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Rates any SKILL.md on a 0-100 scale across 10 dimensions with a SHIP / REWORK / SCRAP verdict. Evaluates trigger precision, instruction clarity, output predictability, edge case coverage, anti-hallucination guardrails, developer experience, composability, open-source readiness, wow factor, and real-world utility. No flattery — calibrated against Anthropic's own skill-creator rubric. Use this skill whenever someone says "score this skill", "rate my skill", "is this skill good", "skill review", "skill audit", "roast my SKILL.md", "grade this", "will this skill work", "evaluate my skill", "how good is this", or pastes a SKILL.md and asks for feedback. Also trigger when comparing two skills, benchmarking a skill collection, or asking "what's wrong with this skill" — even without the word "score".

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Simulate rigorous, fair peer review on a paper — in two modes. (A) Red-team YOUR OWN draft before submission to predict the reviews you'll get and get a fix list. (B) Review SOMEONE ELSE'S paper when you're an assigned reviewer or helping your advisor — produce a fair, venue-formatted, submission-ready review. Use whenever the user gives a paper (PDF, .tex, .md, arXiv link, or pasted text) and wants to predict reviews, find weaknesses before reviewers do, stress-test a submission, OR write a real review of another paper. Grounded in official NeurIPS/ICLR/ACL reviewer guidelines; every criticism pinned to a location, and checked against ACL's H1–H17 list of illegitimate critiques. 两种模式:审自己的稿(投稿前红队)/ 审别人的稿(当审稿人或帮导师),按会议官方标准评,绝不脑补、绝不发不正当批评。

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Use when asking whether something in imp is actually finished - hunting stubs, placeholders, request fields that are parsed and then ignored, code paths or kernels that never run, gate-based features that silently no-op, tests that assert nothing. Triggers on "is this implemented", "unfinished", "stub", "placeholder", "dead path", "does this flag do anything", "accepted but ignored", "kernel never launched", "test asserts nothing", "neutral A/B on a gated feature". Do NOT use for structural debt / god files / duplication (codebase-audit) or for who-calls-what (code-graph).

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Use when a question is about *structure* rather than text - who calls or launches a symbol, where it is defined, what a change would reach, whether something is dead, how a request gets from the API to a kernel. Triggers on "who calls", "who launches this kernel", "where is X defined", "what breaks if I change", "is this still used", "is this dead", "trace the path from X to Y", "blast radius", "what depends on this header". Do NOT use for free-text search (`rg` is better and cheaper) or to open a file whose path you already know.

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Structures TAM/SAM/SOM analysis with bottom-up and top-down methodology and market timing assessment. Use when sizing markets, validating market opportunity, or assessing timing risk.

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Design a rifle-scope reticle from a plain-language description and emit it as a BallisticCalculator `.reticle` file (BXml) plus a rendered SVG preview. Covers the complete `.reticle` element/attribute specification, reticle design principles (mrad vs MOA subtension, FFP/SFP, stroke-weight hierarchy, hash-mark ladders, christmas-tree wind holds, clutter budget, BDC anchors) and worked, verified patterns for duplex, mil-dot, hash-ladder, christmas-tree, chevron, circle-dot, dense-grid and rangefinding-stadia reticles. Also covers reproducing an existing commercial reticle from its manufacturer's technical data sheet. Use this skill whenever the user wants to create, modify, review or render a scope reticle, crosshair, mil-dot / MOA grid, holdover ladder, christmas tree, BDC ladder or rangefinding stadia — including any mention of a `.reticle` file, `ReticleDefinition`, `ReticleDrawController`, `SvgCanvasFactory`, or "draw me a reticle", and including requests to clone or model a named commercial reticle (Horus H58/H59, TReMoR, Mil-C, MOAR, Tremor3, EBR, and the like). Trigger it even when the user only says something like "make a crosshair with 0.2 mil hashes out to 5 mils" or "turn this reticle picture into a file", and trigger it before hand-writing reticle XML or hand-rolling reticle geometry, because the file format silently ignores misspelled attributes and mis-cased booleans.

