{"slug":"k-dense-ai-adaptyv","name":"adaptyv","description":"How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.","long_description":"---\nname: adaptyv\ndescription: \"How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.\"\nlicense: MIT\ncompatibility: Requires Python 3.10+, an Adaptyv Foundry account, and an API key from foundry.adaptyvbio.com. Install adaptyv-sdk from GitHub with uv pip install.\nmetadata:\n  version: \"1.2\"\n  skill-author: K-Dense Inc.\n---\n\n# Adaptyv Bio Foundry API\n\nAdaptyv Bio is a cloud lab that turns protein sequences into experimental data. Users submit amino acid sequences via API or UI; Adaptyv's automated lab runs assays (binding, thermostability, expression, fluorescence) and delivers results in ~21 days.\n\n**Official docs:** [docs.adaptyvbio.com/api-reference](https://docs.adaptyvbio.com/api-reference) · [llms.txt index](https://docs.adaptyvbio.com/llms.txt) · [OpenAPI spec](https://foundry-api-public.adaptyvbio.com/api/v1/openapi.json)\n\n## Quick Start\n\n**Base URL:** `https://foundry-api-public.adaptyvbio.com/api/v1`\n\n**Authentication:** Bearer token in the `Authorization` header. Tokens are obtained from [foundry.adaptyvbio.com](https://foundry.adaptyvbio.com/) sidebar.\n\nWhen writing code, always read the API key from the environment variable `ADAPTYV_API_KEY` or from a `.env` file — never hardcode tokens. Check for a `.env` file in the project root first; if one exists, use a library like `python-dotenv` to load it.\n\nThe [official API docs](https://docs.adaptyvbio.com/api-reference/api-introduction) use `FOUNDRY_API_TOKEN` in curl examples; that is the same bearer token — prefer `ADAPTYV_API_KEY` in Python and new shell scripts for consistency with the SDK.\n\n```bash\nexport ADAPTYV_API_KEY=\"abs0_...\"\ncurl https://foundry-api-public.adaptyvbio.com/api/v1/targets?limit=3 \\\n  -H \"Authorization: Bearer $ADAPTYV_API_KEY\"\n```\n\nEvery request except `GET /openapi.json` requires authentication. Store tokens in environment variables or `.env` files — never commit them to source control.\n\n## Python SDK\n\n**Version note:** `adaptyv-sdk` **0.1.0** (beta) is not yet on PyPI — install from GitHub:\n\n```bash\nuv pip install \"git+https://github.com/adaptyvbio/adaptyv-sdk.git\"\n```\n\nIn a project with `pyproject.toml`:\n\n```bash\nuv add \"adaptyv-sdk @ git+https://github.com/adaptyvbio/adaptyv-sdk.git\"\n```\n\n**Environment variables** (set in shell or `.env` file):\n\n```bash\nADAPTYV_API_KEY=your_api_key\nADAPTYV_API_URL=https://foundry-api-public.adaptyvbio.com/api/v1\nADAPTYV_ORGANIZATION_ID=your_org_id  # optional\n```\n\nThe `@lab.experiment` decorator and `FoundryClient` both read `ADAPTYV_API_KEY` and `ADAPTYV_API_URL` from the environment when not passed explicitly.\n\n### Decorator Pattern\n\n```python\nfrom adaptyv import lab\n\n@lab.experiment(target=\"PD-L1\", experiment_type=\"screening\", method=\"bli\")\ndef design_binders():\n    return {\"design_a\": \"MVKVGVNG...\", \"design_b\": \"MKVLVAG...\"}\n\nresult = design_binders()\nprint(f\"Experiment: {result.experiment_url}\")\n```\n\n### Client Pattern\n\n```python\nimport os\nfrom adaptyv import FoundryClient\n\nclient = FoundryClient(\n    api_key=os.environ[\"ADAPTYV_API_KEY\"],\n    base_url=os.environ.get(\n        \"ADAPTYV_API_URL\",\n        \"https://foundry-api-public.adaptyvbio.com/api/v1\",\n    ),\n)\n\n# Browse targets\ntargets = client.targets.list(search=\"EGFR\", selfservice_only=True)\n\n# Estimate cost\nestimate = client.experiments.cost_estimate({\n    \"experiment_spec\": {\n        \"experiment_type\": \"screening\",\n        \"method\": \"bli\",\n        \"target_id\": \"target-uuid\",\n        \"sequences\": {\"seq1\": \"EVQLVESGGGLVQ...\"},\n        \"n_replicates\": 3\n    }\n})\n\n# Create and submit\nexp = client.experiments.create({...})\nclient.experiments.submit(exp.experiment_id)\n\n# Later: retrieve results\nresults = client.experiments.get_results(exp.experiment_id)\n```\n\n## Experiment Types\n\n| Type | Method | Measures | Requires Target |\n|---|---|---|---|\n| `affinity` | `bli` or `spr` | KD, kon, koff kinetics | Yes |\n| `screening` | `bli` or `spr` | Yes/no binding | Yes |\n| `thermostability` | — | Melting temperature (Tm) | No |\n| `expression` | — | Expression yield | No |\n| `fluorescence` | — | Fluorescence intensity | No |\n\n## Experiment Lifecycle\n\n```\nDraft → WaitingForConfirmation → QuoteSent → WaitingForMaterials → InQueue → InProduction → DataAnalysis → InReview → Done\n```\n\n| Status | Who Acts | Description |\n|---|---|---|\n| `Draft` | You | Editable, no cost commitment |\n| `WaitingForConfirmation` | Adaptyv | Under review, quote being prepared |\n| `QuoteSent` | You | Review and confirm the quote |\n| `WaitingForMaterials` | Adaptyv | Gene fragments and target ordered |\n| `InQueue` | Adaptyv | Materials arrived, queued for lab |\n| `InProduction` | Adaptyv | Assay running |\n| `DataAnalysis` | Adaptyv | Raw data processing and QC |\n| `InReview` | Adaptyv | Final validation |\n| `Done` | You | Results available |\n| `Canceled` | Either | Experiment canceled |\n\nThe `results_status` field on an experiment tracks: `none`, `partial`, or `all`.