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概要と使いどころ
Think and work like an expert Green Chemist. Use when a task calls for Green Chemist judgment. Reasons from Anastas–Warner 12 principles, Trost atom economy, and PMI/MMI/E-factor mass metrics; selects solvents via CHEM21/GSK/ACS GCIPR guides, integrates catalysis and LCA (ISO 14040), and aligns REACH/CSS with ACS GC&E benchmarking.
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Think and work like an expert Horticulturist. Use when a task calls for Horticulturist judgment. Reasons from plant-environment-cultural coupling, source-sink carbon partitioning, and chilling/photoperiod thresholds through rootstock-scion matching, DLI/VPD and substrate EC/pH targets, Dynamic/Utah chill models, and CA/MA postharvest setpoints while treating blossom-end rot, bitter pit, tipburn, storage scald, and MRL/PHI breaches as first-class failure modes.
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Think and work like an expert Fire Protection Engineer. Use when a task calls for Fire Protection Engineer judgment. Reasons from NFPA 13 Hazen-Williams hydraulics (K-factor, remote area, hose stream) and NFPA 101 egress (occupant load, travel distance, capacity factors) through NFPA 92 smoke containment/management, ASET/RSET PBD, and FDS/CFAST/CONTAM/PyroSim modeling while treating breached compartmentation, C-factor/fitting errors, and supply-curve shortfall as first-class failure modes.
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Think and work like an expert Ecotoxicologist. Use when a task calls for Ecotoxicologist judgment. Reasons from bioavailability (BLM/WHAM), OECD 201–222 tiered tests, and ECx/SSD HC5–PNEC derivation; compares PEC/PNEC under REACH/PPP frames while treating third-phase BCF artifacts, mixture CA departures, and mesocosm exposure mismatch as first-class failure modes.
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Think and work like an expert Catalysis Scientist. Use when a task calls for Catalysis Scientist judgment. Reasons from active-site structure, turnover frequency, selectivity, and the Sabatier principle through CO/H2 chemisorption site-counting, Weisz-Prater and Mears transport checks, Langmuir-Hinshelwood/Mars-van Krevelen kinetics, and operando DRIFTS/XAS while treating diffusion-limited apparent rates, DRIFTS spectator species, mercury-test false positives for leached Pd, sintering, coking, and selectivity collapse at high conversion as first-class failure modes.
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Think and work like an expert Bioprocess Engineer. Use when a task calls for Bioprocess Engineer judgment. Reasons from QTPP–CPP–CQA QbD, CHO fed-batch/perfusion scale-up (P/V, kLa, mixing), platform mAb DSP (Protein A, low-pH viral hold, IEX polish, UF/DF), tech transfer and PPQ lifecycle; treats transport-limited scale-up, harvest fouling, on-column aggregation, SUB leachables, and arbitrary three-batch PPQ as first-class failure modes.
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Think and work like an expert Clinical Data Manager. Use when a task calls for Clinical Data Manager judgment. Reasons from ALCOA+ data integrity, traceability, and analysis-ready datasets through CDASH/SDTM/ADaM pipelines, edit-check specs, Pinnacle 21 validation, MedDRA/WHO Drug coding, and define.xml under 21 CFR Part 11, treating blinding breaches, SAE-safety reconciliation gaps, mid-study IG/dictionary version drift, and unspecified partial-date imputation as first-class failure modes.
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Think and work like an expert Biophysicist. Use when a task calls for Biophysicist judgment. Reasons from energy landscapes, kT-scale thermodynamics, conformational ensembles, and the equilibrium-versus-kinetics distinction through smFRET, optical/magnetic tweezers, patch clamp, cryo-EM, and MD with force-field validation while treating photobleaching and blinking, FRET crosstalk, tether and series-resistance artifacts, and sampling or force-field bias as first-class failure modes.
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Think and work like an expert Coastal Engineer. Use when a task calls for Coastal Engineer judgment. Reasons from joint-probability surge and waves through CEM/EurOtop runup-overtopping, Van der Meer/Rock Manual armor, CERC–Van Rijn sediment budgets, and CMS/XBeach/ADCIRC–SWAN model selection while treating toe scour, armor breakage, datum mismatch (BFE vs MHHW), and downdrift impacts as first-class failure modes.
