Agent skills you can check before you install
Public SKILL.md skills from GitHub repositories with 50+ stars and from the vendors themselves, scanned and scored. Install any of them with one command in Claude Code, Cursor, Codex, GitHub Copilot or Gemini CLI.
49,492 skills from 2,391 repositories · updated 7 hours ago
49,490 skills
- revenue-operationscbrock84/headcountRuns the mechanics of the revenue engine — lead lifecycle definitions, routing, CRM hygiene, forecasting process, pipeline reporting, and the marketing-to-sales handoff. Use this to fix a broken handoff, define lifecycle stages, improve forecast accuracy, clean up CRM data, design territory or routing rules, or diagnose why pipeline numbers are not trusted.DesignNo warnings★ 2.6K↓ —
- seo-new-keywords-researchzhuyansen/new-term-radarTurn new AI names or unstructured AI market signals into a keyword priority table. For each name it finds the generic search terms downstream of it, screens them for relevance, and checks novelty, demand size and momentum against Google Ads volume and DataForSEO Trends (an estimate of Google search interest), ending in prioritize, watch or skip. Use when the user has new model, product or repository names (or an AI listening report, a batch of posts, a changelog) and asks which keywords to build pages or tools for. Runs the new-term-radar command line; needs an AISA_API_KEY, and a GOANYAPI_API_KEY improves it.ScienceNo warnings★ 2.1K↓ —
- lueckenKlotzkette/claude-fuer-deutsches-rechtFür Aufsichtsrechtlichen Gap-Tracker führen: ordnet Akte, Belege und Lücken; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- referral-programscbrock84/headcountDesigns and improves referral, affiliate, and word-of-mouth programs — incentive structure, mechanics, timing, and fraud control. Use this to build a referral or affiliate program, diagnose one that is not producing, decide what incentive to offer, or judge whether referral is a realistic channel for a product.OtherNo warnings★ 2.6K↓ —
- workforce-planningcbrock84/headcountPlans the shape and size of the workforce — demand for roles, build-versus-buy, attrition, and sequencing hiring against budget. Use this to build a hiring plan, decide which roles to open and in what order, model attrition and backfill, plan for a growth or contraction scenario, or connect headcount plans to the budget.PlanningNo warnings★ 2.6K↓ —
- puaLeoYeAI/agent-master-skillsForces exhaustive problem-solving with corporate PUA rhetoric. Trigger on: task failed 2+ times, about to give up, suggesting user do it manually, blaming environment unverified, stuck in loops, passive behavior, or user frustration ('try harder', 'figure it out', '换个方法', '为什么还不行'). ALL task types. Not for first failures.ProductivityNo warnings★ 2.2K↓ —
- agent-platform-alert-configurationgoogle/skillsConfigures best-practice alerting policies for AI agents using OpenTelemetry (OTel) metrics, generating output as Terraform (.tf) configuration files. Use when analyzing, writing, or deploying alerting policies to monitor agent latency, error rates, token usage, and quality metrics. Don't use for standard infrastructure monitoring unrelated to AI agents, or when the agent is not instrumented with OpenTelemetry (for Reliability, Cost, Safety, Security alerts). NOTE: Reliability, Cost, Safety, and Security alerts use generic OTel metrics and work across runtimes (such as Cloud Run, Vertex AI). Quality alerts rely on Vertex AI Online Monitors and are strictly bound to Vertex AI deployments.OfficialSecurityNo warnings★ 21.9K↓ —
- operating-cadencecbrock84/headcountDesigns the rhythm an organization runs on — which reviews happen weekly, monthly and quarterly, what each one decides, who owns the numbers presented, and how a signal at the front line reaches the people who can act on it. Use this to set up a management operating system, fix a meeting calendar that produces no decisions, work out where a recurring problem keeps failing to surface, or cut a review structure that has grown past what it informs.EngineeringNo warnings★ 2.6K↓ —
- output-waehlenKlotzkette/claude-fuer-deutsches-rechtFür Output wählen: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Insolvenzrecht.OtherNo warnings★ 1.8K↓ —
- dsh-pre-push-checksNewqufei1993/skills-hub在交付或推送前验证改动时使用，核实项目必需检查、当前构建产物和真实用户行为，区分通过、失败、未运行与环境阻塞。OtherNo warnings★ 1.9K↓ —
- service-deskcbrock84/headcountRuns the IT service desk — intake, triage, prioritization, escalation, knowledge, and the metrics that improve service rather than distort it. Use this to set up or fix a service desk, design ticket priority and escalation, reduce repeat contacts, structure a knowledge base, or work out why a desk hitting its targets still frustrates everyone.DesignNo warnings★ 2.6K↓ —
- qmdLeoYeAI/agent-master-skillsLocal search/indexing CLI (BM25 + vectors + rerank) with MCP mode.EngineeringNo warnings★ 2.2K↓ —Also in 1 other repo
- tddNewLeoYeAI/agent-master-skillsRun a red-green-refactor TDD workflow — generate failing tests first, implement to green, then check coverage gaps. Usage: /tdd <generate|coverage|validate> [target]TestingNo warnings★ 2.2K↓ —
- fable-loopSahir619/fable-methodEnd-to-end orchestrated workflow that runs a task the way Fable ran sessions - parallel evidence subagents, one committed plan, surgical execution with an intent gate, adversarial verification agents, honest outcome-first report. Use for non-trivial multi-step tasks when the user says "/fable-loop", "run the fable loop", or "do this the way Fable would". For the rules alone without orchestration, use fable-method; for large multi-phase projects, prefer the GSD workflow and use this inside phases.PlanningNo warnings★ 2.3K↓ —
