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openai/openai-agents-python

openai/openai-agents-python is a framework in RepoRadar's Developer Tools section, holding Gold tier and a 'try now' verdict. Its strongest signal is workflow potential, scored 10.0 out of 10.

Produced and maintained by RepoRadar Research · Methodology · Corrections.

Open on GitHub →Back to radar
Score8.9
Popularity84.0
Riskconditional
TierGold
Score breakdown
Usefulness9.0
Novelty7.0
Momentum8.0
Maturity8.6
Open-source/build8.4
Evidence7.2
Workflow potential10.0
Setup ease6.4

Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.

Why it matters

Useful for Python teams that want a first-party agent runtime with tracing and guardrails instead of stitching together tool use, orchestration, and review logic by hand.

Where this stands now

openai/openai-agents-python ranks #1 of 1014 tracked Developer Tools items by composite score (8.9 against a section median of 4.9). The section currently carries 784 Bronze, 126 Silver, 103 Gold, 1 Low Signal. RepoRadar has retained observations for this record since 2026-06-20 (99 days in the current window). Signal extremes versus the section: momentum at the 96th percentile; novelty at the 86th percentile.

Who should use it

Python developers teams building agent products automation engineers voice and tool-using agent builders

Who should skip it

Skip openai/openai-agents-python if the source repository or demo is inactive, unmaintained, or no longer matches the description shown here.

About this signal

openai/openai-agents-python is tracked by RepoRadar as a framework in the Developer Tools section. First seen 2026-06-20; the source record was last checked on 2026-06-20. The current verdict is 'try now' with a Gold tier and moderate setup difficulty. The standout signals for openai/openai-agents-python are workflow potential (10.0) and practical usefulness (9.0), while setup ease (6.4) trails — that balance shapes where it fits best. This page summarizes the public evidence on the linked source page and states where additional review is still needed.

How this item is evaluated

The openai/openai-agents-python record combines a 8.9/10 composite score with separate popularity (84.0), risk (conditional), and setup (moderate) signals. See the scoring methodology for the current weights and evidence definitions.

Questions worth asking before you adopt this

Putting this into practice? Read How to vet an AI agent or MCP server before you wire it in for the checklist behind this score.

Risk explanation

The SDK is built to broker tool calls, MCP servers, sandbox execution, and voice or realtime flows into external systems, so start with least-privilege credentials and explicit approval on any side-effecting actions.

Evidence links
Closest alternatives / related signals
openai python agent-sdk mcp voice-agents
Verification record

What RepoRadar actually verified

Tested in a bounded workflow Source-only update since test

Bounded representative workflow retained by RepoRadar verification harness. Last checked 2026-07-13T10:35:57.333092Z.

A source release dated 2026-09-17 is newer than the retained test dated 2026-07-13; the previous test may no longer represent the current release.

Read as a sequence: 2 retained check(s) on 2026-07-13 with outcomes of 2 passed; evidence scopes covered bounded representative workflows and bounded setup checks. Recorded setup time totals 1 minute(s).

passed · cohort-20260712-openai-agents-construct

Tester
RepoRadar automated local verification harness
Started
2026-07-13T03:22:36.270448Z
Completed
2026-07-13T03:22:40.567152Z
Environment
Windows 10 AMD64; Python 3.11.9; credential-stripped child environment; disposable home/cache
Install/setup time
0 minute(s)
Evidence scope
Bounded setup or capability check
Cleanup
Per-check temporary home and work directory removed. Shared cohort package cache removed.
Actions exercised
  • Created a disposable home, work directory, and isolated package cache with credential-like environment variables excluded.
  • Executed bounded check: Construct an OpenAI Agents SDK agent without running it.
  • Captured the complete sanitized stdout, stderr, exit status, and 4.30-second wall time.
Observed results
  • Command exited 0 after 4.30 seconds.
  • Expected marker 'CHECK_OK' was observed in retained output.
Observed strengths
  • The OpenAI Agents SDK constructed a named Agent with local instructions without invoking a runner, tool, trace exporter, credential, or model.
Friction
  • The command emitted stderr; warnings or errors are preserved in the retained log for review.
Limitations
  • No runner, tool, trace export, API credential, or model call was used.
  • This bounded cohort check is not a production benchmark or a claim of real user-workflow adoption.

Pricing assessment: No paid plan or metered provider usage was exercised; package or licensing, hosting, and provider costs remain workflow-dependent.

