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1. Find a target · mkurman | DecimalAI

scienceby mkurman

1. Find a target

mkurman/adaptyv

Source mkurman/zorai ↗License MIT

How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval.

SkillScore91Maintained

Automatic

Research pack

Last verified 8/21/2026

What it changes

Passed 21 of 23 test cases with the skill, and 7 of 23 without it.

Without skill30%

With skill91%

Checks it passed that the model alone missed

Formats the sorting parameter as desc(created_at).
Formats the parameter as sort=desc(created_at),asc(name).
Uses done as the status string in the s-expression filter.

and 20 more in the full report

14 fixed7 passed either way2 still failing0 broke

Pass-rate lift: +61 pp
Tokens: +28%
Agent turns: 0%
Response time: -54%

Model gemini-3.6-flashMeasured 8/21/2026v121 of 23 cases passed with skill

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/mkurman-adaptyv/SKILL.md https://app.decimal.ai/s/mkurman-adaptyv/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add mkurman-adaptyv, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/mkurman-adaptyv/ and pins it in .decimal/skills.lock

decimalai skills add mkurman-adaptyv

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/mkurman-adaptyv/SKILL.md https://app.decimal.ai/s/mkurman-adaptyv/SKILL.md

Raw file: /s/mkurman-adaptyv/SKILL.md ↗ · machine-readable summary at /s/mkurman-adaptyv.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 14 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 14

Prompt

When setting skip_draft to True on an Adaptyv experiment creation request, what initial status does the newly created experiment enter immediately upon creation?

What was checked, without and with the skill
Checked	Without skill	With skill
Transitions newly created experiments directly to WaitingForConfirmation status when skip_draft is True.	Missed	Passed
Bypasses the editable Draft state during creation.	Passed	Passed

case-18 · gemini-3.6-flash · 8/21/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md130 lines2 files

|---|---| | affinity | bli or spr | KD, kon, koff kinetics | Yes | | screening | bli or spr | Yes/no binding | Yes | | thermostability | — | Melting temperature (Tm) | No | | expression | — | Expression yield | No | | fluorescence | — | Fluorescence intensity | No |

Experiment Lifecycle

Draft → WaitingForConfirmation → QuoteSent → WaitingForMaterials → InQueue → InProduction → DataAnalysis → InReview → Done

Status	Who Acts	Description
`Draft`	You	Editable, no cost commitment
`WaitingForConfirmation`	Adaptyv	Under review, quote being prepared
`QuoteSent`	You	Review and confirm the quote
`WaitingForMaterials`	Adaptyv	Gene fragments and target ordered
`InQueue`	Adaptyv	Materials arrived, queued for lab
`InProduction`	Adaptyv	Assay running
`DataAnalysis`	Adaptyv	Raw data processing and QC
`InReview`	Adaptyv	Final validation
`Done`	You	Results available
`Canceled`	Either	Experiment canceled

The results_status field on an experiment tracks: none, partial, or all.

Common Workflows

1. Submit a Binding Screen (Step by Step)

# 1. Find a target
targets = client.targets.list(search="EGFR", selfservice_only=True)
target_id = targets.items[0].id

# 2. Preview cost
estimate = client.experiments.cost_estimate({
    "experiment_spec": {

Track record

Benchmark

21 / 23

test cases passed, vs 7 / 23 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

mkurman / zorai

skills/scientific-skills/adaptyv/SKILL.md

View on GitHub ↗

License MITImported 8/3/2026Version v1Bundled 1 file

Other skills for the same job

Published skills whose descriptions closely match this one, with their headline benchmark lift.

k-dense-ai/adaptyvHow 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`.Close match+64 pp pass-rate lift

More skills from the same source and nearby in the registry, with their headline benchmark lift.