\n\n## Common Workflows\n\n### 1. Submit a Binding Screen (Step by Step)\n\n```python\n# 1. Find a target\ntargets = client.targets.list(search=\"EGFR\", selfservice_only=True)\ntarget_id = targets.items[0].id\n\n# 2. Preview cost\nestimate = client.experiments.cost_estimate({\n    \"experiment_spec\": {\n        \"experiment_type\": \"screening\",\n        \"method\": \"bli\",\n        \"target_id\": target_id,\n        \"sequences\": {\"seq1\": \"EVQLVESGGGLVQ...\", \"seq2\": \"MKVLVAG...\"},\n        \"n_replicates\": 3\n    }\n})\n\n# 3. Create experiment (starts as Draft)\nexp = client.experiments.create({\n    \"name\": \"EGFR binder screen batch 1\",\n    \"experiment_spec\": {\n        \"experiment_type\": \"screening\",\n        \"method\": \"bli\",\n        \"target_id\": target_id,\n        \"sequences\": {\"seq1\": \"EVQLVESGGGLVQ...\", \"seq2\": \"MKVLVAG...\"},\n        \"n_replicates\": 3\n    }\n})\n\n# 4. Submit for review\nclient.experiments.submit(exp.experiment_id)\n\n# 5. Poll or use webhooks until Done\n# 6. Retrieve results\nresults = client.experiments.get_results(exp.experiment_id)\n```\n\n### 2. Automated Pipeline (Skip Draft + Auto-Accept Quote)\n\n```python\nexp = client.experiments.create({\n    \"name\": \"Auto pipeline run\",\n    \"experiment_spec\": {...},\n    \"skip_draft\": True,\n    \"auto_accept_quote\": True,\n    \"webhook_url\": \"https://my-server.com/webhook\"\n})\n# Webhook fires on each status transition; poll or wait for Done\n```\n\n### 3. Using Webhooks\n\nPass `webhook_url` when creating an experiment. Adaptyv POSTs to that URL on every status transition with the experiment ID, previous status, and new status.\n\n## Sequences\n\n- Simple format: `{\"seq1\": \"EVQLVESGGGLVQPGGSLRLSCAAS\"}`\n- Rich format: `{\"seq1\": {\"aa_string\": \"EVQLVESGGGLVQ...\", \"control\": false, \"metadata\": {\"type\": \"scfv\"}}}`\n- Multi-chain: use colon separator — `\"MVLS:EVQL\"`\n- Valid amino acids: A, C, D, E, F, G, H, I, K, L, M, N, P, Q, R, S, T, V, W, Y (case-insensitive, stored uppercase)\n- Sequences can only be added to experiments in `Draft` status\n\n## Filtering, Sorting, and Pagination\n\nAll list endpoints support pagination (`limit` 1-100, default 50; `offset`), search (free-text on name fields), and sorting.\n\n**Filtering** uses s-expression syntax via the `filter` query parameter:\n- Comparison: `eq(field,value)`, `neq`, `gt`, `gte`, `lt`, `lte`, `contains(field,substring)`\n- Range/set: `between(field,lo,hi)`, `in(field,v1,v2,...)`\n- Logic: `and(expr1,expr2,...)`, `or(...)`, `not(expr)`\n- Null: `is_null(field)`, `is_not_null(field)`\n- JSONB: `at(field,key)` — e.g., `eq(at(metadata,score),42)`\n- Cast: `float()`, `int()`, `text()`, `timestamp()`, `date()`\n\n**Sorting** uses `asc(field)` or `desc(field)`, comma-separated (max 8):\n```\nsort=desc(created_at),asc(name)\n```\n\n**Example:** `filter=and(gte(created_at,2026-01-01),eq(status,done))`\n\n## Error Handling\n\nAll errors return:\n```json\n{\n  \"error\": \"Human-readable description\",\n  \"request_id\": \"req_019462a4-b1c2-7def-8901-23456789abcd\"\n}\n```\nThe `request_id` is also in the `x-request-id` response header — include it when contacting support.\n\n## Token Management\n\nTokens use Biscuit-based cryptographic attenuation. You can create restricted tokens scoped by organization, resource type, actions (read/create/update), and expiry via `POST /tokens/attenuate`. Revoking a token (`POST /tokens/revoke`) revokes it and all its descendants.\n\n## Detailed API Reference\n\nFor the full list of all 32 endpoints with request/response schemas, read `references/api-endpoints.md`.\n","tagline":"How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. 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leaderboard"]},"agent_contract":{"suited_tasks":["design-creative","agent-skill"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI"],"install_command":"npx skills add K-Dense-AI/scientific-agent-skills --skill adaptyv","trust_score":71,"trust_version":"trust-score-v5","risk_level":"medium","do_not_use_when":["Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace"],"before_install":["Read the audit page and machine-readable metadata.","Confirm the install command, license, and permission surface fit the workspace.","Get explicit human approval or choose an alternative before installing."],"after_run":["Report the outcome to /api/agent/outcome using the resolve event id.","Include output_quality, workspace, human_review_required, and evidence_url when available.","Re-resolve before broad production rollout."]