- pua-enLeoYeAI/agent-master-skillsPut your AI on a Performance Improvement Plan. Forces exhaustive problem-solving with Western big-tech performance culture rhetoric and structured debugging. Trigger when: (1) task failed 2+ times or stuck tweaking same approach; (2) about to say 'I cannot', suggest manual work, or blame environment without verifying; (3) being passive—not searching, not reading source, just waiting; (4) user frustration: 'try harder', 'stop giving up', 'figure it out', 'again???', or similar. Also for complex debugging, env issues, config/deployment failures. All task types: code, config, research, writing, deployment, infra, API. Do NOT trigger on first-attempt failures or when a known fix is executing.DevOpsNo warnings★ 2.2K↓ —
- product-discoverycbrock84/headcountFinds out whether a problem is real and a solution would work, before building it — recruiting the right people, interviewing without leading them, separating what users say from what they do, naming the riskiest assumption and testing that one first, and reaching a decision rather than a summary. Use this to validate a problem, test an idea cheaply, decide whether to build something, or fix a discovery process that keeps confirming what the team already believed.TestingNo warnings★ 2.6K↓ —
- fable-judgeSahir619/fable-methodAdversarial verification of finished work. Treats any "done" as a set of claims, then re-runs the claimed verifications, diffs what actually changed, detects weakened tests and false completion claims, and delivers an evidence-based verdict (VERIFIED / VERIFIED WITH CAVEATS / REFUTED). Use after any agent or model claims work is complete - "/fable-judge", "judge this work", "verify what it did", "did that actually work?". Also runs the fable-method trap suite against a skill or model via "/fable-judge suite TARGET".TestingNo warnings★ 2.3K↓ —
- fable-domainSahir619/fable-methodDiscuss a domain with the user, research it from real sources, then generate a trusted skill bundle for it - a step-by-step workflow with a flowchart, a domain adapter, a trap fixture, and a smoke eval. Use when the user says "/fable-domain SECTOR", "make a skill for DOMAIN", "add a domain to the fable method", or "give a lesser model Fable's workflow for DOMAIN". The bundle is the deliverable; a workflow without its flowchart, sources, and trap is not done.ScienceNo warnings★ 2.3K↓ —
- portaljs-new-portaldatopian/portaljsScaffold a new PortalJS data portal from a brief. Copies the canonical template from examples/portaljs-catalog and substitutes project tokens. Use when starting a brand-new data portal project from scratch.OtherNo warnings★ 2.4K↓ —
- portaljs-add-datasetdatopian/portaljsAdd a dataset (CSV, TSV, JSON, or GeoJSON) to an existing PortalJS portal. Appends an entry to datasets.json so the catalog and showcase render it automatically; routes the data by source (local file vs remote URL) — R2 via Git LFS by default, remote URLs by passthrough. Use when registering a new dataset in a scaffolded portal.DataNo warnings★ 2.4K↓ —
- portaljs-connect-ckandatopian/portaljsWire a scaffolded PortalJS portal to a CKAN backend over its API. Generates a tiny server-side fetch client (no runtime dependency) and feeds the /search catalog and /@namespace/slug showcases from CKAN instead of datasets.json. Use when connecting an existing portal to a live CKAN instance instead of a static manifest.EngineeringNo warnings★ 2.4K↓ —
- kaltstart-interviewKlotzkette/claude-fuer-deutsches-rechtFür /kaltstart-interview: routet Rolle, Frist, Unterlagen und Fachschritt; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Produkthaftung und Produktrecht.PlanningNo warnings★ 1.8K↓ —
- portaljs-add-resourcedatopian/portaljsAdd another file (resource) to an EXISTING dataset in a PortalJS portal — a data dictionary, methodology, or an additional data file. Turns a single-file dataset into a multi-resource one; the showcase renders a section per resource. Use when a dataset needs a second file, such as a data dictionary, methodology doc, or an additional period's data.MediaNo warnings★ 2.4K↓ —
- portaljs-add-chartdatopian/portaljsAdd a chart (line, bar, area, pie, or scatter) to a dataset's showcase in a PortalJS portal. Installs recharts, writes a reusable Chart component, and renders it in the showcase Views section. Use when visualizing a dataset already registered in datasets.json.MediaNo warnings★ 2.4K↓ —
pathogen-variant-surveillance
K-Dense-AI/scientific-agent-skills
ScienceUpdated 3 days ago
From the author
Queries public GenSpectrum LAPIS data for pathogen genomic surveillance, current lineage nomenclature, weekly sequence proportions, reporting delays, and descriptive mutation frequencies. Use for variant surveillance, Pango lineage validation, dominant submitted lineages, Nextclade assignment provenance, SARS-CoV-2, influenza/H5N1 clades, RSV, mpox, measles, dengue, or LAPIS queries. Distinguishes sequence prevalence from infection prevalence, clades from genotypes, missing calls from reference matches, and sampling changes from biological growth advantage.
Install
npx skills add K-Dense-AI/scientific-agent-skills --skill pathogen-variant-surveillance -a claude-code
Installs to .claude/skills/pathogen-variant-surveillance/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Download .zip
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
What it can touch
Runs bundled scriptsNo network use seenLicence: MIT
Safety checks on SKILL.md
- Ships scripts we have not reviewedLow
Why 89
Security85
Provenance95
Maintenance100
Licence100
Adoption73
Files (9)
- SKILL.md
- references/lapis-api.md
- references/lineage-nomenclature.md
- references/surveillance-caveats.md
- scripts/lapis_client.py
- scripts/lineage_prevalence.py
- scripts/mutation_profile.py
- scripts/reporting_lag.py
- scripts/resolve_lineage.py