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Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for GraphQL schemas, persisted queries, RPC manifests, generated clients, OpenAPI drift, hidden operations, and contract-to-handler mismatches. Use when the user asks to inspect GraphQL or RPC requests, compare client contracts to live handlers, recover hidden operations, trace generated clients, or explain how schema or contract drift produces the decisive behavior. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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Provides reverse engineering techniques. Use when the main job is to understand how a compiled, obfuscated, packed, or virtualized target works before exploiting or solving it, including binaries, APKs, WASM, firmware, custom VMs, bytecode, game clients, malware-like loaders, and anti-debug or anti-analysis logic. Do not use it when the vulnerability is already understood and the remaining task is exploitation; use pwn instead. Do not use it for pure web workflows, log or disk forensics, or standalone crypto problems unless reversing the implementation is the real blocker.

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Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for AD CS, certificate templates, enrollment rights, EKUs, SAN controls, PKINIT, certificate mapping, and cert-based privilege paths. Use when the user asks about ESC-style abuse, certificate templates, enrollment agents, EKUs, SAN or subject controls, smartcard or PKINIT logon, CA policy, or how an issued cert turns into accepted privilege. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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How to author one new tdmcp MCP tool the house way — the file shape (XImpl + registerX), the Python-bridge pattern (buildPayloadScript/parsePythonReport over executePythonScript), the result helpers (errorResult/guardTd/jsonResult/structuredResult), fail-forward error handling, ESM/.js + Biome style, and the offline msw unit test that proves it. Load this whenever building, extending, reviewing, or testing a tdmcp tool file under src/tools/** (and its test under tests/unit/**). Use it for every Phase-13 / v0.5.0 feature-build tool and any re-run after a gate failure.

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Reverse-engineer the hook from a viral Threads post or thread URL. Identifies which of the 10 canonical 2026 Threads formulas it uses (warm contrarian, data-point, build-in-public, quote-post, mini-list, relatable, listicle, story, curiosity-gap, how-I teardown), explains why it worked, and returns a blank template mapped to your topic with its primary goal (replies, reposts, likes, quotes). Use to learn from a post you admire. Not for writing your own (use threads-post-writer).

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Identify the source of an image or video frame — TV show episode, movie scene, geographic location, or original publication. This skill should be used when the user asks to identify where an image is from, trace a screenshot back to its source, geolocate a photo, find what show or movie a frame is from, or do a reverse image search. Chains Google Vision, Picarta geolocation, and Gemini in parallel with graceful degradation. Triggers on: reverse image search, identify source, what show is this, where was this taken, trace image, identify video, what movie, which episode, geolocate photo, image source.

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Fix scattered/torn regions in hex-grid simulated annealing layouts that use "competitive flood-fill" (one tile per region per outer iteration). Use when: (1) regions of >20 tiles end up dispersed instead of forming compact blobs, (2) maxDist/sqrt(N) dispersion ratio is 10×+ worse than the ideal compact blob, (3) tiles assigned to one region show up in multiple disconnected fragments across the layout, (4) the visualization has a "trypophobia ring" pattern at the perimeter where some regions spill into a perimeter spiral, (5) an overflow spiral fallback exists in the layout code and frequently kicks in for large regions, (6) bigger regions look worse than smaller ones (small regions stay compact, big ones shred). Root cause: interleaved competitive flood-fill (round-robin one tile at a time across all regions) lets large regions get boxed in by neighbors before they finish growing — the unfilled remainder is dumped into the overflow spiral at the perimeter, far from the seed. Fix: replace with sequential region-by-region BFS — process regions in size-descending order, fully claim each region's N contiguous tiles before moving to the next.

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Launch a product across 56 platforms — generates all copy, tracks submissions, and guides launch day operations. Use this skill whenever someone wants to submit to directories, get backlinks, launch on Product Hunt or Hacker News, run an AppSumo campaign, or needs help getting their product in front of users. Also triggers on: 'I just built something and want people to know', 'how do I get users', 'where can I submit my SaaS', 'get backlinks for my product', 'multi-platform launch', 'directory submissions', 'startup launch playbook', 'submit everywhere', 'launch across platforms'. This is the operational launcher — it does the work. For high-level launch strategy and phased planning, see launch-strategy.

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Ongoing link-building campaigns that raise domain authority and expand a site's KD ceiling beyond what on-page work alone can earn. Use when the user mentions 'off-page SEO', 'link building', 'directory link building', 'backlink campaign', 'listicle placements', 'guest posts', 'outreach targets', 'get listed in listicles', or asks 'how do I get more domain authority'. Generates a prioritized, researched target list across directories, listicles, and guest-post candidates — does NOT submit anything on the user's behalf. Pairs with `mktg-backlink-prospector` agent for parallel research. For a launch-day push (submit to directories, Product Hunt, BetaList), see /startup-launcher. For measured backlink data — referring domains, backlink counts, rank tracking — see /openseo. Distinct from `seo-machine` (on-page programmatic) and `seo-audit` (technical diagnostic). The off-page half of the SEO operation.