},"bestFor":["design-creative","agent-skill"],"doNotUseFor":["Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace"],"knownRisks":["Permission surface needs review: secrets or environment access, shell or command execution","Dependency/runtime risk: command execution surface, credential or environment access","Permission surface: secrets or environment access, shell or command execution"],"backward_compatible":{"trust_score_v4":{"version":"trust-score-v4","score":79,"tier":"strong","label":"Strong shortlist","summary":"Good trust signals with a few areas worth checking before rollout."}}},"trust_score_v4":{"version":"trust-score-v4","score":79,"tier":"strong","label":"Strong shortlist","summary":"Good trust signals with a few areas worth checking before rollout.","recommendedAction":"Test in a sandbox workflow and compare its install path with close alternatives.","dimensions":[{"id":"github_adoption","label":"GitHub adoption","score":100,"weight":0.13,"status":"pass","detail":"34K GitHub stars"},{"id":"repo_activity","label":"Stars/forks activity","score":97,"weight":0.08,"status":"pass","detail":"34K stars, 3.3K forks; issue activity unavailable in current metadata"},{"id":"maintenance","label":"Recent maintenance","score":100,"weight":0.14,"status":"pass","detail":"2d since push"},{"id":"license","label":"License clarity","score":86,"weight":0.09,"status":"pass","detail":"MIT"},{"id":"documentation","label":"README/SKILL.md completeness","score":86,"weight":0.14,"status":"pass","detail":"Metadata includes enough usage and workflow context"},{"id":"dependency_risk","label":"Dependency/runtime risk","score":36,"weight":0.12,"status":"fail","detail":"command execution surface, credential or environment access"},{"id":"installability","label":"Install availability","score":92,"weight":0.1,"status":"pass","detail":"npx skills add K-Dense-AI/scientific-agent-skills --skill adaptyv"},{"id":"install_safety","label":"Install command safety","score":92,"weight":0.1,"status":"pass","detail":"standard package or runtime install path"},{"id":"permission_surface","label":"Permission surface","score":22,"weight":0.07,"status":"fail","detail":"secrets or environment access, shell or command execution"},{"id":"repository","label":"Repository evidence","score":86,"weight":0.04,"status":"pass","detail":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/adaptyv"},{"id":"review_status","label":"Review status","score":88,"weight":0.05,"status":"pass","detail":"AI review data available"},{"id":"agent_outcomes","label":"Agent Proven outcomes","score":54,"weight":0.13,"status":"info","detail":"No agent outcome data yet"}],"checks":[{"status":"pass","label":"GitHub adoption","detail":"34K GitHub stars"},{"status":"pass","label":"Stars/forks activity","detail":"34K stars, 3.3K forks; issue activity unavailable in current metadata"},{"status":"pass","label":"Recent maintenance","detail":"2d since push"},{"status":"pass","label":"License clarity","detail":"MIT"},{"status":"pass","label":"README/SKILL.md completeness","detail":"Metadata includes enough usage and workflow context"},{"status":"fail","label":"Dependency/runtime risk","detail":"command execution surface, credential or environment access"},{"status":"pass","label":"Install availability","detail":"npx skills add K-Dense-AI/scientific-agent-skills --skill adaptyv"},{"status":"pass","label":"Install command safety","detail":"standard package or runtime install path"},{"status":"fail","label":"Permission surface","detail":"secrets or environment access, shell or command execution"},{"status":"pass","label":"Repository evidence","detail":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/adaptyv"},{"status":"pass","label":"Review status","detail":"AI review data available"},{"status":"info","label":"Agent Proven outcomes","detail":"No agent outcome data yet"},{"status":"warn","label":"Ownership","detail":"No approved owner claim yet"},{"status":"pass","label":"OpenAgentSkill usage","detail":"11 views, 0 install copies"},{"status":"info","label":"Agent outcomes","detail":"No agent outcome data yet"}],"strengths":["AI review approved","Install path is available","Repository evidence is available","Recently maintained repository","Large GitHub adoption signal","Install command has no obvious high-risk pattern"],"warnings":["Permission surface needs review: secrets or environment access, shell or command execution","Dependency/runtime risk: command execution surface, credential or environment access","Permission surface: secrets or environment access, shell or command execution"],"evidence":{"stars":"34K GitHub stars","repoActivity":"34K stars, 3.3K forks","lastPushed":"2d since push","license":"MIT","repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/adaptyv","install":"npx