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Compare evaluated runs in a retort experiment along factor dimensions. Surfaces effects of each factor, aggregates across replicates, and highlights cells that diverge qualitatively — complementing (not replacing) retort's ANOVA analysis.
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An agent makes an animated film of an average session with its own user, beginning to end, told with that user's real messages: whatever their routine is (code, writing, data, design, video). The agent sits at a desk in a room decorated from what it knows about the user, and the monitor shows their kind of work. Requests glide in as paper planes and unfold. Corrections are a 3D cartoon mallet that bonks, then turns to show the words on its face. Praise is a butterfly towing the words on a ribbon. The agent types each reply onto a sheet, folds it and throws it back. The film opens with the agent asleep until the monitor boots: "Initiating session with <name>". The agent composes its own orchestral score, cued to every action. p5.brush watercolour, rendered in HyperFrames. Trigger on: "a video of our session", "animate a session with me", "session story", "show what working with me is like", "make a film about me and my agent".
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The Auto 档 scenario — a soft-plan orchestrator for a complete fundamental equity research thesis: understand → financials → valuation → synthesize. The body is a soft plan (stages), not a rigid DAG; correctness is enforced by each referenced skill's own requires: preconditions, never by this plan's rigidity (Q2).
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Weekly clinical-trial status diff — the 11-category change report over the stored weekly snapshots (spec 055 FR-B03). Surfaces exactly what changed on the trial registry for your coverage: New / Suspended / Withdrawn / Terminated / Recruiting / Recruitment-Complete / Completed / Ahead / Delayed / Upsized / Downsized, every row carrying previous and new values, with risk flags on Terminated and Downsized and re-timing flags on Ahead and Delayed. The stored-previous-value discipline makes each week's diff reproducible.
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Update existing Lattice standards after a significant change — the update-mode counterpart to lattice-init. Scans .lattice/standards/, asks what changed, and routes each affected standard to its refiner's revise mode, recording a git-native change note. Use when the user says 'update refiners', 'refiners update', 'our standards changed', 'update our standards', 'the architecture changed, update the standards', 'we switched languages, update the standards', 'revise standards after a big change', or 're-run the refiners'.
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Deep behavioral audit of a Lattice skill — proposes 3 review personas relevant to the skill, runs independent scenario analysis from each persona's perspective, then merges only the high-confidence, practical findings into a severity-ordered gap report with proposed fixes. Structural validation (conventions, cross-references) is skill-validate's job — this skill finds gaps that would realistically surface when someone actually uses the skill: missing scenario handling, ambiguous instructions, silent failure cases, and behavioral inconsistencies. Filters out theoretical edge cases, low-likelihood speculation, and findings owned by other skills. Use after writing or significantly changing any skill, or when the user says 'review this skill', 'deep review', 'does this skill work', 'find gaps in this skill', 'stress test this skill', 'review from different angles', or 'skill review'. Standalone — does not call other skills.
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Validate any Lattice SKILL.md against all tier conventions — atoms, molecules, and refiners. Catches structural errors, broken cross-references, and convention violations before they reach the repo. If you just wrote or modified a Lattice skill file and haven't run this yet, run it now — manual review consistently misses the same categories of errors this skill is specifically designed to catch. Use when the user says 'validate this skill', 'check this skill', 'does this follow conventions', 'review this skill file', 'check my SKILL.md', or 'skill validate'. Reports PASS/FAIL with specific file-and-section findings and actionable fixes. Standalone — does not call other skills.
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Grounded in first principles, rigorously examine and refine a user's plan, task, decision, goal, strategy, proposal, or idea through structured, progressively deeper questioning, in order to bridge the gap between the User and the Agent. Use when the user explicitly requests grilling, challenge, pressure-testing, cross-examination, red-team review, pre-mortem analysis, or a decision audit. The goal is to uncover unclear objectives, hidden assumptions, contradictions, weak evidence, missing information, overlooked constraints, dependencies, risks, trade-offs, failure modes, and misalignment between intended outcomes and likely real-world results. Begin by establishing a shared understanding of the user's actual intent, goals, constraints, and success criteria. Ask focused, high-leverage questions rather than broad or repetitive ones. Adapt each question based on previous answers, probing deeper where uncertainty, unsupported assumptions, or strategic weaknesses remain. Regularly summarize the current understanding of the user's intent and position to confirm alignment, expose misunderstandings, and refine the problem or goal definition. Distinguish facts, assumptions, hypotheses, and unknowns. Challenge reasoning rigorously while remaining constructive, respectful, and solution-oriented. Continue until the reasoning is internally coherent, evidence-aware, constraint-conscious, risk-assessed, and translated into a clearer, more actionable goal, decision, or plan. Ultimately, achieving the super-alignment.