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RED-GREEN-MUTATE-KILL MUTANTS-REFACTOR workflow for writing production code. Use before ANY production code change - new features, bug fixes, or behavior changes. Triggers on starting implementation work of any kind. Covers the cycle itself - failing test first, minimum code to pass, mutation verification, refactor assessment. For how to write good tests, see testing. For the refactoring step in detail, see refactoring. TDD is non-negotiable.

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Show recent Claude Code sessions across all projects, so the user can re-enter work after a reboot or context switch. Lists per session the absolute project path, a short summary, where the session stopped, last activity, turn count, git branch, model, and a ready-to-paste resume command; can search sessions by what was said in them, flag projects with uncommitted or unpushed work, and re-open every session at once in new terminal tabs. Use when the user asks "what was I working on", "which projects did I touch recently", "where did I leave off", "list my recent sessions", "how do I get back into that session", "open all my sessions again", "which session did I fix X in", "where do I still have uncommitted work", or invokes /recap. Reads only local files; the default run is instant and offline.

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Builds a personal voice profile so Cowork writes the way you write — not like a generic AI. Use when personalizing your writing style, for capturing your communication patterns and tone, during setup after getting generic-sounding output, when training Cowork to match your voice, or when the user says "teach claude my voice", "my writing style", "output doesn't sound like me", "brand voice", "personalize output", "make it sound like me", "it sounds too formal", "it sounds too robotic", "can cowork match my tone", or "how do I get cowork to write like me".

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Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains.

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"Apply the Technology Acceptance Model (Davis, 1989) and Unified Theory of Acceptance and Use of Technology (Venkatesh et al., 2003) to predict technology adoption. Use this skill when the user needs to evaluate user acceptance of a new system, diagnose adoption barriers, design interventions to improve technology uptake, or when they ask 'why aren't users adopting this', 'what drives technology acceptance', or 'how do we increase adoption rates'.".

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"Apply Service-Dominant Logic (Vargo and Lusch, 2004) and value co-creation principles to reframe exchange and value creation. Use this skill when the user needs to redesign value propositions around service exchange, analyze co-creation dynamics between firms and customers, shift from goods-dominant to service-dominant thinking, or when they ask 'how is value created with customers', 'what is our service logic', or 'how do we enable co-creation'.".

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"Apply pragmatist philosophy (Peirce, James, Dewey) to frame knowledge as instrumental for action, evaluate ideas by their practical consequences, and conduct inquiry as problem-solving. Use this skill when the user needs to bridge theory and practice, evaluate competing theories by their usefulness, employ abductive reasoning to generate hypotheses, or when they ask 'which theory is more useful here', 'how do I move from abstract ideas to actionable knowledge', or 'what practical difference does this distinction make'.".

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"Apply the Elaboration Likelihood Model to design persuasion strategies by matching message type to audience elaboration level. Use this skill when the user needs to craft persuasive communications, choose between argument-based and cue-based messaging, predict attitude durability after a campaign, or when they ask 'why did the message fail to persuade', 'how to change resistant attitudes', or 'should we use data or endorsements'.".

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"Apply behavioral finance theory to identify systematic investor biases and their impact on asset prices. Use this skill when the user needs to analyze irrational market behavior, explain pricing anomalies through cognitive biases, diagnose investor decision errors, or when they ask 'why do investors hold losers too long', 'how does loss aversion affect pricing', or 'what biases drive this market pattern'.".

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"Apply Affordance Theory (Gibson, 1979; Norman, 1988) to analyze the action possibilities that an artifact provides to an actor. Use this skill when the user needs to evaluate technology design from an affordance perspective, identify why users struggle with an interface, analyze IT-enabled organizational change through affordance actualization, or when they ask 'what does this technology afford', 'why can't users figure out this feature', or 'how does technology enable new practices'.".

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"Perform RFM (Recency, Frequency, Monetary) customer segmentation from transaction data. Use this skill when the user needs to segment customers by purchase behavior, identify high-value buyers, design retention campaigns, or prioritize marketing spend by customer value — even if they say 'who are our best customers', 'which customers are at risk of churning', or 'how do we target our marketing'.".

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"Apply action research through Plan-Act-Observe-Reflect cycles and Participatory Action Research (PAR) to generate knowledge while improving practice. Use this skill when the user needs to design practitioner research that integrates inquiry with intervention, facilitate participatory research with stakeholders, structure iterative improvement cycles, or when they ask 'how do I research my own practice', 'how do I involve participants as co-researchers', or 'how do I combine research with practical change'.".

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"Develop brand positioning strategy including positioning statements, perceptual maps, and brand personality/archetype analysis. Use this skill when the user needs to define or refine how their brand is perceived relative to competitors, craft a positioning statement, build a brand identity framework, or map competitive positions — even if they say 'what makes us different', 'our brand feels generic', or 'how do customers see us vs competitors'.".

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"Run conjoint analysis to measure how product attributes drive consumer preferences and willingness to pay. Use this skill when the user needs to quantify feature value trade-offs, estimate willingness to pay for specific features, or optimize product configuration — even if they say 'which features do customers value most', 'willingness to pay for feature X', or 'product attribute trade-offs'.".

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Explain what slushpile is, what each skill does, what order to run them in, where the workspace files live, and how to set up a voice agent. Use when the user asks how slushpile works, what to run next, or how to fix a workspace problem.

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。