adaptyv

Name: adaptyv
Author: K-Dense-AI

812installs3.1kforks

How to install adaptyv?

k-dense-ai/scientific-agent-skills/adaptyv

$npx -y skills add K-Dense-AI/scientific-agent-skills --skill adaptyv

Installs into the current project.

Summary

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, o

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SKILL.md

1	# Adaptyv Bio Foundry API
2
3	Adaptyv 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.
4
5	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)
6
7	## Quick Start
8
9	Base URL: `https://foundry-api-public.adaptyvbio.com/api/v1`
10
11	Authentication: Bearer token in the `Authorization` header. Tokens are obtained from [foundry.adaptyvbio.com](https://foundry.adaptyvbio.com/) sidebar.
12
13	When 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.
14
15	The [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.
16
17	```bash
18	export ADAPTYV_API_KEY="abs0_..."
19	curl https://foundry-api-public.adaptyvbio.com/api/v1/targets?limit=3 \
20	-H "Authorization: Bearer $ADAPTYV_API_KEY"
21	```
22
23	Every request except `GET /openapi.json` requires authentication. Store tokens in environment variables or `.env` files — never commit them to source control.
24
25	## Python SDK
26
27	Version note: `adaptyv-sdk` 0.1.0 (beta) is not yet on PyPI — install from GitHub:
28
29	```bash
30	uv pip install "git+https://github.com/adaptyvbio/adaptyv-sdk.git"
31	```
32
33	In a project with `pyproject.toml`:
34
35	```bash
36	uv add "adaptyv-sdk @ git+https://github.com/adaptyvbio/adaptyv-sdk.git"
37	```
38
39	Environment variables (set in shell or `.env` file):
40
41	```bash
42	ADAPTYV_API_KEY=your_api_key
43	ADAPTYV_API_URL=https://foundry-api-public.adaptyvbio.com/api/v1
44	ADAPTYV_ORGANIZATION_ID=your_org_id # optional
45	```
46
47	The `@lab.experiment` decorator and `FoundryClient` both read `ADAPTYV_API_KEY` and `ADAPTYV_API_URL` from the environment when not passed explicitly.
48
49	### Decorator Pattern
50
51	```python
52	from adaptyv import lab
53
54	@lab.experiment(target="PD-L1", experiment_type="screening", method="bli")
55	def design_binders():
56	return {"design_a": "MVKVGVNG...", "design_b": "MKVLVAG..."}
57
58	result = design_binders()
59	print(f"Experiment: {result.experiment_url}")
60	```
61
62	### Client Pattern
63
64	```python
65	import os
66	from adaptyv import FoundryClient
67
68	client = FoundryClient(
69	api_key=os.environ["ADAPTYV_API_KEY"],
70	base_url=os.environ.get(
71	"ADAPTYV_API_URL",
72	"https://foundry-api-public.adaptyvbio.com/api/v1",
73	),
74	)
75
76	# Browse targets
77	targets = client.targets.list(search="EGFR", selfservice_only=True)
78
79	# Estimate cost
80	estimate = client.experiments.cost_estimate({
81	"experiment_spec": {
82	"experiment_type": "screening",
83	"method": "bli",
84	"target_id": "target-uuid",
85	"sequences": {"seq1": "EVQLVESGGGLVQ..."},
86	"n_replicates": 3
87	}
88	})
89
90	# Create and submit
91	exp = client.experiments.create({...})
92	client.experiments.submit(exp.experiment_id)
93
94	# Later: retrieve results
95	results = client.experiments.get_results(exp.experiment_id)
96	```
97
98	## Experiment Types
99
100	\| Type \| Method \| Measures \| Requires Target \|
101	\|---\|---\|---\|---\|
102	\| `affinity` \| `bli` or `spr` \| KD, kon, koff kinetics \| Yes \|
103	\| `screening` \| `bli` or `spr` \| Yes/no binding \| Yes \|
104	\| `thermostability` \| — \| Melting temperature (Tm) \| No \|
105	\| `expression` \| — \| Expression yield \| No \|
106	\| `fluorescence` \| — \| Fluorescence intensity \| No \|
107
108	## Experiment Lifecycle
109
110	```
111	Draft → WaitingForConfirmation → QuoteSent → WaitingForMaterials → InQueue → InProduction → DataAnalysis → InReview → Done
112	```
113
114	\| Status \| Who Acts \| Description \|
115	\|---\|---\|---\|
116	\| `Draft` \| You \| Editable, no cost commitment \|
117	\| `WaitingForConfirmation` \| Adaptyv \| Under review, quote being prepared \|
118	\| `QuoteSent` \| You \| Review and confirm the quote \|
119	\| `WaitingForMaterials` \| Adaptyv \| Gene fragments and target ordered \|
120	\| `InQueue` \| Adaptyv \| Mat

