Build a custom session search tool that indexes and queries past Claude Code CLI chat logs to retrieve historical findings, techniques, and context. Based on Critical Thinking Bug Bounty Podcast Episode 166.
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概要と使いどころ
Build a custom session search tool that indexes and queries past Claude Code CLI chat logs to retrieve historical findings, techniques, and context. Based on Critical Thinking Bug Bounty Podcast Episode 166.
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。
White-box source code security review structured around OWASP ASVS 5.0 (427 verification requirements across 16 chapters). Reads and understands application source code to build a security-aware knowledge base that enriches all downstream skills. Covers: tech stack identification, route/endpoint mapping, authentication and authorization architecture, dangerous function patterns, source-to-sink data flow tracing, IaC review, dependency analysis, ASVS compliance mapping, and LLM integration security (prompt injection, tool abuse, output handling, RAG poisoning, MCP server patterns). When LLM/AI framework usage is detected, automatically reviews OWASP LLM Top 10 patterns from source code and chains into /ai-redteam with white-box context for live endpoint testing. Chains into /pentester, /threat-modeling, /web-exploit, /api-security, /cloud-security, /analyze-cve, /credential-audit, and /ai-redteam — providing white-box context that transforms black-box testing into targeted, informed assessment.
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Analyze competitors using Blue Ocean Strategy's ERRC Grid and Strategy Canvas (W. Chan Kim and Renee Mauborgne) to identify uncontested market space, not just who is better on the same axes. Produces an ERRC Grid, Strategy Canvas, positioning matrix, messaging comparison, and differentiation map. Use when the user asks for competitive analysis, competitor research, "how do we compare to X", positioning vs competitors, market landscape, "analyze our competition", "where is the blue ocean", or wants to update competitor docs. Writes to knowledge/markets/competitors.md. For a lightweight competitor summary in the knowledge base, see brand-context. For positioning against them, see positioning-doc.
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Spin up a new loop (domain) in a file-based knowledge base — bootstrap the substrate if it's missing, gather the loop's charter, scaffold domains/<loop>/README.md, then do ONE real test run and record it in the loop's Timeline and LOG.md. Use when the user says "set up a new loop", "create a domain", "start a new beat/workstream", or names a recurring job they want the agent to own.
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Initialize, adopt, and route work for a separate Obsidian knowledge vault through the portable claude-obsidian core. Use for vault setup, scaffolding, workspace selection, cross-project configuration, or choosing the correct wiki sub-skill. Triggers: /wiki, set up wiki, scaffold vault, create knowledge base, adopt this vault, Obsidian vault, second brain setup, persistent wiki.
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Use when building or maintaining a personal LLM-powered knowledge base. Triggers: ingesting sources into a wiki, querying wiki knowledge, linting wiki quality, 'add to wiki', 'what do I know about', or any mention of 'LLM wiki' or 'Karpathy wiki'.
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。
Search the knowledge base in [Notion](https://composio.dev/toolkits/notion) for answers to customer questions.
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。
Master the `agentbrain` CLI (npm package `agentbrain-cli`). Use this skill whenever the user runs, installs, configures, or asks about `agentbrain` commands; when they interact with the AgentBrain enterprise data hub — organizations, connectors, knowledge bases, workflows, media/documents, knowledge graph, permissions, LLM/prompt config, cost & usage, governance, audit logs; when uploading documents/files to AgentBrain (`agentbrain media upload`); when authenticating (login/logout/token/apiKey); when retrieving MCP context (`agentbrain retrieve-context`); when running SQL against a connector; when the user pastes any `agentbrain …` command; when they edit `~/.agentbrain/config.json`; or when they mention AgentBrain, agent-brain, agentbrain-cli, or the `.agentbrain` folder.
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Persistent cross-session knowledge base. Manages per-project learnings that compound across sessions — patterns, pitfalls, preferences, and project quirks. The agent gets smarter on your codebase over time. At session start, searches relevant learnings. During sessions, logs discoveries. Supports review, search, prune, and export. Use proactively when the agent encounters a durable project quirk, user preference, or pattern that would save 5+ minutes next time. Also use at session start to recover context. Triggers: "remember this", "log this", "what have we learned?", "show learnings".
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Personal knowledge base powered by Ensue for capturing and retrieving understanding. Use when user wants to save knowledge, recall what they know, manage their toolbox, or build on past learnings. Triggers on "save this", "remember", "what do I know about", "add to toolbox", "my notes on", "store this concept".
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Capture, gate, query, and render long-term project knowledge through the gated `mewkit wiki` subsystem. Use to create a wiki, propose/approve candidates (scanner-gated), hand off a skill's terminal artifact as a scanned candidate, recall context, search the FTS index, or list pages. Agents may only PROPOSE candidates; canonical pages are written only via human approve. NOT for short-lived JSON memory (see mk:memory); NOT for fetching external sources (see mk:wiki-research); NOT for HTML snapshots (see mk:wiki-render).
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Generate and maintain a persistent codebase wiki — LLM-built interlinked markdown knowledge base (Karpathy LLM Wiki pattern)
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n8n workflow automation knowledge base. Provides n8n node information, node functionality details, workflow patterns, and configuration examples. Covers triggers, data transformation, data input/output, AI integration, covering 10 nodes. Keywords: n8n, workflow, automation, node, trigger, webhook, http request, database, ai agent.
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Maintain a review-first Markdown knowledge base for Codex practices with source provenance, engineering capture, citation-aware queries, explicit archive and promotion, and deterministic linting. Use when asked to capture a durable engineering lesson, ingest Codex research, query or archive what the repository knows, check wiki health, reconcile conflicting guidance, or promote verified knowledge.
