bear-counter

by wisp-science

给一句话或一段话，找出真实学术文献来反对它——相反结论、边界条件、替代解释、方法批评、复制失败。按威胁程度排序，每篇附一行"它如何威胁这个观点"和"怎么回应它"。底层走真实检索（scimaster-cli），绝不编造反例。 **以下情况请主动触发本技能**：用户想"提前挡住审稿人"、"找这个结论的反例"、"这个方向有没有争议"、"有没有跟这个相反的研究"、"帮我攻击这个论点"、"这个结论稳不稳"、"想知道有哪些反对意见"——即使用户没有说"bear-counter"，只要意图是**为一个观点寻找学术反对证据**，就使用本技能。bear-support 和 bear-counter 配对使用效果最好：对同一段话各跑一遍，就能同时看到正反两面。不适用于：找支持文献（用 bear-support）、选题查重（用 bear-scoop）、概念地图（用 bear-map）、溯源演化史（用 bear-trace）。

v1.0.0New

#wisp-science

Unsigned, install at your own risk

Unverified

This skill has no cryptographic signature attached. We can't verify the contents match what the publisher intended.

Install this skill

Run this command in your terminal. No account required — it auto-detects your AI tool and installs the skill file.

npx @skills-hub-ai/cli install wisp-science-bear-counter

Or download directly:

Browse all CLI commands →

Setup by platform

Claude Code

~/.claude/skills/<skill>/SKILL.md

Setup guide →

Install

One-click setup for your editor

Run in your project root

npx @skills-hub-ai/cli install wisp-science-bear-counter --target claude-code

Instructions

This skill doesn’t include stateful context yet, instructions only. Learn about stateful skills.

Security

Loading security scan...

Reviews (0)

View full changelog & diffs →

Browse all →

word-zotero-citationsBuild, audit, authorize, recover, or finalize dynamic Zotero citations and bibliographies in Microsoft Word DOCX files with a protected-source, digest-bound workflow. Use for Word–Zotero citation conversion, static OOXML citation audits, mocked/offline validation, Refresh authorization/report review, UI-evidence contracts, run recovery, or rollback proposals; never perform live Word/Zotero integration without separate explicit authorization.0 installs social-noteTurn a scientific conversation, paper takeaway, or figure story into paste-ready social copy. Use when the user asks for 小红书文案, a Xiaohongshu note, 微信/朋友圈, 公众号草稿, a tweet, Twitter/X copy, or share-to-social text from a Wisp session. Ask which platform unless the user already named one.0 installs public-data-accessPlan, validate, and document public-bioinformatics data acquisition for GEO/GSE/GSM/GPL/GDS, SRA/ENA, TCGA/GDC, GTEx, and DepMap. Covers expression matrices, raw reads, download manifests, caches, and optional geokit SOFT/Series Matrix acquisition for R workflows.0 installs bear-map给一个概念，从真实检索到的论文摘要里挖出它的邻近概念，画出以该概念为中心的知识地图——每个节点都锚定真实文献，不从记忆里补节点。同时输出 Mermaid 概念图（可在 Claude Code / GitHub / Obsidian 渲染）和可截图的独立 HTML 地图，再给 3–6 篇入门推荐。 **以下情况请主动触发本技能**：用户说"帮我画一张这个概念的知识地图"、"这个词周围有哪些相关概念"、"梳理一下这个方向的概念网络"、"给我一张概念图"、"这个领域的核心概念有哪些"、"知识地图"、"概念地图"、"map out this concept"、"draw a knowledge map of X"、"what concepts surround X"、"show me the concept network around this term"、"concept map for X"——即使用户没有说"bear-map"，只要意图是**以一个概念为中心，了解它周围的知识版图**，就使用本技能。不适用于：为观点找支持文献（用 bear-support）、找反对文献（用 bear-counter）、选题查重（用 bear-scoop）、溯源演化史（用 bear-trace）。0 installs remote-compute-sshSubmit recoverable SSH-direct research Runs with live progress cards and model-free monitoring.0 installs figure-composerCompose or improve a publication-grade multi-panel scientific figure from a claim, concrete data paths, or an existing image. Use for figure outlining, parallel panel rendering, exact-grid composition, visual inspection, and adversarial figure review. Use figure-style for one standalone plot and paper-narrative for whole-paper figure ordering.0 installs

