Record findings from completed offline human tasks (interviews, observations, outreach) back into the canvas. The re-entry point after /mycelium:handoff.
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。
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概要と使いどころ
Record findings from completed offline human tasks (interviews, observations, outreach) back into the canvas. The re-entry point after /mycelium:handoff.
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。
Entity and relation tracking skill using MCP memory server patterns and local knowledge graph storage. Build persistent knowledge graphs of entities, relationships, and observations across agent sessions. Covers the MCP memory server (@modelcontextprotocol/server-memory), local JSON-based graphs, and entity-relation querying patterns for long-running agents.
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用户需要从可观察的外部信号推断隐藏的内部状态时激活;当需要评估某人或某系统的整体状态但无法直接检测内部时; 当多个外部信号互相矛盾需要综合判断时。 典型触发信号: 用户说"怎么看出来这个人状态怎么样""从表面现象怎么判断内在情况""几个信号互相矛盾该怎么判断"。 不适用于: 可以直接测量/检测的场景(有体检数据、有监控面板、有可量化的指标), 或只有一个信号源且无法交叉验证的情况。
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Observe and assess a garden using a structured sensory protocol adapted from Coordinate Remote Viewing. Covers pre-entry clearing (meditate checkpoint), Stage I gestalt impression, Stage II sensory layer (leaf, stem, root, soil), Stage III pattern recognition with AOL management, and garden health triage matrix (heal checkpoint). Use before any intervention, when plants show stress symptoms, at seasonal transitions, when evaluating a new garden site, during regular health monitoring, or after extreme weather events such as frost or heat waves.
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。
AI intuitive exploration for approaching unknown codebases, problems, or systems without preconceptions. Adapts the Coordinate Remote Viewing protocol to AI investigation: cooldown (clear assumptions), staged data gathering (raw signals → dimensional → analytical), AOL management (separating observations from premature labels), and structured review. Use when investigating an unfamiliar codebase with unknown architecture, debugging a problem where premature hypotheses could mislead, exploring a domain with limited context, or when previous attempts have been led astray by assumptions and "beginner's mind" would be more productive.
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。
Field identification of minerals and ores using hardness, streak, luster, cleavage, crystal habit, and simple chemical tests. Covers the systematic elimination methodology, Mohs scale application, and common ore indicators for precious metals, gemstones, and industrial minerals. Use when encountering an unknown rock or mineral specimen, when prospecting and assessing whether a site shows valuable mineral indicators, when distinguishing ore-bearing rock from barren rock in the field, or when building geological literacy through systematic observation.
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Manage an engagement buffer that ingests, prioritizes, rate-limits, deduplicates, and tracks state for incoming engagement items across platforms. Generates periodic digests and enforces cooldown periods. Composes with du-dum: du-dum sets the observation/action cadence, this skill manages the queue between beats.
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Close out a finished memex milestone slice by writing the handoff trail: update `docs/CONTINUE_HERE.md` §1 current-state and §3 next-slice, tick the `docs/ROADMAP.md` scoreboard (milestone header ✅ + version, `- [x]` items), confirm any new observation is logged (deferring to memex-observe), and propose the git tag plus a `MN Slice X:` commit subject. Use after you finish a milestone slice in the memex repo and before you commit/tag it, when handing the next slice to a fresh session, or whenever CONTINUE_HERE and ROADMAP have drifted behind what actually shipped.
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Fit hidden Markov models using the Baum-Welch (EM) algorithm with model selection, Viterbi decoding for state sequences, and forward-backward probabilities. Use when observations are generated by unobservable latent states, you need to segment a time series into latent regimes (market regimes, speech phonemes, biological sequences), compute sequence probabilities, decode the most likely hidden state path, or compare models with different numbers of hidden states.
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Investigate root causes and manage CAPAs (Corrective and Preventive Actions) for compliance deviations. Covers investigation method selection (5-Why, fishbone, fault tree), structured root cause analysis, corrective vs preventive action design, effectiveness verification, and trend analysis. Use when an audit finding requires a CAPA, when a deviation or incident occurs in a validated system, when a regulatory observation needs a formal response, when a data integrity anomaly requires investigation, or when recurring issues suggest a systemic root cause.
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。
Identify gemstones using optical properties, physical tests, and inclusion analysis. Covers refractive index, specific gravity, pleochroism, spectroscopy indicators, and common simulant detection. Use when identifying an unknown gemstone, verifying a seller's claim about species identity, distinguishing natural stones from simulants or synthetics, building gemological literacy through structured observation, or identifying rough material before cutting to ensure safe handling.