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adaptyv

812installs3.1kforks

View on GitHub

How to install adaptyv?

k-dense-ai/scientific-agent-skills/adaptyv

$npx -y skills add K-Dense-AI/scientific-agent-skills --skill adaptyv

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Adaptyv Bio Foundry API
2
3	Adaptyv 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.
4
5	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)
6
7	## Quick Start
8
9	Base URL: `https://foundry-api-public.adaptyvbio.com/api/v1`
10
11	Authentication: Bearer token in the `Authorization` header. Tokens are obtained from [foundry.adaptyvbio.com](https://foundry.adaptyvbio.com/) sidebar.
12
13	When 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.
14
15	The [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.
16
17	```bash
18	export ADAPTYV_API_KEY="abs0_..."
19	curl https://foundry-api-public.adaptyvbio.com/api/v1/targets?limit=3 \
20	-H "Authorization: Bearer $ADAPTYV_API_KEY"
21	```
22
23	Every request except `GET /openapi.json` requires authentication. Store tokens in environment variables or `.env` files — never commit them to source control.
24
25	## Python SDK
26
27	Version note: `adaptyv-sdk` 0.1.0 (beta) is not yet on PyPI — install from GitHub:
28
29	```bash
30	uv pip install "git+https://github.com/adaptyvbio/adaptyv-sdk.git"
31	```
32
33	In a project with `pyproject.toml`:
34
35	```bash
36	uv add "adaptyv-sdk @ git+https://github.com/adaptyvbio/adaptyv-sdk.git"
37	```
38
39	Environment variables (set in shell or `.env` file):
40
41	```bash
42	ADAPTYV_API_KEY=your_api_key
43	ADAPTYV_API_URL=https://foundry-api-public.adaptyvbio.com/api/v1
44	ADAPTYV_ORGANIZATION_ID=your_org_id # optional
45	```
46
47	The `@lab.experiment` decorator and `FoundryClient` both read `ADAPTYV_API_KEY` and `ADAPTYV_API_URL` from the environment when not passed explicitly.
48
49	### Decorator Pattern
50
51	```python
52	from adaptyv import lab
53
54	@lab.experiment(target="PD-L1", experiment_type="screening", method="bli")
55	def design_binders():
56	return {"design_a": "MVKVGVNG...", "design_b": "MKVLVAG..."}
57
58	result = design_binders()
59	print(f"Experiment: {result.experiment_url}")
60	```
61
62	### Client Pattern
63
64	```python
65	import os
66	from adaptyv import FoundryClient
67
68	client = FoundryClient(
69	api_key=os.environ["ADAPTYV_API_KEY"],
70	base_url=os.environ.get(
71	"ADAPTYV_API_URL",
72	"https://foundry-api-public.adaptyvbio.com/api/v1",
73	),
74	)
75
76	# Browse targets
77	targets = client.targets.list(search="EGFR", selfservice_only=True)
78
79	# Estimate cost
80	estimate = client.experiments.cost_estimate({
81	"experiment_spec": {
82	"experiment_type": "screening",
83	"method": "bli",
84	"target_id": "target-uuid",
85	"sequences": {"seq1": "EVQLVESGGGLVQ..."},
86	"n_replicates": 3
87	}
88	})
89
90	# Create and submit
91	exp = client.experiments.create({...})
92	client.experiments.submit(exp.experiment_id)
93
94	# Later: retrieve results
95	results = client.experiments.get_results(exp.experiment_id)
96	```
97
98	## Experiment Types
99
100	\| Type \| Method \| Measures \| Requires Target \|
101	\|---\|---\|---\|---\|
102	\| `affinity` \| `bli` or `spr` \| KD, kon, koff kinetics \| Yes \|
103	\| `screening` \| `bli` or `spr` \| Yes/no binding \| Yes \|
104	\| `thermostability` \| — \| Melting temperature (Tm) \| No \|
105	\| `expression` \| — \| Expression yield \| No \|
106	\| `fluorescence` \| — \| Fluorescence intensity \| No \|
107
108	## Experiment Lifecycle
109
110	```
111	Draft → WaitingForConfirmation → QuoteSent → WaitingForMaterials → InQueue → InProduction → DataAnalysis → InReview → Done
112	```
113
114	\| Status \| Who Acts \| Description \|
115	\|---\|---\|---\|
116	\| `Draft` \| You \| Editable, no cost commitment \|
117	\| `WaitingForConfirmation` \| Adaptyv \| Under review, quote being prepared \|
118	\| `QuoteSent` \| You \| Review and confirm the quote \|
119	\| `WaitingForMaterials` \| Adaptyv \| Gene fragments and target ordered \|
120	\| `InQueue` \| Adaptyv \| Mat

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