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MITRE ATT&CK is a globally-accessible knowledge base of adversary tactics, techniques, and procedures (TTPs) based on real-world observations. This skill covers systematically mapping threat actor beh
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This skill should be used when providing ITIL 4-based IT service management consulting. Use this when organizations need guidance on implementing ITIL 4 practices, improving service management maturity, optimizing IT operations, or aligning IT services with business objectives. Provides tailored recommendations based on department, scenario, and organizational context using comprehensive ITIL 4 knowledge.
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Load when asked where code lives, how modules relate, what calls a symbol, what implements a feature, or for an architecture/codebase tour using the knowledge graph; not for bug diagnosis, diff review, or refactoring.
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Knowledge base from NASA System Safety Handbook Volume 2 (NASA/SP-2014-612). Use for risk-informed safety cases (RISC), integrated safety analysis (ISA), adequate safety concepts, safety objectives and requirements, acquirer/provider roles, graded safety analysis, claims-evidence-argument structure, SSMP development, and RISC evaluation. Does not cover nuclear or chemical safety domains, occupational health regulations, or NASA-specific programmatic requirements beyond system safety.
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Knowledge base from the NIST/SEMATECH e-Handbook of Statistical Methods (NIST HB 151) — the practical statistics reference for engineering, metrology, and quality. Use for: exploratory data analysis and the four univariate assumptions (4-plot); measurement process characterization including bias/precision, calibration designs, gauge R&R, and ISO/GUM uncertainty budgets; production process characterization (stability vs. capability); process modeling and regression (LS/WLS/NLS/LOESS); design of experiments (screening, fractional/factorial, response-surface, Taguchi); statistical process control (Shewhart/CUSUM/EWMA charts, capability indices, acceptance sampling); product/process comparisons (hypothesis tests and confidence intervals for 1/2/3+ groups, ANOVA, multiple comparisons); and reliability (lifetime & repair-rate models, accelerated testing, reliability growth). Scope limits: this is applied frequentist statistics for measurement and quality — it does NOT reproduce the per-distribution formula galleries, worked case studies, datasets, plot images, or Dataplot/R code of the original web Handbook (those are described, not copied); it is thin on modern machine learning, Bayesian methods beyond conjugate reliability priors, time-series/forecasting, and Bayesian experimental design.
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Knowledge base from NIST Cybersecurity Framework (CSF) 2.0. Use for cybersecurity risk management, GOVERN, IDENTIFY, PROTECT, DETECT, RESPOND, RECOVER, Organizational Profiles, CSF Tiers, supply chain risk, enterprise risk management, incident response. Covers the CSF 2.0 document only; does not cover specific SP 800-53 controls, NIST RMF system authorization steps, or sector-specific regulations.
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Knowledge base from NIST SP 800-61 Rev. 3 (Incident Response Recommendations for Cybersecurity Risk Management). Use for CSF 2.0-aligned incident response life cycles, IR roles, Community Profile priorities for DE/RS/RC and preparation, playbooks, coordination, and continuous improvement. Covers 800-61r3 only; does not replace CSF 2.0 full text, SP 800-61r2 tactical playbooks, or sector-specific breach-notification law.
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Knowledge base from NIST SP 800-160 Vol 1 (Engineering Trustworthy Secure Systems) and Vol 2 (Developing Cyber-Resilient Systems). Use for systems security engineering (SSE): the three SSE framework contexts (problem/solution/trustworthiness), the 30+ design principles for trustworthy secure design, trustworthiness and assurance/assurance cases, security across the ISO/IEC/IEEE 15288 life-cycle process groups, and the Vol 2 cyber-resiliency engineering framework — 4 goals (anticipate/withstand/recover/adapt), objectives, 14 techniques, implementation approaches, and design principles for the APT/adverse-conditions threat model. Bridges systems engineering and the NIST security cluster (CSF/SSDF/RMF). Does not reproduce ISO/IEC/IEEE 15288 process text, nor cover SP 800-53 control catalogs in depth.
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Knowledge base from the NIST Framework for Cyber-Physical Systems (SP 1500-201/202/203, v1.0, 2017). Use for engineering and analyzing cyber-physical systems (CPS) and IoT: the CPS Framework's aspect × facet grid (nine aspects of concern examined through conceptualization, realization, and assurance facets), cross-property trustworthiness risk management (safety/security/privacy/reliability/resilience together), data interoperability (syntactical/semantic/contextual, canonical models, identifiers, provenance), the timing aspect (time-interval classes, time domains, time-aware networking) and secure/resilient time (GNSS jamming/spoofing, PTP/NTP attacks, holdover, the clock-error model and Allan/MTIE metrics), plus the use-case requirements method. Bridges IT and OT under a clock. Scope limits: a 2017 living/draft document, thin on post-2017 standards and on detailed control catalogs; it names but does not reproduce ISO/IEC/IEEE 42010 and 15288 process text or permission-licensed third-party figures.
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Knowledge base from NIST Secure Software Development Framework (SSDF) v1.1 (SP 800-218). Use for secure software development practices, SDLC security integration, software supply chain security, vulnerability disclosure, SBOM, threat modelling, secure coding, build hardening, EO 14028 compliance. Covers the four SSDF practice groups (PO, PS, PW, RV) only; does not cover NIST CSF, SP 800-53 controls, or cloud-specific security frameworks in depth.
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。