More from wisp-science

View source →

analysis-workflowOrganize multi-step scientific analyses into reproducible, self-contained modules. Use for workflows such as QC→PCA→DEG→GSEA that produce scripts, inputs, figures, tables, and methods. Creates a stable module layout, records exact inputs/parameters/package and database versions in each module README, keeps large data as references instead of copies, and verifies outputs before completion.0 installs figure-styleCorrectness and legibility checklist for publication figures, plus a matplotlib sidecar. Load before plotting anything and call `apply_figure_style()` (role-mapped font ladder, outward ticks, frameless legends, 300-dpi saves, CJK-safe fonts). Covers data fidelity, label budgets, axis/colour/type rules, chart choice by data shape, composition, and a mandatory render-then-inspect QA pass (bbox collisions + per-panel visual crops). Helpers: focal_palette, bar_with_points, strip_with_median, end_of_line_labels, panel_letter, set_frame, panel_crops. Multi-panel assembly lives in figure-composer; whole-paper figure ordering in paper-narrative.0 installs customizeCreate a Wisp specialist or author a project-local skill using the tools Wisp actually exposes. Use when the user wants a custom Agent persona, a restricted specialist loadout, a new skill, or changes to an existing project-local skill.0 installs figure-duplicate-auditAudit scientific figures for duplicated, reused, transformed, or uninformative image panels. Use for 图片查重, 论文图像重复, PDF figure 审核, when the user attaches a PDF, asks to review selected PDF pages, or tags a directory containing manuscript input images. For PDFs, extract large embedded figure images before splitting them into panels; for directories, preserve originals and split every composite image directly. Produces a reviewed panel manifest, all-pairs candidate table, visual evidence, coverage accounting, and a cautious integrity report.0 installs literature-reviewRetrieve, verify, and synthesize scientific literature. Use for seminal-paper lookups, evidence summaries, method comparisons, and gap analyses. Every citation must come from a live lookup, never from memory; retractions are checked; the deliverable is argued prose with resolvable DOI links.0 installs singlecell-qcUse when designing, reviewing, or implementing single-cell RNA-seq QC in Python or R with a human-in-the-loop, data-driven approach. Trigger for scRNA QC metrics, per-sample diagnosis, threshold discussion, mitochondrial/ambient/doublet assessment, MAD vs fixed cutoffs, or refactoring automated merge-first QC. The analyst confirms key decisions at each step—agents must inspect data, propose options, and wait for approval before filtering, doublet removal, or merging. Not a turnkey pipeline skill.0 installs

More Build skills

Browse category →

ui-design-systemUI design system toolkit for Senior UI Designer including design token generation, component documentation, responsive design calculations, and developer handoff tools. Use when creating design systems, generating design tokens, maintaining visual consistency, or facilitating design-dev collaboration and developer handoff.208 installs senior-frontendFrontend development skill for React, Next.js, TypeScript, and Tailwind CSS applications. Use when building React components, optimizing Next.js performance, analyzing bundle sizes, scaffolding frontend projects, implementing accessibility, or reviewing frontend code quality.146 installs frontend-designGuidance for distinctive, intentional visual design when building new UI or reshaping an existing one. Helps with aesthetic direction, typography, and making choices that don't read as templated defaults.102 installs self-improving-agentCurate Claude Code's auto-memory into durable project knowledge. Analyze MEMORY.md for patterns, promote proven learnings to CLAUDE.md and .claude/rules/, extract recurring solutions into reusable skills. Use when: (1) reviewing what Claude has learned about your project, (2) graduating a pattern from notes to enforced rules, (3) turning a debugging solution into a skill, (4) checking memory health and capacity.81 installs senior-backendDesigns and implements backend systems including REST APIs, microservices, database architectures, authentication flows, and security hardening. Use when the user asks to "design REST APIs", "optimize database queries", "implement authentication", "build microservices", "review backend code", "set up GraphQL", "handle database migrations", or "load test APIs". Covers Node.js/Express/Fastify development, PostgreSQL optimization, API security, and backend architecture patterns.66 installs using-superpowersUse when starting any conversation - establishes how to find and use skills, requiring skill invocation before ANY response including clarifying questions60 installs

Frequently asked questions about bear-counter

What does the bear-counter skill do?

How do I install the bear-counter skill?

Run `npx @skills-hub-ai/cli install wisp-science-bear-counter` from your terminal. The CLI writes the SKILL.md to the correct location for your AI tool (e.g. ~/.claude/skills/wisp-science-bear-counter/ for Claude Code or ~/.cursor/skills/ for Cursor with --target cursor) and adds it to your project's .skills.json lockfile.

Which AI tools does bear-counter work with?

bear-counter runs in Claude Code. It follows the open Agent Skills standard (SKILL.md), so the same skill works in every supported tool without modification.

Is the bear-counter skill free?

Yes. Every skill on skills-hub.ai is free and open-source. There are no premium tiers, paywalls, or usage limits. You only pay for whatever AI assistant you're already using.

How do I use bear-counter after installing it?

In Claude Code, type `/wisp-science-bear-counter` (or whatever slash command the skill registers) and the AI follows the skill's instructions immediately. You can also reference it by name in natural language, your AI loads the skill into context when relevant.

Can I share the bear-counter skill with my team?

Yes. Commit your project's .skills.json lockfile and teammates run `npx @skills-hub-ai/cli install` (no args) to install every skill at the exact version you pinned. Organization-scoped installs work via skills-hub.ai organizations.