample-size calculations, guardrails, and decision rules for A/B and split tests.

Validates the Emotional Attitude Score (EAS) metric by measuring its consistency with human judgment on word-level sentiment polarity, using the AmbGIMT dataset and pairwise score comparisons.

Provides guidance on acceptable blood sampling conditions for primary aldosteronism screening when ideal early‑morning supine fasting conditions cannot be met. Triggers include when a clinician says “The patient wasn’t fasting/supine” or questions whether non‑ideal sampling affects screening validity.

Performance-coaching mode for repeated failures, passive behavior, completion-quality issues, or explicit try-harder requests. Uses structured troubleshooting and evidence-first delivery habits.

Determines if PAC/PRA ratio and PAC levels indicate positive or provisionally positive screening for primary aldosteronism. Triggered when a clinician has PAC and PRA results and asks “Is this screening test positive for PA?” or needs to interpret borderline results.

Evaluates execution outcomes against defined success criteria, scoring each criterion and producing a structured verdict with actionable feedback.

Assesses cloud infrastructure for security misconfigurations, IAM privilege escalation paths, S3 public exposure, open security group rules, and IaC security gaps across AWS, Azure, and GCP with MITRE ATT&CK mapping.

Score a clinical ASR manifest against a chosen NIM, produce a five-section KER leaderboard, and route the user via a post-eval decision tree.

Ranks any list of impediments and their countermeasures using a value-stream scoring model (ROI, Cost to Implement, Ease of Deployment, Risk Factor) and a fixed prioritization formula.

PTES-aligned adversarial security audit for backend, frontend, and mobile applications. Produces a CVSS-scored Hacker Report with verified PoCs and phased remediation.

Stress-test a feature idea for an existing product by surfacing risky assumptions across Value, Usability, Viability, and Feasibility using multi-perspective devil's advocate thinking.