Results for “categorize”

Operator-side analysis of historical ML experiment PRs in Senpai research tracks. Use this skill whenever the user asks to: analyze experiments, categorize PRs, bucket experiments, summarize what's been tried, understand experiment history, review merged vs closed results, or asks "what experiments have we run / worked / failed". Also triggers for: "pull the latest experiments", "what's been tried so far", "category breakdown of PRs", "which experiments succeeded", "noam track analysis". When a branch name is mentioned (e.g. "noam branch", "on the noam branch"), pass it as the base branch to scope the fetch to just those PRs.

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"Implement LDA topic modeling to discover latent topics in document collections. Use this skill when the user needs to extract topics from a text corpus, categorize documents by theme, or explore thematic structure — even if they say 'what are the main topics', 'topic extraction', or 'document clustering by theme'.".

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Run a monthly money check-in with an AI assistant: categorize spending, spot leaks, set one savings target, and view it through the 50/30/20 lens — judgment-free. Use once a month to stay aware of where your money goes. General educational information, not financial advice.

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Track, categorize, and prioritize technical debt across the codebase. Scans for debt indicators, maintains a debt register, and recommends repayment scheduling.

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Write SEO-optimized long-form articles targeting specific keywords using the They Ask You Answer Big 5 framework (Marcus Sheridan). Articles are categorized by Big 5 type (Cost, Problems, Versus, Best/Reviews, How-To) and structured accordingly. The "answer first" rule applies to every article. Use when the user asks for an SEO article, blog post for ranking, "rank for keyword X", organic content, search-optimized post, pillar page, or content for organic traffic. Includes keyword targeting, search intent matching, internal linking suggestions, and meta tags. For improving an existing article, see copy-review. For deciding what to write about, see social-calendar pillars and icp-research. For repurposing it, see content-repurposer.

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Generate or update CHANGELOG.md from git history. Parses conventional commits, groups by version tags, categorizes into Added/Fixed/Changed/Breaking sections using keep-a-changelog format, and creates comparison links. Use when you need to create a changelog, update release notes, document version history, or prepare release documentation.

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Generate a production-grade OEE (Overall Equipment Effectiveness) measurement pipeline for a manufacturing line — data ingestion from MQTT/OPC-UA/Modbus/CSV, A×P×Q calculation engine, Six Big Losses categorizer, MTBF/MTTR/TEEP metrics, Grafana or Streamlit dashboard.

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Generates backend or frontend engineering specs in structured Jira format with description, categorized acceptance criteria, routes, dev notes, and table schemas.

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Phase 1 of the SRS workflow. User gives a project topic → AI runs a deep, categorized brainstorm (5 mandatory rounds) to fully understand actors, features, scope boundary, tech constraints, and business rules before writing anything.

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Phase 1 of the SRS workflow. User gives a project topic → AI runs a deep, categorized brainstorm (5 mandatory rounds) to fully understand actors, features, scope boundary, tech constraints, and business rules before writing anything.

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Produces privilege-safe U.S. corporate legal billing summaries from time and expense data. Converts entries into client-friendly narratives with categorized hours, rates, expenses, and milestones while enforcing engagement-letter rules and ethical billing safeguards. Use when asked to create a billing summary, invoice narrative, timekeeper breakdown, expense summary, or fee narrative.

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Produces structured asset and liability summaries from financial documents for legal proceedings. Extracts valuations, ownership classifications, and encumbrances, then outputs net-worth overview, categorized schedules, disputed items, and documentation gaps. Use when preparing financial summaries for divorce/dissolution, estate planning, bankruptcy, business valuation, or settlement negotiations. Trigger on: net worth summary, marital estate, balance sheet, asset schedule, liability schedule, community/separate property.

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Remove AI-generated code smells (slop) from branch changes or an explicit file list. Locks behavior with regression tests FIRST, then runs categorized cleanup via parallel `deep` agents in batches of 5, then verifies with quality gates. Covers 10 slop categories including performance equivalences, excessive complexity (object annotations, if/elif variant chains), and oversized modules (250+ pure LOC with mandatory modular refactoring). MUST USE when the user asks to "remove slop", "clean AI code", "deslop", "clean up AI-generated code", "remove AI slop", or wants to clean up AI-generated patterns from recent changes. Triggers - "remove ai slops", "clean ai code", "deslop", "cleanup AI generated", "remove AI slop", "clean up AI-generated code", "strip slop", "ai-slop cleanup".

