69 skills · sorted by relevance
Recommend runtime and V2 scene management: run recommendation requests, manage recommend scenes and rules, and verify the deployed recommendation path.
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Investigate suspected email account takeovers by examining audit logs, sign-ins, inbox rules, and app permissions. Identify suspicious forwarding, unlikely travel between sign-ins, and unusual access, then summarize findings and recommended containment actions in a severity-rated report.
Interactive BPA rule generation for Power BI semantic models; guided discovery, model investigation, and expert rule authoring. Automatically invoke when the user mentions "BPA rule", "Best Practice Analyzer", or asks to "create a BPA rule", "audit BPA rules", "recommend BPA rules", "set up BPA for my team", "check model for best practices", "validate BPA rules", "improve a BPA expression".
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Investigate suspicious email forwarding and hidden inbox rules that may expose messages after an account compromise. The skill guides log analysis, validation, and reporting, helping analysts document evidence, assess risk, and recommend response actions.
Assign unowned leads and opportunities using company routing rules and existing account relationships. Prepare a recommendation with its reasoning, draft handoff notes, and apply ownership changes after a person accepts or overrides each recommendation.
Review AI agent instructions for unnecessary rules, contradictions, repetition, and vague wording. Get recommendations on what to remove, merge, clarify, or load only when needed, plus an estimate of savings in tokens, the units models process.
Use this skill when the user is tuning a live or captured `doca-flow` pipeline with `doca_flow_tune` — snapshotting pipe / counter / KPI state, picking a tuning axis (rule placement, resource hints / table sizing, HW-offload mode) and a matching measurement (rule-install rate, lookup latency, hardware-counter delta), running offline or online (read-only or state-changing) modes, reading the dumper CSV / analyze JSON / visualize mermaid, or applying a recommendation back into the Flow program. Trigger even when the user does not explicitly mention "doca_flow_tune" — typical implicit phrasings include "Flow rule-install rate is low on BlueField", "table sizing looks wrong for this pipe", "tune visualize step is empty", "before/after counters don't move", or "which doca-flow knob does this recommendation hit". Refuse and route elsewhere for measuring baseline numbers (doca-flow-perf, doca-flow-dpa-perf), writing the doca-flow application, DOCA install, or streaming Flow telemetry — those belong to other skills.
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Use this agent when you need to review UniProt annotation rules (ARBA, UniRule) for quality, biological accuracy, and GO annotation appropriateness. This agent performs comprehensive analysis of rule condition sets, evaluates literature support, assesses taxonomic scope, and recommends curation actions.
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Audit instructions and memory files loaded on every agent turn. Identify repeated rules, contradictions, outdated content, and material better moved into skills, then receive evidence-backed recommendations ranked by estimated token savings and change risk.
Review Claude Code’s automatically saved memory to identify outdated entries, duplicates, and conflicts with existing instructions. Produces a health report and recommendations for consolidating notes or turning recurring lessons into lasting project rules.
Check the state of an agent’s project memory with a dashboard of line counts, topic files, capacity, outdated file references, and duplicates. Get cleanup recommendations or request a one-line status summary.
MUST USE when reviewing ClickHouse schemas, queries, or configurations. Contains 31 rules that MUST be checked before providing recommendations. Always read relevant rule files and cite specific rules in responses.
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Produces a Rule 506(d) bad actor disqualification review for private securities offerings, including a covered persons register, tailored questionnaires mapping to each disqualifying event category, a documented reasonable-care diligence record, and classification analysis of flagged events with remediation or disclosure recommendations. Use this skill when conducting Rule 506(d) diligence, identifying covered persons for a Regulation D offering, drafting bad actor questionnaires, or analyzing potential disqualifying events involving criminal convictions, SEC orders, SRO sanctions, or state regulatory actions. Also trigger when the user mentions bad actor screening, covered persons analysis, Rule 506(d) questionnaire, disqualification waiver, or reasonable care defense. Even if the user just says "bad actor check" or "506(d) diligence," use this skill.
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Audit a dataset or access rule before it joins an identity-graph build (access rules behave like datasets in NQL here). Enumerates failure modes (hub identifiers, high-degree nodes, suspicious values, over-connected identifiers), tests hypotheses in parallel, quantifies damage by rows / edges / entities, and proposes minimal filters ranked by severity. When issues are found, returns a validated `CREATE MATERIALIZED VIEW` NQL the caller can run to produce a graph-ready clean source; if the data passes, says so and recommends it unchanged. Plans and authors the clean-view NQL; does not execute it. Use when: "audit this dataset before the graph build", "find bad edges in <source>", "check identity data quality", "recommend filters for the graph build", "quantify damage from <identifier_type>", "pre-graph DQ". (narrative-identity)
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Turn a decision into a concise brief with one problem, three distinct options, and one recommendation. Compare benefits and drawbacks, then define measurable success criteria and practical steps for carrying out the recommended approach.
Generate coding agent instruction files from a project's actual code using AgentRC. Capture detected languages, frameworks, and conventions in one shared file or split rules by topic and project area, with a preview before writing.
Review incoming GitHub issues and pull requests, verify claims, and organize evidence alongside existing decisions. Prepare unresolved choices with recommendations and consequences for maintainers, then carry out actions covered by verified authorization without merging changes.
Investigate service account misuse by examining unexpected interactive logons, privilege changes, and movement between systems. Correlate endpoint and security logs, distinguish suspicious activity from legitimate operations, and document evidence, risk, and recommended responses.
Monitor Modbus traffic in industrial control networks to identify unauthorized writes, unusual commands, and departures from normal communication. Use packet analysis and intrusion detection rules to investigate suspected controller changes and produce reports with recommended actions.
Find repeated engineering tasks and turn them into agent workflows with clear checks, stopping rules, and approval boundaries. Compare published workflows, adapt suitable examples, or review existing ones for weak verification and uncontrolled repetition.
Review a game design document before implementation. Check missing sections, conflicting rules, formulas, dependencies, and testable success conditions, then report blocking issues and recommended changes. Full mode adds reviews by relevant specialist agents.
Create reusable starting configurations that combine an agent’s role, startup context, and source history. The skill guides registry entries, checks whether their sources are current, and manages their progression from initial capture to recommendation or retirement.
Investigate unexpected LoopX behavior, such as stalled progress or conflicting next steps. Identify whether agent decisions, state reporting, or workflow rules caused the problem, then repair, validate, and record the correction.
Analyze SonarCloud findings for a pull request, a proposed code change. Group issues by severity, type, file, and rule, then produce a report highlighting frequent problems and recommended priorities without modifying code.