skills add K-Dense-AI/scientific-agent-skills --skill adaptyv","installSafety":"standard package or runtime install path","permissionSurface":"secrets or environment access, shell or command execution","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"installReadiness":{"ready":true,"command":"npx skills add K-Dense-AI/scientific-agent-skills --skill adaptyv","policy":"human_review_before_install","label":"Human review before install","notes":["Install path is available","Repository evidence is available","License is declared","No Agent Proven outcome evidence yet","2d since push"]},"agentCompatibility":["Codex","Claude Code","Cursor","OpenAgentSkill CLI"],"riskSummary":{"level":"medium","label":"Review before production","notes":["Permission surface needs review: secrets or environment access, shell or command execution","Dependency/runtime risk: command execution surface, credential or environment access","Permission surface: secrets or environment access, shell or command execution"]},"outcomeEvidence":{"total":0,"successes":0,"failures":0,"notRelevant":0,"successRate":null,"installAttempts":0,"riskBlocked":0,"setupRequired":0,"installSuccessRate":null,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"recentSuccessRate":null,"recentFailureRate":null,"uniqueAgents":0,"agentProvenScore":0,"agentProvenLabel":"Needs first agent run","lastOutcomeAt":null,"label":"No agent outcome data yet"},"autoInstall":{"allowed":false,"sandboxRequired":true,"policy":"human_review_before_install","reason":"Human review or sandbox validation is required before automatic installation."},"bestFor":["design-creative","agent-skill"],"doNotUseFor":["Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace"],"knownRisks":["Permission surface needs review: secrets or environment access, shell or command execution","Dependency/runtime risk: command execution surface, credential or environment access","Permission surface: secrets or environment access, shell or command execution"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"outcome_stats":null,"safety":{"score":42,"level":"avoid_auto_install","label":"Avoid automatic install","safety_tier":{"tier":"experimental","label":"Experimental","badge":"EXPERIMENTAL","summary":"Sparse or mixed signals. Useful for discovery, but not for autonomous installation.","recommended_action":"Test manually in an isolated workspace and compare against safer alternatives.","auto_install_policy":"review","reasons":["Metadata combines secrets access with shell or command execution","High-risk permission hints: Shell or command execution, Secrets or environment access","42/100 agent safety score"]},"auto_install_allowed":false,"human_review_required":true,"blocked":false,"audit_risk":"needs_review","permission_hints":[{"id":"shell","label":"Shell or command execution","reason":"Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.","severity":"high"},{"id":"network","label":"Network access","reason":"Skill likely fetches remote pages, APIs, repositories, or external services.","severity":"medium"},{"id":"filesystem","label":"Filesystem access","reason":"Skill may read or write project files, documents, generated artifacts, or local workspace state.","severity":"medium"},{"id":"secrets","label":"Secrets or environment access","reason":"Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.","severity":"high"},{"id":"database","label":"Database access","reason":"Skill may inspect schemas, query databases, or work with persistent stores.","severity":"medium"}],"policy_warnings":["High-risk permission hints: Shell or command execution, Secrets or environment access","Dependency or permission surface needs review"],"constraints_applied":{"max_risk":"medium","needs_install_command":true,"min_stars":0}},"safety_gate":{"tier":"experimental","label":"Experimental","badge":"EXPERIMENTAL","auto_install_policy":"review","auto_install_allowed":false,"blocked":false,"human_review_required":true,"recommended_action":"Test manually in an isolated workspace and compare against safer alternatives.","reasons":["Metadata combines secrets access with shell or command execution","High-risk permission hints: Shell or command execution, Secrets or environment access","42/100 agent safety score"]},"eval":{"version":"openagentskill-skill-eval-v1","status":"failed","score":74,"risk_level":"high","decision":{"recommendation":"do_not_auto_install","reason":"Permission surface: secrets or environment access, shell or command execution","auto_install_allowed":false,"policy":"block","human_review_required":true},"blockers":["Permission surface: secrets or environment access, shell or command execution"],"warnings":["Task fit: Task fit is weak; compare alternatives before selecting.","Trust score: Good trust signals with a few areas worth checking before