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White-box security audit. Blue-teamer and lead red-teamer run in parallel isolation for an independent first pass — neither sees the other's output during reconnaissance. A synthesis step categorizes findings into four prescriptive buckets (anchoring-suppressed, convergent, blue-flagged-unverified, divergent), producing a unified target list. Focused red-teamers then deep-dive each target. Iterates when exploit chains are discovered. Heavy and thorough by design. Advisory only — produces findings and proposes tickets; does not implement remediation.

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Transform technical git commits into polished, user-friendly changelogs and release notes. Automatically categorizes changes, translates developer language into customer-friendly copy, and generates professional changelog entries.

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This skill categorizes hypercalcemia of malignancy (HCM) severity using albumin‑adjusted serum calcium into mild (<12 mg/dL), moderate (12‑14 mg/dL), or severe (>14 mg/dL). Use it when a clinician needs to stage HCM to guide initial therapy choices, such as deciding between observation, IV bisphosphonate/denosumab, or calcitonin‑based combination regimens.

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Systematic VPS cleanup — analyze files, categorize by importance, safely delete temporary/old data to free disk space

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Durable categorized record-keeping for any predicate-enabled walk. Trigger when: - Classifying a step's output for recording (decision, finding, debt, feedback). - Promoting a scratch artifact to the ledger, to repo/docs, or to a category home (.ledger/tech-debt/, .ledger/process-feedback/). - Auditing whether a draft is structurally ready for its destination. - Running a zero-context sensibility read before committing to promotion. - Recording a known limitation as a tech-debt entry (not prose in the log). - Recording a friction, miss, improvement, or process amendment. - Prompt contains: /record, record-keeping, promote, ledger note, zettelkasten, scratch-to-ledger, zero-context read, over-strip, classification trigger, tech-debt, process-feedback, amendment.

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Periodic inbox scan that categorizes new emails by project/client, identifies action-required items, and generates prioritized summary with FYI/requires-response/requires-action/blocked-waiting classifications. Use for inbox overview, project-based email grouping, or action item extraction.

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Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing. Covers network, host, email, and behavioral indicators using STIX/TAXII formats and threat intelligence platforms. Activates for requests involving IOC collection, indicator extraction, threat indicator sharing, compromise indicators, STIX export, or IOC enrichment.

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Audit ClawJS/Clawix code hygiene without editing code, producing categorized findings, baseline status, and validation evidence.

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Knowledge base from NIST SP 800-37 Revision 2, the Risk Management Framework (RMF) for information systems and organizations. Use for the seven RMF steps (Prepare, Categorize, Select, Implement, Assess, Authorize, Monitor) and their tasks; the three-tier organization-wide risk model; authorization boundaries; the requirements-to-controls relationship; security categorization (FIPS 199/200 high-water mark) and control selection/tailoring (SP 800-53/53B baselines); assessment, the authorization decision and risk acceptance, continuous monitoring and ongoing authorization; the security/privacy distinction; and supply chain risk management. This is the security-and-privacy-risk-governance edge of systems engineering — it governs how much protection and whether to accept residual risk, complementing the disciplines that decide how protection is built. Does NOT reproduce the SP 800-53 control catalog or its baselines, the FIPS impact tables, or the ISO/IEC/IEEE 15288 process text; it names and routes to them rather than restating them.

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Small-business bookkeeping skills for converting financial evidence into accountant-reviewable outputs, including setup/context, receipt processing, expense categorization, bank reconciliation, tax preparation, monthly close, jurisdiction-aware tax references, plus specialized skills for home office, vehicle, meals, depreciation, 1099 contractors, and estimated taxes. Trigger on "help me with my bookkeeping", "set up my bookkeeping", "bookkeeping context", "chart of accounts", "process my receipts", "categorize expenses", "reconcile my bank statement", "get my books ready for taxes", "close the month", "organize my finances".

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Repeatable month-end close checklist for small businesses — lock the period, process outstanding receipts, categorize remaining items, reconcile all accounts, review large transactions, check contractor 1099 thresholds, generate monthly P&L summary. Trigger on "close the month", "month-end close", "monthly bookkeeping", "close the books".

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