527 skills · sorted by relevance
Automate Esignatures IO operations through Rube MCP using Composio tools. The skill guides an agent through finding available actions, checking the service connection, and supplying the required inputs for individual or bulk tasks.
Implement electronic signatures compliant with 21 CFR Part 11 Subpart C and EU Annex 11. Covers signature manifestation (signer, date/time, meaning), signature-to-record binding, biometric vs non-biometric controls, policy creation, and user certification requirements. Use when a computerized system requires legally binding electronic signatures for GxP records, when replacing wet-ink signatures in regulated workflows, when implementing batch release or document approval workflows, or when a regulatory gap reveals missing signature controls.
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Identify recurrent and driver copy number alterations across a tumor cohort with GISTIC2 (G-score, Ziggurat deconstruction, focal vs broad/arm-level analysis, q-values from permutation) and quantify copy-number signatures with the Steele 2022 COSMIC framework and the Drews 2022 CINSignatures framework. Covers driver-gene localization from recurrence peaks, distinguishing focal drivers from arm-level passengers, and the caller-sensitivity caveats of copy-number signatures. Use when finding recurrently amplified or deleted regions in a cohort, localizing driver genes, separating focal from broad events, running GISTIC2, or extracting copy-number mutational signatures.
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Identify recurrent and driver copy number alterations across a tumor cohort with GISTIC2 (G-score, Ziggurat deconstruction, focal vs broad/arm-level analysis, q-values from permutation) and quantify copy-number signatures with the Steele 2022 COSMIC framework and the Drews 2022 CINSignatures framework. Covers driver-gene localization from recurrence peaks, distinguishing focal drivers from arm-level passengers, and the caller-sensitivity caveats of copy-number signatures. Use when finding recurrently amplified or deleted regions in a cohort, localizing driver genes, separating focal from broad events, running GISTIC2, or extracting copy-number mutational signatures.
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Identify recurrent and driver copy number alterations across a tumor cohort with GISTIC2 (G-score, Ziggurat deconstruction, focal vs broad/arm-level analysis, q-values from permutation) and quantify copy-number signatures with the Steele 2022 COSMIC framework and the Drews 2022 CINSignatures framework. Covers driver-gene localization from recurrence peaks, distinguishing focal drivers from arm-level passengers, and the caller-sensitivity caveats of copy-number signatures. Use when finding recurrently amplified or deleted regions in a cohort, localizing driver genes, separating focal from broad events, running GISTIC2, or extracting copy-number mutational signatures.
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Identify recurrent and driver copy number alterations across a tumor cohort with GISTIC2 (G-score, Ziggurat deconstruction, focal vs broad/arm-level analysis, q-values from permutation) and quantify copy-number signatures with the Steele 2022 COSMIC framework and the Drews 2022 CINSignatures framework. Covers driver-gene localization from recurrence peaks, distinguishing focal drivers from arm-level passengers, and the caller-sensitivity caveats of copy-number signatures. Use when finding recurrently amplified or deleted regions in a cohort, localizing driver genes, separating focal from broad events, running GISTIC2, or extracting copy-number mutational signatures.
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Ed25519 is a high-performance digital signature algorithm using the Edwards curve Curve25519. It provides 128-bit security with 64-byte signatures and 32-byte keys, offering significant advantages ove
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Process PDFs, Office documents, HTML, and images through the Nutrient DWS API. Convert formats, extract text and tables, recognize text in scans with OCR, remove sensitive information, add watermarks or digital signatures, and fill PDF forms.
Assess authorized single sign-on systems using SAML, OIDC, and OAuth2. Map the login flow, check signatures, redirects, and token validation, then document reproducible findings and their impact, including identity or tenant confusion.
Assess software dependencies, build pipelines, and container images for security risks. Create a software component inventory, check vulnerabilities and license conflicts, verify artifact signatures, and prioritize fixes based on whether vulnerable code can actually be reached.
Analyze authorized macOS applications and Mach-O binaries, the executable format used on macOS. Examine signatures, dependencies, Objective-C and Swift symbols, and runtime behavior to produce findings tied to specific addresses or symbols.
Trace how a web page generates request signatures and encrypted parameters by inspecting network requests and JavaScript execution. Collect runtime evidence, then use it to reproduce the behavior locally in Node.js.
Create rules for Suricata and Snort, systems that detect suspicious network traffic, to flag port scans and reconnaissance. Combine packet patterns with connection counts, tune alert volume, and summarize scanning sources, targets, and activity.
Check training data and machine learning models for malicious changes, including backdoors that cause unexpected behavior on specific inputs. Combine data quality checks, model analysis, and file integrity verification, then document findings and retest after remediation.
Investigate attacks that make legitimate Windows applications load malicious DLL files. This skill examines loading events, digital signatures, file hashes, and unusual locations, then checks process behavior to document suspicious cases and guide remediation.
Investigate Entra ID reconnaissance by searching Graph API logs for tool signatures and unusual directory queries. Use KQL, a log query language, to correlate suspicious requests with sign-ins and turn useful searches into Sentinel detection rules.
Analyze Cobalt Strike communication profiles and Beacon payload configurations to extract request paths, headers, timing, and process injection settings. Turn these indicators into a JSON report and network detection rules for Suricata or Snort.
Search automatically generated code documentation to check function parameters, class definitions, API details, and comments before making changes. Find relevant documents by meaning, exact keywords, or document type, then retrieve their full contents.
Checks published OpenWork desktop downloads for mac-arm64, verifying developer signatures, Apple notarization, and update metadata. It checks versions, download references, and file hashes, then records evidence to support a release rollout decision.
Examine writing for familiar AI patterns, statistical features, Pangram detection scores, and hidden character signatures. Compare drafts against known human writing to interpret the evidence, with explanations and limitations rather than a definitive authorship claim.
Plan encryption, TLS connections, digital signatures, and key management using established cryptographic libraries. Get guidance on choosing algorithms, storing passwords, rotating keys, and avoiding implementation mistakes such as reused nonces or comparisons that reveal information through timing.
Finds Lark contacts by name or email and retrieves open_id, an identifier used in later actions. It also looks up profile details, personal status, and signatures, and searches for bots or agents visible to the current user.
Diagnose macOS app launch and trust failures by inspecting code signatures, app permissions, and Gatekeeper checks. Identify the failure category and get a minimal validation or repair sequence that distinguishes local development issues from distribution requirements.
Extract and analyze mutational signatures from somatic variants using SigProfiler or MutationalPatterns to characterize mutagenic processes. Use when identifying DNA damage mechanisms or etiology in cancer genomes.
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