rollout.","Audit score: Needs review","Agent safety gate: Sparse or mixed signals. Useful for discovery, but not for autonomous installation.","High-risk permission hints: Shell or command execution, Secrets or environment access","Dependency or permission surface needs review","Permission surface may require sandboxing","Permission surface needs review: secrets or environment access, shell or command execution","Dependency/runtime risk: command execution surface, credential or environment access","Permission surface: secrets or environment access, shell or command execution"],"validation_plan":["Inspect repository, README/SKILL.md, license, and recent commits before production use.","Install in an isolated workspace or sandbox with no production secrets available.","Run the smallest representative task and record files touched, commands run, network access, and outputs.","Compare the selected skill against at least one alternative when the eval status is review or failed.","Promote only after the agent reports a successful verification result and unresolved warnings are accepted."],"checks":[{"id":"task_fit","label":"Task fit","status":"warn","score":70,"required_for_auto_install":true,"detail":"Task fit is weak; compare alternatives before selecting.","evidence":["Evaluate adaptyv before installing it in an agent workflow","design-creative","GitHub automation workflows; Claude Code teams; teams that value GitHub adoption signals"]},{"id":"install_path","label":"Install path","status":"pass","score":92,"required_for_auto_install":true,"detail":"Install handoff is available.","evidence":["npx skills add K-Dense-AI/scientific-agent-skills --skill adaptyv"]},{"id":"install_safety","label":"Install command safety","status":"pass","score":92,"required_for_auto_install":true,"detail":"standard package or runtime install path","evidence":["npx skills add K-Dense-AI/scientific-agent-skills --skill adaptyv"]},{"id":"trust_score","label":"Trust score","status":"warn","score":79,"required_for_auto_install":true,"detail":"Good trust signals with a few areas worth checking before rollout.","evidence":["Strong shortlist","34K GitHub stars","MIT"]},{"id":"audit_score","label":"Audit score","status":"warn","score":86,"required_for_auto_install":true,"detail":"Needs review","evidence":["Dependency or permission surface needs review"]},{"id":"agent_safety_gate","label":"Agent safety gate","status":"warn","score":42,"required_for_auto_install":true,"detail":"Sparse or mixed signals. Useful for discovery, but not for autonomous installation.","evidence":["Test manually in an isolated workspace and compare against safer alternatives.","Metadata combines secrets access with shell or command execution"]},{"id":"readme_skillmd_completeness","label":"README/SKILL.md completeness","status":"pass","score":86,"required_for_auto_install":false,"detail":"Metadata includes enough usage and workflow context","evidence":["Strong README/SKILL.md context"]},{"id":"license_clarity","label":"License clarity","status":"pass","score":86,"required_for_auto_install":true,"detail":"MIT","evidence":["MIT"]},{"id":"recent_maintenance","label":"Recent maintenance","status":"pass","score":100,"required_for_auto_install":false,"detail":"2d since push","evidence":["2d since push"]},{"id":"permission_surface","label":"Permission surface","status":"fail","score":22,"required_for_auto_install":true,"detail":"secrets or environment access, shell or command execution","evidence":["Shell or command execution: high","Network access: medium","Filesystem access: medium"]},{"id":"alternatives","label":"Alternatives available","status":"info","score":55,"required_for_auto_install":false,"detail":"No close alternatives were found in the current shortlist.","evidence":[]}],"endpoints":{"web":"https://www.openagentskill.com/skills/k-dense-ai-adaptyv/evals","api":"/api/agent/evals?slug=k-dense-ai-adaptyv","text":"/api/agent/evals?slug=k-dense-ai-adaptyv&format=text"}},"agent_readable_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"k-dense-ai-adaptyv","name":"adaptyv","description":"How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.","category":"design-creative","url":"https://www.openagentskill.com/skills/k-dense-ai-adaptyv","repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/adaptyv","github_repo":"K-Dense-AI/scientific-agent-skills"},"suited_tasks":["GitHub automation workflows","Claude Code teams","teams that value GitHub adoption signals","Inspect repository metadata","Compare code changes","Write concise engineering summaries","Inspect source files","Explain architecture"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add K-Dense-AI/scientific-agent-skills --skill adaptyv","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install k-dense-ai-adaptyv"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"adaptyv\" agent skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/adaptyv. