Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-05 10:01 UTC

flytohub / flyto-ai

Plans new work as Flyto2 workflows, then reuses exact solved procedures without another planning call.

PythonApache-2.0★ 2 stars⑂ 0 forkssince Feb 2026View on GitHub ↗
KindLibraryCommand-line toolMCP serverhow this is determined
#ai-agent#workflow-automation#flyto2#mcp-server#procedure-reuse

flytohub/flyto-ai holds a health index of 78 out of 100, placing it in the Good band. It scores highest on Engineering Quality (81/100) and lowest on Community & Adoption (48/100). It was last updated today. A single contributor accounts for most of its recent work.

78
overall / 100
Good

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

78
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 67 is calibrated to 78 on the published index scale (record calibration 2026-08-02).

Ownership

Flyto2Organization
43 followers17 public repossince Nov 2025

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIflyto-ai0.20.04,007850 days agoai-agentai-agent-frameworkanthropicautomationbrowser-automationllmmcpollamaopenaiworkflowworkflow-automation

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

80Excellent · 21% of overall

Development activity

78Good
How it's scored
36/36Push recency — last push 0 days ago
13.8/36Commit cadence — 20/52 weeks with commits
18/18Commit volume — 312 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year312
human_commit_share1
days_since_last_push0
active_weeks_last_year20

Release discipline

84Excellent
How it's scored
27/27Ships releases — 1 releases published
36/36Release recency — latest release 33 days ago
12.6/27Release cadence — cadence unknown (single release)
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count1
latest_release_tagv0.14.3
releases_from_tagsno
days_since_latest_release33
mean_days_between_releases—
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

48Weak · 17% of overall

Popularity & adoption

1Critical
How it's scored
0/60Stars — 2 stars
0/25Forks — 0 forks
0/15Watchers — 1 watchers
Inputs used
forks0
stars2
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

92Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges5
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesshields.io
has_pull_request_templateyes

Ecosystem adoption (downloads)

60Moderate
How it's scored
48/80Monthly downloads — 4,007 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesflyto-ai
dependents—
ecosystemspypi
total_downloads—
monthly_downloads4,007
unverified_packages_excluded—
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

54Moderate · 23% of overall

Maintainer resilience (bus factor)

13Critical
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0/22.5Commit distribution — top contributor authored 100% of commits
1.4/13.5Contributor breadth — 1 contributors
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor1
contributors_sampled1
top_contributor_share1

Issue & PR responsiveness

68Good
How it's scored
42/42Issue resolution — 100% of issues closed
16.8/30PR acceptance — 28/50 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/30 approved changesets -- score normalized to 0
Inputs used
merged_prs28
open_issues0
closed_issues1
prs_merged_7d4
prs_decided_7d4
prs_merged_30d17
prs_decided_30d17
issue_closed_ratio1
closed_unmerged_prs22
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

52Moderate
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
11.8/25Owner reach — 43 followers of flytohub
10.7/25Track record — 17 public repos, account ~0 yr old
Inputs used
followers43
owner_typeOrganization
is_verifiedno
owner_loginflytohub
public_repos17
account_age_days279

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 0 days ago
20/20Version history — 85 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesflyto-ai
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

81Excellent · 19% of overall

Engineering practices

68Good
How it's scored
24/24CI workflows — 8 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 6 out of 6 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://flyto2.com
10/10Repository description
10/10Topics — 5 topics
10/10Wiki
Inputs used
topicsai-agent, workflow-automation, flyto2, mcp-server, procedure-reuse
has_wikiyes
homepagehttps://flyto2.com
docs_sitehttps://flyto2.com
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

76Good · 16% of overall

Security posture

76Good
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.5/2.5CI-Tests — 6 out of 6 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/30 approved changesets -- score normalized to 0
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1
5/5SAST — SAST tool is run on all commits
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
6.8/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate7.6
Excluded from scoring (no data or not applicable): Branch-Protection, Signed-Releases. Remaining weights renormalized.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

62Moderate · 4% of overall

Agent context & guidance

100Exceptional
How it's scored
45/45Agent instructions — AGENTS.md, CLAUDE.md
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://flyto2.com/llms.txt)
40/40Legible commit history — 97 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://flyto2.com/llms.txt
legible_history_share0.97
agent_instruction_filesAGENTS.md, CLAUDE.md
agent_instruction_max_bytes6,807

Verify loop (build / test / typecheck)

48Weak
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environment — Dockerfile
10/10Demonstrated agent practice — 5 of the last 100 commits agent-authored or agent-credited
5/8Automated maintenance — dependency automation configured, none observed in the sampled commits
1/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share0.05
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

52Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
51.7/55Manageable file sizes — 19/320 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes370,043
source_files_sampled320
oversized_source_files19

Machine-readable interfaces

33At Risk
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
20/20MCP server
0/40Runnable examples
Inputs used
example_dirs—
has_mcp_signalyes
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto). Remaining weights renormalized.

Key facts

2GitHub stars
1contributors
312commits, last 12 months
0days since last push
1releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • deps.dev does not index pypi:flyto-ai@0.20.0; advisories assessed against the repository dependency graph instead
  • No resolved dependencies carried a version and a supported ecosystem

More detail

OpenSSF Scorecard 7.6 / 10
7.6aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-09-05 10:01 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
10CI-Tests6 out of 6 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/30 approved changesets -- score normalized to 0
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
1Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 1
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
9Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 7
RegistryPackageVersion constraintManifest
PyPIpyyaml>=6.0pyproject.toml
PyPIpydantic>=2.0.0pyproject.toml
PyPIopenai>=1.0.0pyproject.toml
PyPIlangdetect>=1.0.9pyproject.toml
PyPIaiosqlite>=0.19.0pyproject.toml
PyPIrich>=13.0pyproject.toml
PyPIcryptography>=46.0.7pyproject.toml
All dependencies 16

Full resolved dependency set from the GitHub dependency graph: 7 direct and 9 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIaiosqlite—direct
PyPIcryptography—direct
PyPIlangdetect—direct
PyPIopenai—direct
PyPIpydantic—direct
PyPIpyyaml—direct
PyPIrich—direct
PyPIaiohttp—indirect
PyPIanthropic—indirect
PyPIclaude-agent-sdk—indirect
PyPIflyto-blueprint—indirect
PyPIflyto-core—indirect
PyPIflyto-pro-core—indirect
PyPIpytest—indirect
PyPIpytest-asyncio—indirect
PyPIruff—indirect
Dependency advisories not assessed

Advisory matching could not run for this report: No resolved dependencies carried a version and a supported ecosystem

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

Related records

Inspected repositories sharing catalogue tags or ecosystems with flytohub/flyto-ai. Read them side by side →

97langgenius/difyBuild Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without rebuilding the stack.Exceptional96JetBrains/koogKoog is a JVM (Java and Kotlin) framework for building predictable, fault-tolerant and enterprise-ready AI agents across all platforms – from backend services to Android and iOS, JVM, and even in-browser environments. Koog is based on our AI products expertise and provides proven solutions for complex LLM and AI problemsExceptional96strands-agents/toolsA set of tools that gives agents powerful capabilities.Exceptional98n8n-io/n8nFair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.Exceptional98Agenta-AI/agentaAgenta is a workspace where you and your team build agents and automations.Exceptional98modelcontextprotocol/python-sdkThe official Python SDK for Model Context Protocol servers and clientsExceptional

Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.