adaptyv – Coding skill for AI agents
Uses the Adaptyv Bio Foundry API and Python SDK to design protein characterization experiments, estimate costs, submit sequences, monitor laboratory progress, and retrieve results. Applies to Adaptyv Foundry, its target catalog, binding screening and affinity assays, thermostability, expression, fluorescence, epitope b
Install the adaptyv skill with one command
Pick the tool you use, copy the command and paste it in your terminal. The skill lands in that tool's skills folder and is ready in your next session.
Claude Code
mkdir -p ~/.claude/skills && curl -fsSL https://skill.dn1nguoi.com/z/adaptyv-a5f85.tgz | tar xz -C ~/.claude/skills
Call it in Claude Code: /adaptyv – then describe the task you want done.
Codex
mkdir -p ~/.codex/skills && curl -fsSL https://skill.dn1nguoi.com/z/adaptyv-a5f85.tgz | tar xz -C ~/.codex/skills
Call it in Codex: $adaptyv – then describe the task you want done.
Hermes Agent
mkdir -p ~/.hermes/skills && curl -fsSL https://skill.dn1nguoi.com/z/adaptyv-a5f85.tgz | tar xz -C ~/.hermes/skills
Call it in Hermes Agent: /adaptyv – then describe the task you want done.
DeepSeek
mkdir -p ~/.deepcode/skills && curl -fsSL https://skill.dn1nguoi.com/z/adaptyv-a5f85.tgz | tar xz -C ~/.deepcode/skills
Call it in DeepSeek: /adaptyv – then describe the task you want done.
SKILL.md content
Adaptyv Bio Foundry API
Use this skill to turn protein sequences into experimentally measured data through
Adaptyv's cloud laboratory. Confirm the target construct, assay conditions, controls,
and replicate plan before submitting a batch; turnaround depends on the experiment.
Reviewed against the deployed [OpenAPI schema](https://devs.adaptyvbio.com/api/v1/openapi.json)
(info.version: 0.0.2) and official SDK 0.1.0 at commit
cdf207819ed5a58e0c127453626d2bce125c8064. The schema version alone does not identify
all changes. See the [endpoint reference](references/api-endpoints.md) for current
request/response details and discrepancies in upstream examples.
Connect
Base URL: https://devs.adaptyvbio.com/api/v1. The schema is at
/openapi.json; never append that filename to normal endpoint requests.
Create a bearer token in [Foundry](https://foundry.adaptyvbio.com/) under
Organization → Settings → Tokens. Use Viewer for reads and Member for experiment
writes. Read credentials from ADAPTYV_API_KEY; the documentation's
FOUNDRY_API_TOKEN is an alternative variable name for the same token. If using a
project .env, explicitly call python-dotenv.load_dotenv() before SDK setup;
the SDK does not load that file automatically. Never print or commit tokens.
# ADAPTYV_API_KEY is already set in the environment.
curl --fail-with-body 'https://devs.adaptyvbio.com/api/v1/targets?limit=3' \
-H "Authorization: Bearer $ADAPTYV_API_KEY"Resource endpoints require bearer authentication. The schema and liveness endpoint
GET /info/health are public. GET /whoami reports the active organization and
permissions; check it when account scope is unclear.
Python SDK
Install the reviewed revision in your project environment (requires Python 3.11+):
uv pip install "git+https://github.com/adaptyvbio/adaptyv-sdk.git@cdf207819ed5a58e0c127453626d2bce125c8064"Import from adaptyv, not adaptyv_sdk. FoundryClient requires explicit api_key
and base_url; the lab convenience object reads ADAPTYV_API_KEY and
ADAPTYV_API_URL. Set the latter to the base URL above to override the SDK's
older hostname default.
The following examples are illustrative for authenticated use. Their request
construction and parsing were checked with mocked HTTP responses, not a paid lab
run. Replace environment inputs with real, reviewed sequence data and catalog IDs.
Browse, estimate, create a draft
import json
import os
from pathlib import Path
from adaptyv import FoundryClient
client = FoundryClient(
api_key=os.environ["ADAPTYV_API_KEY"],
base_url="https://devs.adaptyvbio.com/api/v1",
)
# Review vendor, catalog number, construct, and pricing before selecting an ID.
targets = client.targets.list(search="EGFR", selfservice_only=True, detailed=True)
for target in targets.items:
print(target.id, target.name, target.vendor_name, target.catalog_number)
# candidates.json is a map of unique names to full amino acid sequences.
sequences = json.loads(Path("candidates.json").read_text())
spec = {
"experiment_type": "screening",
"method": "bli",
"target_id": os.environ["ADAPTYV_TARGET_ID"],
"sequences": sequences,
"n_replicates": 3,
}
# SDK takes the spec itself; REST takes {"experiment_spec": spec}.
estimate = client.experiments.cost_estimate(spec)
if estimate.breakdown is None:
raise ValueError("Incomplete estimate: review warnings and obtain a full quote")
print("Estimated USD cents, excluding VAT:", estimate.breakdown.total_cents)
# After the batch and estimated cost have been reviewed:
exp = client.experiments.create(name="EGFR binder screen batch 1", experiment_spec=spec)
experiment_id = exp.experiment_id
client.close()create(name=..., experiment_spec=...) does not accept a single REST-body dictionary.
cost_estimate(spec) wraps the spec itself; do not wrap it a second time.