Privacy assessment: No repository content, user data, or provider prompt was transmitted; broader product data handling was not assessed by this bounded run.

Open retained test log →

passed · cohort-20260712-openai-agents-function-tool-workflow

Tester
RepoRadar automated local verification harness
Started
2026-07-13T10:35:52.923510Z
Completed
2026-07-13T10:35:57.333092Z
Environment
Windows 10 AMD64; Python 3.11.9; credential-stripped child environment; disposable home/cache
Install/setup time
1 minute(s)
Evidence scope
Bounded representative workflow
Cleanup
Per-check temporary home and work directory removed. Shared cohort package cache removed.
Actions exercised
  • Created a disposable home, work directory, and isolated package cache with credential-like environment variables excluded.
  • Created 1 synthetic fixture file(s) inside the disposable work directory; retained hashes prove the exact inputs.
  • Decorated a typed Python function with the SDK's function_tool adapter and inspected its generated JSON schema.
  • Created a local ToolContext, dispatched serialized severity input through on_invoke_tool, and retained the schema and page result.
  • Executed bounded check: Generate and invoke a typed OpenAI Agents SDK function tool entirely locally.
  • Captured the complete sanitized stdout, stderr, exit status, artifact checks, and 4.41-second wall time.
Observed results
  • Command exited 0 after 4.41 seconds.
  • The SDK generated an integer-typed tool schema, parsed the JSON argument, invoked the function, and returned page.
  • Expected marker 'CHECK_OK tool=triage type=integer result=page' was observed in retained output.
  • Validated result.json: 3 required marker(s) present and 0 excluded marker(s) absent; size and SHA-256 are retained.
Observed strengths
  • Function-tool adaptation, strict schema generation, JSON argument handling, and invocation were usable independently of an API-backed agent run.
Friction
  • Direct invocation requires constructing a ToolContext; the full Runner normally supplies this context during a model-selected tool call.
  • Setup or runtime emitted 1 stderr line(s); the complete warnings/errors are preserved in the retained log.
Limitations
  • Direct function-tool invocation validates schema generation and input dispatch, not an Agent Runner, model selection, handoffs, tracing export, or hosted tool calls.
  • This credential-free disposable workflow does not establish production scale, model quality, reliability under sustained use, or team adoption.

Pricing assessment: The typed tool workflow used the local open-source SDK and made no OpenAI API, model, or hosted tracing request.

Privacy assessment: Only the synthetic severity argument was parsed in process; no API key, prompt, trace, or network transport was present.

Open retained test log →

Verification sources

Longitudinal intelligence

How this decision record is moving

Raw history JSON →

78 dated snapshots retained from 2026-06-20 through 2026-09-27; see the snapshot index for explicit coverage gaps. Stars, version, release, pricing, integration, risk, maintenance, verdict, score, and momentum fields remain explicit even when a source has not reported them. Repository momentum is a normalized 0–10 RepoRadar signal; GitHub stars appear only where the popularity monitor retained exact timestamped observations.

RepoRadar score8.9 current · +0.0 net
Repository momentum9.3 current · +1.3 net
GitHub stars (observed)29,710 current · +1,820 net
GitHub stars29,710 exact observation
Versionv0.22.3
Last release2026-09-17T22:19:05Z
MaintenanceActive
Current riskConditional
Current verdictTry now
Pricing baselineNo structured commercial pricing baseline
Pricing checkedNot applicable or not recorded
Pricing freshnessNo dated commercial pricing review
Integrations baselineNo structured integrations recorded

Recent dated points

DateScoreMomentumStarsRiskVerdictMaintenance
2026-09-278.99.329,710ConditionalTry nowActive
2026-09-268.99.329,704ConditionalTry nowActive
2026-09-258.99.629,696ConditionalTry nowActive
2026-09-248.99.629,682ConditionalTry nowActive
2026-09-238.99.629,658ConditionalTry nowActive
2026-09-228.99.029,636ConditionalTry nowActive
2026-09-218.99.029,618ConditionalTry nowActive
2026-09-208.99.629,581ConditionalTry nowActive
2026-09-198.99.029,561ConditionalTry nowActive
2026-09-178.99.029,524ConditionalTry nowActive
2026-09-158.99.629,451ConditionalTry nowActive
2026-09-138.99.029,394ConditionalTry nowActive

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