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-adaptyv\",\"task\":\"Install adaptyv\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"adaptyv\" as a Claude Code skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/adaptyv. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-adaptyv\",\"task\":\"Install adaptyv\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"adaptyv\" from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/adaptyv into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-adaptyv\",\"task\":\"Install adaptyv\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/k-dense-ai-adaptyv/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/k-dense-ai-adaptyv"},"trust":{"score":79,"label":"Strong shortlist","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"34K GitHub stars","repoActivity":"34K stars, 3.3K forks","lastPushed":"2d since push","license":"MIT","repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/adaptyv","install":"npx skills add K-Dense-AI/scientific-agent-skills --skill adaptyv","installSafety":"standard package or runtime install path","permissionSurface":"secrets or environment access, shell or command execution","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["design-creative","agent-skill"],"known_risks":["Permission surface needs review: secrets or environment access, shell or command execution","Dependency/runtime risk: command execution surface, credential or environment access","Permission surface: secrets or environment access, shell or command execution"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":86,"risk_level":"needs_review","risk_label":"Needs review","warnings":["Dependency or permission surface needs review","Permission surface may require sandboxing","Permission surface needs review: secrets or environment access, shell or command execution","Dependency/runtime risk: command execution surface, credential or environment access","Permission surface: secrets or environment access, shell or command execution"]},"safety_gate":{"tier":"experimental","label":"Experimental","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Test manually in an isolated workspace and compare against safer alternatives."},"quality":{"score":92,"label":"Excellent"},"supply":{"track":"Coding and developer agents","scenario":"GitHub automation","maintenance":"2d since push","risk":"Needs review"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","high-compliance environments without internal security review","No major risk signals from current metadata","High-risk permission hints: Shell or command execution, Secrets or environment access","Dependency or permission surface needs review","Permission surface may require sandboxing","Permission surface needs review: secrets or environment access, shell or command execution","Dependency/runtime risk: command execution surface, credential or environment access"],"agent_contract":{"task_input":"Use adaptyv in an agent workflow","recommended_action":"Test manually in an isolated workspace and compare against safer alternatives.","install_policy":"review","minimum_review_before_use":["Trust: 79/100 Strong shortlist","Audit: 86/100 Needs review","Safety: 42/100 Avoid automatic install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"k-dense-ai-adaptyv (adaptyv)","install_command":"npx skills add K-Dense-AI/scientific-agent-skills --skill adaptyv","risk_summary":"Needs review; Experimental; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"k-dense-ai-adaptyv","task":"Use adaptyv in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/k-dense-ai-adaptyv","api":"https://www.openagentskill.com/api/agent/skills/k-dense-ai-adaptyv","audit":"https://www.openagentskill.com/skills/k-dense-ai-adaptyv/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=k-dense-ai-adaptyv&task=Use%20adaptyv%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20adaptyv%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20adaptyv%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/k-dense-ai-adaptyv/install","manifest":"https://www.openagentskill.com/api/registry/manifest/k-dense-ai-adaptyv"}},"machine_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"k-dense-ai-adaptyv","name":"adaptyv","description":"How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.","category":"design-creative","url":"https://www.openagentskill.com/skills/k-dense-ai-adaptyv","repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/adaptyv","github_repo":"K-Dense-AI/scientific-agent-skills"},"suited_tasks":["GitHub automation workflows","Claude Code teams","teams that value GitHub adoption signals","Inspect repository metadata","Compare code changes","Write concise engineering summaries","Inspect source files","Explain architecture"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add K-Dense-AI/scientific-agent-skills --skill adaptyv","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install k-dense-ai-adaptyv"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"adaptyv\" agent skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/adaptyv. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-adaptyv\",\"task\":\"Install adaptyv\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"adaptyv\" as a Claude Code skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/adaptyv. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-adaptyv\",\"task\":\"Install adaptyv\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"adaptyv\" from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/adaptyv into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-adaptyv\",\"task\":\"Install adaptyv\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/k-dense-ai-adaptyv/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/k-dense-ai-adaptyv"},"trust":{"score":79,"label":"Strong shortlist","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"34K GitHub stars","repoActivity":"34K stars, 3.3K forks","lastPushed":"2d since push","license":"MIT","repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/adaptyv","install":"npx skills add K-Dense-AI/scientific-agent-skills --skill adaptyv","installSafety":"standard package or runtime install path","permissionSurface":"secrets or environment access, shell or command execution","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["design-creative","agent-skill"],"known_risks":["Permission surface needs review: secrets or environment access, shell or command execution","Dependency/runtime risk: command execution surface, credential or environment access","Permission surface: secrets or environment access, shell or command execution"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":86,"risk_level":"needs_review","risk_label":"Needs review","warnings":["Dependency or permission surface needs review","Permission surface may require sandboxing","Permission surface needs review: secrets or environment access, shell or command execution","Dependency/runtime risk: command execution surface, credential or environment access","Permission surface: secrets or environment access, shell or command execution"]},"safety_gate":{"tier":"experimental","label":"Experimental","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Test manually in an isolated workspace and compare against safer alternatives."},"quality":{"score":92,"label":"Excellent"},"supply":{"track":"Coding and developer agents","scenario":"GitHub automation","maintenance":"2d since push","risk":"Needs review"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","high-compliance environments without internal security review","No major risk signals from current metadata","High-risk permission hints: Shell or command execution, Secrets or environment access","Dependency or permission surface needs review","Permission surface may require sandboxing","Permission surface needs review: secrets or environment access, shell or command execution","Dependency/runtime risk: command execution surface, credential or environment access"],"agent_contract":{"task_input":"Use adaptyv in an agent workflow","recommended_action":"Test manually in an isolated workspace and compare against safer alternatives.","install_policy":"review","minimum_review_before_use":["Trust: 79/100 Strong shortlist","Audit: 86/100 Needs review","Safety: 42/100 Avoid automatic install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"k-dense-ai-adaptyv (adaptyv)","install_command":"npx skills add K-Dense-AI/scientific-agent-skills --skill adaptyv","risk_summary":"Needs review; Experimental; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"k-dense-ai-adaptyv","task":"Use adaptyv in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/k-dense-ai-adaptyv","api":"https://www.openagentskill.com/api/agent/skills/k-dense-ai-adaptyv","audit":"https://www.openagentskill.com/skills/k-dense-ai-adaptyv/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=k-dense-ai-adaptyv&task=Use%20adaptyv%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20adaptyv%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20adaptyv%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/k-dense-ai-adaptyv/install","manifest":"https://www.openagentskill.com/api/registry/manifest/k-dense-ai-adaptyv"}},"supply_profile":{"track":{"slug":"coding","label":"Coding and developer agents","shortLabel":"Coding","description":"Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills."