Results for “benchling”

Reference for Benchling REST API v2 endpoints, covering authentication, pagination, error handling, and CRUD operations for sequences, entities, containers, and notebook entries.

Scores competitors across nine weighted dimensions with explicit 1–5 rubrics and a tension plot, producing comparable profile cards for competitive analysis.

Install a local rebuttal workspace for academic papers with structured intake, reviewer analysis, and strategy planning to produce venue-compliant author responses.

Researching competitors and shaping positioning: feature matrices, SWOT, benchmarking, positioning maps, battle cards, win/loss, LLM brand visibility. Research only — use for strategy, not code.

Persistent task ledger for agent coordination. Plan multi-step work, checkpoint progress across session boundaries, and coordinate across multiple agents with project pool routing.

Read artifacts from the shared bench — the workspace where desks leave findings, verdicts, and work products for each other and the operator.

Clerk Billing for subscription management - render Clerk's PricingTable and in-app checkout drawer, configure subscription plans, seat-limit plans for B2B, feature entitlements with has(), and billing webhooks. Use for SaaS monetization, plan gating, checkout flows, trials, invoicing, and subscription lifecycle management.

Discover, bet on, track, and settle Hunch prediction markets in natural language with on-chain settlement on Base via x402.

Train or fine-tune sentence-transformers models for retrieval, similarity, clustering, classification, and reranking, with support for bi-encoders, cross-encoders, and sparse encoders.

Benchmark Jetson LLM/VLM serving performance across vLLM, llama.cpp, and Ollama with structured JSON output.

Anchors work at the current moment and places events as spatial distances ahead or behind to improve temporal reasoning.

Facilitates a read-only standup across git worktrees, branches, or PRs to compare changes and produce one consolidation plan.

Use when planning an ICLR project timeline from topic selection through OpenReview submission, discussion, revision, decision, camera-ready, poster, video, and public artifact release. Use when sequencing milestones against the current cycle's OpenReview deadlines, budgeting time for the long public discussion phase, or assigning owners for anonymity audits and reviewer-verifiable evidence paths.

Build serverless background jobs, event-driven workflows, and durable execution with Inngest, without managing queues or workers.

Create exercise directory structures with sections, problems, solutions, and explainers that pass linting. Use when user wants to scaffold exercises, create exercise stubs, or set up a new course section.

Flamingo: A Visual Language Model for Few-Shot Learning

Design loading, skeleton, and progressive content reveal patterns that maintain user confidence and perceived performance.

Replace heavy UX deliverables with hypothesis-driven design, collaborative sketching, and rapid experiments to learn what users actually need.

Alignment

Integrate Honcho memory and social cognition into existing Python or TypeScript codebases. Use when adding Honcho SDK, setting up peers, configuring sessions, implementing the dialectic chat endpoint for AI agents, or wiring Honcho into bot frameworks (nanobot, openclaw, picoclaw, etc).

Shares memory between agents at the representation level by compacting the orchestrator's KV cache for efficient worker handoff, reducing token costs without summarization or retrieval.

Generate a scaffolded sequence of practice problems with graduated difficulty and strategic variability. Use when creating worksheets, homework sets, or independent practice materials.

Extends effective context capacity through strategic compression, masking, caching, and partitioning techniques.

Creates a structured, queryable snapshot of a domain's current state, capturing entities, relationships, and properties with confidence scores and evidence anchors.

Guide cross-functional teams through creating Jeff Gothelf's Lean UX Canvas v2 to frame business problems, surface assumptions, and define experiments.

Audit, write, or update CHANGELOG.md following Keep a Changelog 1.1.0. Use when creating a CHANGELOG, or reviewing commits to ensure Unreleased reflects user-visible changes. Defers to auto-managed setups (changesets, release-please, git-cliff, semantic-release, towncrier) and applies semver 2.0.0 — or Haskell PVP for Haskell projects.

Build and debug Retrieval-Augmented Generation pipelines — chunking, embedding, retrieval, reranking

Produces a one-page lean canvas across nine interlocking blocks (problem, customer, UVP, solution, channels, revenue, cost, metrics, unfair advantage) with optional inline HTML and SVG visual rendering. Use when framing a new product thesis, stress-testing an existing strategy, comparing strategic options side-by-side, or aligning a team on business-model assumptions. Works as a strategic hub that cross-links to deeper PM skills without duplicating them.

Cognitive enhancement toolkit combining non-linear reasoning, mental models, and literate programming. Use for complex analysis, system design, debugging, deep learning, and research workflows.

Offload sub-tasks to other agents, specialist models, or background jobs, with guidance on choosing the right method and verifying results.

Models cascading what-if scenarios across all business functions to prepare for compound adversity, using a structured six-step framework that maps variables, domain impacts, cascade effects, severity levels, early warning signals, and hedging strategies.

Building engineer self-branding by turning technical contributions into a professional brand. Use for GitHub/LinkedIn/blog/conference positioning or content strategy.

Run structured competitive analysis with feature matrices, SWOT, pricing comparison, review mining, and positioning maps using the inference.sh CLI.

Write compelling B2B case studies using the STAR framework, with research, data visualization, and distribution formats.

基于 anchor 论文、topic 关键词或当前 wiki 状态，产出一份排好序的候选论文 shortlist，供用户或上游 skill 决定是否进一步 `/ingest`。当用户问 "接下来该读什么"、"找和这篇相似的论文"、"推荐相关工作"、"这个方向周围有什么" 时触发；`/ingest --discover` 也会内部调用本 skill。本身不 ingest，只提出候选。