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概要と使いどころ
Agent fallback for CBaseEntity_dtor (auto-generated, category: func). Locate CBaseEntity::~CBaseEntity in the CS2 server module via IDA Pro MCP and emit a fresh, minimal-unique artifact. The deterministic preprocessor could not resolve this symbol on the current gamever - your job is the re-sign. Trigger: CBaseEntity_dtor, CBaseEntity::~CBaseEntity
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。
Agent fallback for C_GameRules_vtable (auto-generated, category: func). Locate C_GameRules_vtable in the CS2 client module via IDA Pro MCP and emit a fresh, minimal-unique artifact. The deterministic preprocessor could not resolve this symbol on the current gamever - your job is the re-sign. Trigger: C_GameRules_vtable, C_GameRules_vtable
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。
Agent fallback for CAM_Command_CommandHandler (auto-generated, category: func). Locate CAM_Command_CommandHandler in the CS2 client module via IDA Pro MCP and emit a fresh, minimal-unique artifact. The deterministic preprocessor could not resolve this symbol on the current gamever - your job is the re-sign. Trigger: CAM_Command_CommandHandler, CAM_Command_CommandHandler
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。
Agent fallback for CBaseAnimGraph_GetAnimationController-decompiles (auto-generated, category: func). Locate CBaseAnimGraph::GetAnimationController in the CS2 server module via IDA Pro MCP and emit a fresh, minimal-unique artifact. The deterministic preprocessor could not resolve this symbol on the current gamever - your job is the re-sign. Trigger: CBaseAnimGraph_GetAnimationController-decompiles, CBaseAnimGraph::GetAnimationController
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。
Locate CBaseEntity_EmitSoundFilter_SoundName in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the local gamedata entry "CBaseEntity_EmitSoundFilter_SoundName" (symbol CBaseEntity_EmitSoundFilter_SoundName). The gamedata consumer stores a BYTE SIGNATURE for this entry - ALWAYS emit the func schema (func_sig), never vfunc fields. The function may be virtual; locating it via the owning class vtable (RTTI) is a fine strategy, but once found, read its head bytes and emit func_sig. Locate via cross-references, distinctive constants/strings, callers of related symbols, or vtable slots; verify by decompilation before committing. Trigger: CBaseEntity_EmitSoundFilter_SoundName, CBaseEntity_EmitSoundFilter_SoundName
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。
Agent fallback for Callback_GenericChanged (auto-generated, category: func). Locate Callback_GenericChanged in the CS2 engine module via IDA Pro MCP and emit a fresh, minimal-unique artifact. The deterministic preprocessor could not resolve this symbol on the current gamever - your job is the re-sign. Trigger: Callback_GenericChanged, Callback_GenericChanged
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。
Agent fallback for BotAdd_CommandHandler (auto-generated, category: func). Locate CCSBotManager::BotAddCommand in the CS2 server module via IDA Pro MCP and emit a fresh, minimal-unique artifact. The deterministic preprocessor could not resolve this symbol on the current gamever - your job is the re-sign. Trigger: BotAdd_CommandHandler, CCSBotManager::BotAddCommand
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。
Agent fallback for CBaseEntity_GetChangeAccessorPathInfo_2 (auto-generated, category: vfunc). Locate CBaseEntity::GetChangeAccessorPathInfo_2 in the CS2 server module via IDA Pro MCP and emit a fresh, minimal-unique artifact. The deterministic preprocessor could not resolve this symbol on the current gamever - your job is the re-sign. Trigger: CBaseEntity_GetChangeAccessorPathInfo_2, CBaseEntity::GetChangeAccessorPathInfo_2
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。
Finds what changed in Claude — docs, release notes, changelogs, GitHub and community posts on Claude Code, claude.ai, Cowork, the API and models — and turns each change into adopt rows for your setup, plus a fit card for a new model or feature and a monthly bench of your skills against public skill and plugin repos (build, adopt or skip). Trigger on what changed since a date or version, a weekly sweep, features worth adopting, a feature that broke unannounced, a stale model table, what a new model or feature is good for, or how your skills compare with popular or little-known skill and plugin repos; or say scoutwright (sweep, since, watch, adopt, fit, bench, sources, refresh). Outside research is researchscribe's; applying a row, skillwright's; config, rigwright's; schedules, agentwright's; tier picks, promptwright's.