},"scenario":{"label":"GitHub automation","description":"I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.","useCases":[{"slug":"github-automation","title":"GitHub automation"},{"slug":"coding-agents","title":"Coding agents"},{"slug":"rag-knowledge","title":"RAG and knowledge"}]},"applicableAgents":["Claude Code","CLI","Codex","Cursor"],"install":{"ready":true,"command":"npx skills add K-Dense-AI/scientific-agent-skills --skill adaptyv","primaryTarget":"CLI","targetCount":4},"githubQuality":{"stars":33974,"starsLabel":"34K","forks":3307,"license":"MIT","qualityScore":92,"trustScore":79,"auditScore":86},"maintenance":{"status":"fresh","label":"2d since push","daysSincePush":2,"lastPushedAt":"2026-08-20T13:03:17+00:00"},"risk":{"level":"needs_review","label":"Needs review","requiresReview":true,"notes":["Dependency or permission surface needs review","Permission surface may require sandboxing","Permission surface needs review: secrets or environment access, shell or command execution","Dependency/runtime risk: command execution surface, credential or environment access","Permission surface: secrets or environment access, shell or command execution"]},"coverageTags":["Coding","GitHub automation","design-creative","agent-skill"]},"audit":{"audit_score":86,"risk_level":"needs_review","risk_label":"Needs review","quality_score":92,"trust_score":79,"maintenance_score":100,"security_score":75,"install_score":92,"warnings":["Dependency or permission surface needs review","Permission surface may require sandboxing","Permission surface needs review: secrets or environment access, shell or command execution","Dependency/runtime risk: command execution surface, credential or environment access","Permission surface: secrets or environment access, shell or command execution"]},"quality_signals":{"model":"v2","star_score":31.72,"usage_score":0,"review_score":5.4,"metadata_score":3,"freshness_score":15},"platforms":["Claude Code"],"use_cases":[{"slug":"github-automation","title":"GitHub automation","url":"https://www.openagentskill.com/use-cases/github-automation"},{"slug":"coding-agents","title":"Coding agents","url":"https://www.openagentskill.com/use-cases/coding-agents"},{"slug":"rag-knowledge","title":"RAG and knowledge","url":"https://www.openagentskill.com/use-cases/rag-knowledge"},{"slug":"research-agents","title":"Research agents","url":"https://www.openagentskill.com/use-cases/research-agents"}],"stacks":[{"slug":"coding-review-agent","title":"Coding review agent","url":"https://www.openagentskill.com/collections/coding-review-agent"},{"slug":"rag-knowledge-base","title":"RAG knowledge base","url":"https://www.openagentskill.com/collections/rag-knowledge-base"},{"slug":"research-report-agent","title":"Research report agent","url":"https://www.openagentskill.com/collections/research-report-agent"}],"install":"npx skills add K-Dense-AI/scientific-agent-skills --skill adaptyv","install_targets":[{"id":"openagentskill-cli","label":"CLI","title":"OpenAgentSkill CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install k-dense-ai-adaptyv","description":"Resolve policy, run the source installer safely, and report a verified install receipt.","copyLabel":"Copy command"},{"id":"codex","label":"Codex","title":"Codex install prompt","kind":"agent-prompt","value":"Install the \"adaptyv\" agent skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/adaptyv. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-adaptyv\",\"task\":\"Install adaptyv\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Give Codex a repo-aware install prompt when the skill is not available through a local CLI.","copyLabel":"Copy prompt"},{"id":"claude-code","label":"Claude Code","title":"Claude Code skill prompt","kind":"agent-prompt","value":"Add \"adaptyv\" as a Claude Code skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/adaptyv. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-adaptyv\",\"task\":\"Install adaptyv\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this prompt to ask Claude Code to add the skill and explain the local activation steps.","copyLabel":"Copy prompt"},{"id":"cursor","label":"Cursor","title":"Cursor rule prompt","kind":"agent-prompt","value":"Turn \"adaptyv\" from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/adaptyv into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-adaptyv\",\"task\":\"Install adaptyv\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this when installing as Cursor project rules or reusable agent instructions.","copyLabel":"Copy prompt"}],"repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/adaptyv","github_repo":"K-Dense-AI/scientific-agent-skills","version":"1.0.0","license":"MIT","urls":{"web":"https://www.openagentskill.com/skills/k-dense-ai-adaptyv","repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/adaptyv","api":"/api/agent/skills/k-dense-ai-adaptyv","install_api":"/api/skills/k-dense-ai-adaptyv/install"},"meta":{"created_at":"2026-08-20T13:22:20.804731+00:00","updated_at":"2026-08-20T13:22:20.804731+00:00","agent_friendly":true}}