Task-scoped authorization for AI agents. Cryptographic warrants constrain tools and arguments, prevent privilege escalation at every delegation hop, and produce signed evidence of what was allowed or denied.
C-Rank Grade: A (Welcoming) - 56/100
External PR Merge Rate: 63%
Response Time: 25d
First Timer Success: 100%
tenuo-ai/tenuo has a recorded first-timer success rate of 100.0%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in tenuo-ai/tenuo respond to incoming external pull requests in approximately 608.7 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.
The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 56.2 places tenuo-ai/tenuo in the A tier.
The external contributor pull request merge rate for tenuo-ai/tenuo is 62.5%, based on public PR activity from non-core contributors.
tenuo-ai/tenuo currently has 26 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".
Collaborative maintainer environment in tenuo-ai/tenuo. Reviews community pull requests with focus on project quality.
Discussions in tenuo-ai/tenuo focus heavily on practical implementation feedback, code formatting standards, and issue reproduction details.
Unlinked PRs without issue context and changes that fail automated test suites face the highest review friction.
Average Response Latency
Tracks hours until a maintainer leaves a review, comment, or PR response.
External Acceptance Rate
Percentage of community pull requests successfully merged into main.
First PR Conversion
Rate at which developers submitting their first repository PR succeed.
Show contributors that your repository actively reviews and merges external pull requests.
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Historical health & responsiveness evolution
External PR acceptance
First PR success rate
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90% receive response in
Maintainer review activity heatmap & prime window prediction
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Maintainers are most responsive around 09:00 UTC (09:00 UTC in your timezone). Recommended submission window is Wednesday - Friday from 06:00 to 10:00 UTC (06:00 - 10:00 UTC local).
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~396 hours (78% approval). Large PRs (>500 lines) take ~2922 hours (28% approval). Keep your diff compact for rapid review.
Goal Make missing-optional-dependency errors across the Python integrations consistently point users to the correct Tenuo 0.3.0 installation extra. Today the behavior is inconsistent: some messages recommend installing a framework directly, some omit an installation command, and some already name the correct extra. Repository location Integration modules under tenuo-python/tenuo/, especially openai.py, autogen.py, crewai.py, langchain.py, langgraph.py, fastapi.py, google_adk/, and mcp/ New parameterized coverage: tenuo-python/tests/unit/test_optional_dependency_errors.py Reuse the subprocess/import-isolation pattern in tenuo-python/tests/adapters/test_mcp_fastmcp_import_errors.py where helpful Package source of truth: tenuo-python/pyproject.toml Tenuo 0.3.0 extras to report tenuo[openai] tenuo[autogen] tenuo[langchain] tenuo[langgraph] tenuo[crewai] tenuo[google_adk] tenuo[a2a] tenuo[mcp] or tenuo[fastmcp], depending on the API used tenuo[fastapi] Use a consistent command such as p
Goal Add a consumer-facing pytest recipe for code protected with Tenuo 0.3.0. The SDK exports testing helpers and documents them in the API reference, but there is no runnable example that an application developer can copy into their own test suite. Repository location Recipe: tenuo-python/examples/testing/test_protected_tools.py Guide: tenuo-python/examples/testing/README.md Regression coverage: tenuo-python/tests/examples/test_testing_recipe.py Index/docs: update tenuo-python/examples/README.md Tenuo 0.3.0 API to use Public application API: SigningKey.generate(), Warrant.mint_builder(), @guard, warrant_scope, and key_scope Public testing API from tenuo.testing: assert_authorized, assert_denied, assert_can_grant, assert_cannot_grant, and deterministic_headers Prefer testing real authorization decisions. allow_all() may be mentioned as an intentional bypass for isolated unit tests, but it must not be the main recipe and must not appear in production modules. Suggested coverage Prot
Goal Add a runnable A2A authorization-preflight example using Tenuo 0.3.0's existing dry_run(), simulate(), and visualize_chain() helpers. These helpers are public and have documentation snippets, but no executable example shows how an agent developer uses them before dispatching a task. Repository location Example: tenuo-python/examples/a2a/preflight.py Tests: tenuo-python/tests/examples/test_a2a_preflight_example.py Index/docs: update tenuo-python/examples/a2a/README.md and tenuo-python/examples/README.md Tenuo 0.3.0 API to use A2AServerBuilder or A2AServer for an in-process local server object dry_run(server, warrant, skill, arguments, warrant_chain=...) simulate(server, warrant, skill, arguments, warrant_chain=...) visualize_chain([parent, child], use_rich=False) for deterministic output Warrant.mint_builder() and grant_builder() for the displayed chain Suggested scenario Register a read_file skill constrained to a safe path. Preflight one allowed path and one denied path, prin
Goal Add a minimal Google ADK SequentialAgent example whose child agents use Tenuo 0.3.0's existing protect_agent() helper. The repository has substantial ADK incident-response demos, but no small workflow using ADK's native workflow-agent composition and no runnable use of protect_agent(). Repository location Example: tenuo-python/examples/google_adk_sequential_workflow/demo.py Example notes: tenuo-python/examples/google_adk_sequential_workflow/README.md Tests: tenuo-python/tests/examples/test_google_adk_sequential_workflow.py Index/docs: update tenuo-python/examples/README.md Tenuo 0.3.0 API to use from tenuo.google_adk import protect_agent protect_agent(agent, allow=[...]) for the zero-config, Tier 1 allowlist path Google ADK's native SequentialAgent and child-agent composition Make the security boundary explicit: protect_agent() in 0.3.0 is an allowlist helper. Do not describe it as holder-bound Tier 2 delegation. The README may point readers to GuardBuilder.with_warrant(...) f
Goal Add a protected AutoGen AgentChat team example using RoundRobinGroupChat and Tenuo 0.3.0's existing AutoGen tool wrappers. The current examples use AssistantAgent instances and a custom orchestrator tool, but none exercises AutoGen's native team abstraction. Repository location Example: tenuo-python/examples/autogen_round_robin_group_chat.py Tests: tenuo-python/tests/examples/test_autogen_round_robin_group_chat.py Index/docs: update tenuo-python/examples/README.md Tenuo 0.3.0 API to use warrant.bind(signing_key) to obtain each agent's BoundWarrant from tenuo.autogen import guard_tools guard_tools(tools, bound) or guard_tool(tool, bound, tool_name=...) Warrant.mint_builder() / grant_builder() for holder-bound authority Use AutoGen AgentChat >=0.7's native AssistantAgent and RoundRobinGroupChat APIs, matching the current tenuo[autogen] extra. Suggested scenario Create a researcher and reviewer team. Only the researcher can call a constrained lookup tool; only the reviewer can ca
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When evaluating whether to contribute to tenuo-ai/tenuo, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.
Currently, maintainers of tenuo-ai/tenuo acknowledge new external contributions in approximately 25 days+. Out of all submitted pull requests from non-core authors in the last 180-day window, 62.5% were successfully merged into the primary branch.
tenuo-ai/tenuo has a recorded first-timer success rate of 100.0%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~25 days+. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 56.2 places tenuo-ai/tenuo in the Welcoming tier.
The external pull request merge rate is 62.5%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
Yes, tenuo-ai/tenuo currently has 26 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.
All metrics displayed for tenuo-ai/tenuo are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.