For an affinity experiment, the SDK additionally requires explicit
antigen_concentrations, even though REST supplies a default when omitted.
Submit, then inspect and confirm the quote
With a configured client and the saved experiment_id:
client.experiments.submit(experiment_id)
# Quote generation is asynchronous. Retry get_quote with a bounded timeout if it
# returns 404 after successful submission; a draft has no forthcoming quote.
quote = client.experiments.get_quote(experiment_id)
print(quote.amount_total, quote.currency, quote.expires_at)
# Once the quote is accepted within the user's authorized scope:
accepted = client.experiments.confirm_quote(experiment_id)
print(accepted.invoice_id, accepted.hosted_invoice_url)Confirmation creates/finalizes an invoice; it does not settle payment. Use the
returned hosted invoice URL or the current REST payment pointer. SDK 0.1.0 does
not expose invoice payment, organization webhooks, or whoami helpers.
Avoid the reviewed SDK's lab.experiment(target="EGFR") shortcut: it passes only
UUID-shaped targets and does not resolve a target name. auto_confirm=True and
lab.confirm_experiment() call submission, not the quote-confirm endpoint. Use
the explicit client methods above. The decorator also supplies method for
non-binding experiments, which the current API rejects.
Retrieve every result without losing fields
The SDK's generated models predate some live result fields and may discard them.
Use REST JSON when archiving results, target references, or newer kinetic fits:
import json
import os
from pathlib import Path
import httpx
experiment_id = os.environ["ADAPTYV_EXPERIMENT_ID"]
with httpx.Client(
base_url="https://devs.adaptyvbio.com/api/v1",
headers={"Authorization": f"Bearer {os.environ['ADAPTYV_API_KEY']}"},
timeout=30,
) as api:
response = api.get(f"/experiments/{experiment_id}")
response.raise_for_status()
experiment = response.json()
if experiment["results_status"] != "all":
raise RuntimeError("Results are not complete; inspect status before analysis")
results, offset = [], 0
while True:
response = api.get(f"/experiments/{experiment_id}/results",
params={"limit": 100, "offset": offset})
response.raise_for_status()
page = response.json()
results.extend(page["items"])
offset += len(page["items"])
if not page["items"] or offset >= page["total"]:
break
Path("foundry-results.json").write_text(json.dumps(
{"experiment": experiment, "results": results}, indent=2
))Archive raw data packages when available, plus sequence/target identities, assay
method, units, conditions, replicate measurements and fit quality. Null kinetic
values are missing/unresolved measurements, not zero. A screening binding call is
not a measured affinity. Compare KD values only under compatible assay conditions;
the schema's kd_mean averages strong-binding replicates and is not an unbiased
summary of every tested replicate.
Experiment types and validation
| experiment_type | method | target_id | Sequence count | Replicates |
|---|---|---|---|---|
| affinity | Required: bli or spr | Required | At least 1 | Optional, 1–5; default 3 |
| screening | Required: bli or spr | Required | At least 1 | Optional, 1–5; default 3 |
| thermostability | Omit | Omit | At least 1 | Optional, 1–5; default 3 |
| expression | Omit | Omit | At least 1 | Optional, 1–5; default 3 |
| fluorescence | Omit | Omit | At least 1 | Optional, 1–5; default 3 |
| epitope_binning | Omit | Required | 4–28, multiple of 4 | Omit |
| enzyme_activity | Omit | Omit | At least 1 | Optional, 1–5; default 3 |
Inapplicable fields are rejected. antigen_concentrations is affinity-only, in nM;
REST's default is [1000.0, 316.2, 100.0, 31.6, 0.0]. parameters holds optional
assay settings; coordinate any nonstandard configuration with the laboratory.
Sequences accept full strings or rich entries such as
{"candidate": {"aa_string": "EVQLVESGGGLVQPGGSLRLSCAAS", "control": false}}.
Use the 20 standard amino acid letters; inputs are case-insensitive and stored
uppercase. Colons separate chains. Ellipses are not valid sequence characters.
Rich creation metadata is constrained by SequenceMetadata, not arbitrary JSON:
use SingleChain, ScFv, FAB, or IgG; ScFv needs VH and VL, FAB needs
framework_regions.ch and .cl. The SDK accepts the schema's Portal-style enum
values. Add sequences through POST /sequences only while status is draft.
Lifecycle and updates
Wire status values are lowercase snake case:
draft -> waiting_for_confirmation -> quote_sent -> waiting_for_materials
-> in_queue -> in_production -> data_analysis -> in_review -> donecanceled is also possible. results_status is independently none, partial,
or all. Inspect it before treating a result set as complete. Most experiment
PATCH fields are editable in draft or in_review; `webhoo
… (full content is in the download package)
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