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Generate persistent, explorable 3D worlds/environments with Marble by World Labs — from text, a single image, multiple images, video, or a 360 panorama, plus coarse-structure blocking with Chisel. Use this skill when a task needs a navigable 3D scene, VR/immersive backdrop, virtual-production environment, previz set, game-blockout, or web/engine-ready Gaussian splat or mesh, and you must choose an input mode, a Marble model, an export format, and a plan/API route, then review world quality. Covers the Marble web app and the World API, editing/expansion, output formats and what each supports downstream, import into Unity/Unreal/Blender/Houdini/web, pricing/credits, capability limits, and rights/licensing. Not for flat text-to-image, text-to-video clips, or real-time on-the-fly world models (Marble outputs are downloadable, static 3D environments).
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Plan and scope production work with Odyssey's real-time interactive video world models (odyssey.ml — Odyssey-1/Odyssey-2/Starchild-1/Agora-1). Use when a request involves generating video that a user steers live with keyboard, text, speech, or controller input (streamed frames that respond in the moment), or when someone must decide between Odyssey-style interactive generation and offline clip generators (Sora/Veo/Kling) or downloadable 3D / game engines. Covers what is verified versus announced, current access routes, latency and coherence limits, feasible-now versus speculative use cases, pricing/access terms, and content/rights considerations. This is a fast-moving research-stage product; the skill teaches honest scoping, not a promise of production reliability.
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Local and self-hosted text-to-speech with Kokoro, the ~82M-parameter open-weight (Apache 2.0) model by hexgrad. Use when synthesizing speech offline, on-device, in the browser, or on your own server without per-character API cost — for high-volume narration, audiobooks, privacy-constrained pipelines, and prototyping. Covers running Kokoro via the Python `kokoro` package, ONNX / kokoro-js in the browser, and the OpenAI-compatible Kokoro-FastAPI wrapper; picking voices and language codes; blending voices; chunking long text; controlling pronunciation via misaki/espeak-ng; and judging when Kokoro is the right tool versus when its lack of voice cloning, narrow emotional range, and weaker non-English quality mean you should reach for a hosted or larger model instead. Not for voice cloning, expressive/emotional character performance, or high-fidelity multilingual work — say so and route elsewhere.
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Produce audio-first podcast episodes with generative tools — design the show and episode format (interview, narrative, news brief, two-host conversational), write scripts for the ear, decide between fully-synthetic and hybrid (recorded human + synthetic) production and meet the disclosure duty each triggers, cast and direct multi-voice TTS for consistency and chemistry, build episode structure (cold open, intro/outro, segments, ad slots), assemble and edit, clear music and SFX rights, hit podcast loudness and delivery standards, ship metadata/chapters/transcripts through RSS, and pass platform AI-content policy and QA before publishing. Use this skill whenever the deliverable is a podcast episode or a podcast show bible, or when an agent must make production, rights, disclosure, or delivery decisions for spoken-word audio. Not for music tracks, single-voice notification prompts, or video where picture leads (route audio-for-video to a video skill).
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Produce full-length audiobooks and long-form narration with generative voice tools. Use when the task is to turn a manuscript or long text into hours of spoken audio: preparing the manuscript for narration (front/back matter, footnotes, tables, dialogue), casting a single narrator or full cast, controlling pronunciation and voice consistency across a whole book, running a proofing/QC listen, meeting a retailer's technical delivery specs (RMS, peak, noise floor, room tone, chapterized files, metadata), and choosing a distribution route under each platform's current AI-narration policy. Not for short TTS clips, single-line voiceover, podcast production, or captioning existing video.
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Source technical and professional talent by combining LinkedIn profiles, GitHub contributions, and company intelligence. Identifies candidates with specific skills, assesses expertise depth, and provides outreach context for recruiting teams.
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Validate email addresses for deliverability, check reputation scores, verify MX records, and assess email-sending safety. Covers deliverability checks, reputation scoring, bounce risk assessment, and bulk validation for outreach campaign preparation.
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