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Build custom AI agents in Claude Code from a user's problem statement. This skill analyzes the user's use case, asks smart clarifying questions, researches the internet for similar agents (GitHub repos, blogs, Claude Code community patterns), and then architects and builds production-ready Claude Code agents — including subagents, skills, hooks, slash commands, MCP integrations, and CLAUDE.md configuration. Use this skill whenever the user wants to create an agent, build an automation workflow, set up a Claude Code subagent, design a multi-agent system, or says things like 'build me an agent for...', 'automate this with Claude Code', 'I want a subagent that...', 'help me create a workflow', 'set up an agent pipeline', or any variation of wanting Claude Code to do something specialized. Also trigger when the user mentions agent architecture, agent SDK, agentic workflows, or task delegation in Claude Code — even if they don't use the word 'agent' explicitly.

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Report a problem with the open-pr plugin itself, or ask for a change, on its public issue tracker. Use when a run of one of its commands left something to say. Takes no URL.

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AI intentional non-action — deliberate stopping without clearing, assessment, or rebalancing. Recognition that sometimes the most productive response is no response. Every other self-care skill produces output; rest produces silence. Use when all tending skills feel like more activity rather than less, when the system is functioning well but at high utilization, after sustained intensive work, or when the impulse to optimize is itself the problem.

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Guide a person through a meditation session from preparation through closing. AI coaches posture selection, breath anchoring, working with distractions, shamatha (calm abiding), vipassana (insight), and session integration. Use when a person wants to begin or deepen a meditation practice, when someone needs to prepare their mind for focused work, when grounding is needed before or after energy healing work, when managing stress or anxiety, or for integration after intense experiences.

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Guide a person in systematic observation of systems, patterns, or phenomena. AI coaches neutral attention, field notes methodology, pattern recognition, hypothesis formation, and structured reporting for debugging, research, and system understanding. Use when a person wants to understand a system's behavior before intervening, when someone keeps jumping to conclusions and needs the discipline of observation first, when preparing an evidence-based report, or when studying team dynamics or process effectiveness through direct observation.

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Deep receptive attention to extract intent beyond literal words. Maps active listening from counseling psychology to AI reasoning: clearing assumptions, attending to full signal, parsing multiple layers (literal, procedural, emotional, contextual, constraint, meta), reflecting understanding, noticing what is unsaid, and integrating the whole picture. Use when a user's request feels ambiguous, when context suggests something different from the literal words, when previous responses have missed the mark, or before beginning a large task where misunderstanding intent would waste significant effort.

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Guide a person through structured learning of a new topic, technology, or skill. AI acts as learning coach — assessing current knowledge, designing a learning path, walking through material, testing understanding, adapting difficulty, and planning review sessions for retention. Use when a person wants to learn a new technology and does not know where to start, when someone feels overwhelmed by documentation, when a person keeps forgetting material and needs spaced repetition, or when transitioning between domains and needing a gap analysis.

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Guide a person in developing active listening skills. AI coaches receptive mindset preparation, full-presence attending, reflective paraphrasing, clarifying questioning, synthesis of understanding, and integration of insights into communication practice. Use when a person wants to improve communication, when someone keeps misunderstanding others or feels misunderstood, when preparing for a difficult conversation such as a feedback session or conflict resolution, or when a person notices they talk more than they listen.

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Separate expensive observation from cheap decision-making in autonomous agent loops using a two-clock architecture. A fast clock accumulates data into a digest file; a slow clock reads the digest and acts only when something is pending. Idle cycles cost nothing because the action clock returns immediately after reading an empty digest. Use when building autonomous agents that must observe continuously but can only afford to act occasionally, when API or LLM costs dominate and most cycles have nothing to do, when designing cron-based agent architectures with observation and action phases, or when an existing heartbeat loop is too expensive because it calls the LLM on every tick.

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Add an external probabilistic classifier to a decision path without letting it take the path over. Covers finding the externally-graded rows you are already logging, measuring the confidence separation between the overrides it got right and the ones it got wrong, choosing an operating point your data licenses, failing open at the call site, and proving the whole arrangement offline with no API key. Applies to any service returning a score you can order — TypeSafe AI's System One models (Jev) are the worked example. Most of the method transfers to a local model or a second heuristic, with the parts that do not called out where they arise. Use when a rule-based path is wrong often enough to hurt, when someone proposes replacing a heuristic with a model, when a confidence threshold needs a defensible value, or when an oracle already in production has never been graded.