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。
Finds where every credential on the machine lives, without showing a value. Trigger to list where keys, tokens and passwords are stored (Credential Manager, gh, .env, settings, .mcp.json, Docker); to cut a gh token to least privilege or switch gh accounts; to rotate a key and update its users; after a key was printed, pasted or committed; to check a command that uses a token before it runs; or say keywarden (inventory, scope, rotate, leak, preflight, refresh). Drives op or bw when present. Leak scans and commit email are shieldwarden's; rules and hooks gatewarden's; routine credentials agentwright's; vetting a vault MCP trustwarden's.
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。
Keeps the user's identity and secrets out of anything public. Trigger on what should not be published in a repo, branch, history, diff, PR text, draft or pasted file, to find a home path, email, real or client name, or secret; for a commit's email, a codename or per-repo identity; for injected instructions in skills, hooks or prompts; for artifacts Claude made; for files named like secrets; after a leak, to plan a history rewrite; or say shieldwarden (scan, plan, rewrite, land, after, policy, check, identity, signposts, refresh). Rules and hooks are gatewarden's; rotation and gh sign-in keywarden's; brand words brandscribe's; a skill's own posture skillwright's; schedules agentwright's.
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。
Run convex-doctor static analysis, interpret findings, and fix issues across security, performance, correctness, schema, and architecture categories. Use when running convex-doctor, fixing convex-doctor warnings or errors, improving the convex-doctor score, or when asked about Convex code quality, static analysis, or linting Convex functions.
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。
Audits Convex performance for reads, subscriptions, write contention, and function limits. Use for slow features, insights findings, OCC conflicts, or read amplification.
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。
Find and buy a domain for the current Convex app through Convex, then bind it (labs; spend action).
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。
Read the Convex deployment's 72h insights (read limits, OCC contention), root-cause each event in code, report evidence-backed perf/cost findings with fixes.
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。
Index-based file discovery using ABOUTME headers. Use INSTEAD of grep or Explore agent when searching for files by purpose or feature. Faster and more accurate than scanning code. Invoke this skill when user asks "which files handle X", "where is Y implemented", or when you need to find files related to a feature or task.
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。
[32] ANALYZE. Ensure every critical claim has verifiable evidence with confidence levels. Each fact must have source + confidence percentage. If confidence <85%, enter Loop150 to find more sources. Use for critical decisions, factual claims, legal/compliance work, or any situation where unverified claims are dangerous.
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。
[21] UNDERSTAND. Deep research workflow for this project using 150% scope (100% core + 50% boundary), evidence-based reasoning, and structured investigation notes. Use when the task requires investigation, root-cause analysis, or mapping unknown areas. Always maintain a research log file that captures findings, hypotheses, and next branches; use web.run when external verification is needed.
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。
[22] UNDERSTAND. Deep research from all sources — internal (code, git, logs) AND external (web, docs, best practices). Use when choosing libraries, investigating solutions, understanding legal/technical questions, comparing approaches, or anytime you need comprehensive knowledge from both project context and world knowledge. Triggers on "research", "investigate", "find best approach", "what do others do", "compare options", or complex questions requiring multiple sources.
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。
Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.
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。
Systematically finds and fixes bugs using proven debugging techniques. Traces from symptoms to root cause, implements fixes, and prevents regression.
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。
Enables ultra-granular, line-by-line code analysis to build deep architectural context before vulnerability or bug finding.
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。
Find and evaluate influencers for brand partnerships, verify authenticity, and track collaboration performance across Instagram, Facebook, YouTube, and TikTok.
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。
Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying 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。