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 ClinicalTrials.gov registry through its version 2 REST API for interventional and observational studies, their phases, enrolment, endpoints, sponsors, and posted results. Use this skill to survey who is developing what against an indication, date a competitor's programme, read primary and secondary outcome measures, find eligibility criteria, and distinguish a study that completed from one that was terminated or withdrawn. Also trigger on ClinicalTrials.gov, NCT number, trial registry, study phase, enrolment, primary outcome measure, recruiting status, trial sponsor, or competitive landscape.
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Execute one bounded read-only Proto UI autonomous-maintenance observation mission. Use for drift hunting, external-oracle comparison, repeatability control, or a no-finding maintenance run. Stop before verification or remediation.
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Freeze one eligible Proto UI autonomous-maintenance candidate into a bounded mission packet and lease. Use before observation when a current request or governed queue supplies scope, oracle, baseline, capability, risk, budget, completion, and stop conditions. Do not observe, verify, repair, or invent a mission.
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。
YC Office Hours — two modes. Startup mode: six forcing questions that expose demand reality, status quo, desperate specificity, narrowest wedge, observation, and future-fit. Builder mode: design thinking brainstorming for side projects, hackathons, learning, and open source. Saves a design doc. Use before /plan-ceo-review or /plan-eng-review.
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。
Behavioral guidelines to reduce common LLM coding mistakes. Derived from Andrej Karpathy's observations. Use ALWAYS when writing, reviewing, or refactoring code. Covers assumption surfacing, simplicity, surgical edits, and goal-driven execution with verification.
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Use when a report or article needs to be split into individual claims before it is graded, cited or used as evidence — the user asks "what does this report actually claim?", "split this into claims", "separate the facts from the judgements", or another skill needs a claim list. Turns one document into five to twelve atomic claims, each typed (observation, attribution, assessment, actor claim, victim disclosure) and anchored to the verbatim sentence it rests on, so every extraction can be checked against the source. Preserves the source's own hedging. Does not grade. Invoked by /quality-of-information-check; its output feeds /ach, /key-assumptions-check, /intelligence-writing, /writing-assessments and /threat-actor-profiling.
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。
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
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"Apply panel data analysis with fixed effects, random effects, and dynamic GMM to exploit longitudinal variation and control for unobserved heterogeneity. Use this skill when the user has repeated observations over time for multiple entities, needs to choose between FE and RE via Hausman test, or when they ask 'how do I control for firm-specific effects', 'fixed or random effects', or 'how to handle endogeneity in panels'.".
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。
Full ASVS 5.0 compliance assessment against a codebase and/or architecture diagrams. Reads all 346 controls from the companion CSV, performs targeted code analysis per control, and produces a complete matrix marked COMPLIANT / NON_COMPLIANT / NOT_RELEVANT — with per-control reasoning and evidence (code snippets, file:line references, diagram observations). Outputs a reviewed CSV matrix and a self-contained HTML evidence report.
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 a task needs the judgment of an Economist — estimating a demand elasticity or causal treatment effect from observational or experimental data, building a cost-benefit or welfare analysis for a policy or pricing decision, forecasting a macro or market aggregate under stated assumptions, or stress-testing whether a "the data shows X" claim survives a confounding-variable check.
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Use when a task needs the judgment of an emergency medicine physician — risk-stratifying an undifferentiated chief complaint against a can't-miss diagnosis, deciding an ED disposition (discharge/observation/admit/transfer) under time and bed pressure, reasoning through EMTALA screening-and-stabilization obligations, or triaging a department under crowding/boarding load.
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Use when a task needs the judgment of an astronomer — calculating exposure time or signal-to-noise for a target, writing the feasibility math for a telescope-time proposal, reducing photometric or spectroscopic data, distinguishing a systematic error floor from statistical noise, or reviewing an observational result for calibration or upper-limit red flags.
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 a task needs the judgment of an Anthropologist/Archeologist working in cultural resource management (CRM) — scoping a Section 106 Phase I identification survey, designing a shovel-test-pit sampling strategy, evaluating National Register of Historic Places eligibility under Criteria A-D, interpreting excavation stratigraphy via a Harris matrix and radiocarbon results, or running the ethnographic field-methods branch (participant observation, informant interviewing) for a cultural-anthropology component of a project.
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。