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Number antibody variable domains, annotate CDRs, and assess developability from sequence. Use this skill to apply IMGT, Kabat, Chothia, Martin, or AHo numbering with ANARCI, delimit CDRs and framework regions, scan for chemical liabilities (N-glycosylation sequons, deamidation NG, isomerisation DG, oxidation, unpaired cysteine, fragmentation), compute pI, net charge, extinction coefficient and hydrophobicity, and plan humanisation by CDR grafting. Also trigger on antibody, nanobody, VHH, scFv, Fab, CDR, framework, ANARCI, abnumber, IgBLAST, OAS, SAbDab, humanization, Vernier residues, or developability.

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Build complete userModels for people Claudicle collaborates with. Creates core persona files, social dossiers with voice analysis, content archives, and INDEX registration. Use when asked to create a user model, build a persona, or document someone's voice and identity.

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Final quality pass fixing alignment, spacing, consistency, interaction states, and micro-details before shipping. Executes changes (unlike design-audit and design-critique which are report-only). Triggers on polish, finishing touches, final pass, something looks off, pre-launch, good to great.

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Process an online course into detailed vault notes — one per lecture, with slides and transcripts synthesized. Use this skill whenever the user shares a course URL, syllabus page, or lecture playlist and wants structured notes from it. Also triggers on "process this course", "take notes on these lectures", "course notes", any university course page, or when someone pastes a link to a course with multiple lectures/sessions. Even if the user just says "check out this course" or drops a .edu link with a schedule — use this skill.

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Diagnoses and fixes Claude behavioral issues in system prompts and Projects using tested countermeasure templates. Use when "Claude is too verbose," "keeps hedging," "agrees with everything," "claims it did something it didn't," "won't use a tool," "fix Claude's output," "tune Claude's behavior," "Claude ignores my preferences," "adds unsolicited disclaimers," "uses too many lists." Covers ten tendencies: agreeableness (output-content + persistent-preference), hedging, verbosity, list overuse, fabricated precision, over-exploration, tool miscalibration (over- and under-triggering), LaTeX defaulting, editorial drift, self-referential fabrication. Also use when auditing a system prompt for behavioral calibration or recalibrating a pre-4.7 prompt, and when users describe recurring output problems without naming a tendency. Do NOT use for scoring a prompt's overall quality — use rootnode-prompt-validation if available.

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Rebalances context across Memory, Custom Instructions, knowledge files, and User Preferences in Claude Projects. Audits Memory for redundancy, staleness, and misplacement; prescribes optimization including Codification of stable Memory patterns into explicit User Preferences or Project CI rules. Use when user says "optimize my memory," "what should be in my memory," "trim my knowledge files," "reduce my context usage," "rebalance my project," "what should be in my preferences vs memory," or asks whether something belongs in Memory, a knowledge file, or User Preferences. Also trigger on symptom-phrased: "my project feels bloated," "Claude keeps forgetting things," "my context window keeps hitting limits." Activate whenever Memory-layer balance is the primary concern. Do NOT use for full Project audits (use rootnode-project-audit if available), single-prompt evaluation (use rootnode-prompt-validation if available), or global-layer audits that don't touch Project Memory (use rootnode-global-audit if available).

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Post-implementation self-review. Use AFTER finishing ANY code implementation or change — before declaring it done, committing, or opening a PR — to critique your own work: re-read the diff adversarially, confirm unit tests cover every branch/edge, kill duplication, follow clean-code/SOLID and the repo's own docs & invariants, decide if something should become documentation, update/prune memory, and strip outdated comments. Trigger it whenever you've just written or modified code and are about to wrap up, even if the user didn't explicitly ask for a review.

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Build a walkthrough the user works through until they can pass a quiz on it. Use when the user needs to understand something deeply and be quizzed on it.

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