Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-09 03:06 UTC

nousergon / flow-doctor

Self-hosted error-monitoring for Python pipelines: capture exceptions, deduplicate, diagnose root causes with LLMs, route alerts (Telegram/Slack/email/GitHub/S3), and auto-generate fix PRs — from a logging handler or one report() call.

PythonMIT★ 0 stars⑂ 0 forkssince Mar 2026View on GitHub ↗
KindCommand-line toolPluginLibraryNetwork servicehow this is determined

nousergon/flow-doctor holds a health index of 65 out of 100, placing it in the Good band. It scores highest on Engineering Quality (86/100) and lowest on Sustainability & Governance (29/100). It was last updated today. A single contributor accounts for most of its recent work.

65
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.

65
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 60 is calibrated to 65 on the published index scale (record calibration 2026-08-02).

Ownership

Nous ErgonOrganization
5 followers24 public repossince Jun 2026

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIflow-doctorpoints to another repo — not scored0.16.2-4111 days agoerror-handlingerror-monitoringexception-handlingobservabilitymonitoringalertingpipelinediagnosisauto-fixllmclaudetelegramslackself-hosted

Metrics by category

Vitality

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

84Excellent · 21% of overall
How it's scored
36/36Push recencylast push 0 days ago
13.8/36Commit cadence20/52 weeks with commits
18/18Commit volume164 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 5 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year164
human_commit_share0.75
days_since_last_push0
active_weeks_last_year20
How it's scored
27/27Ships releases2 releases published
36/36Release recencylatest release 64 days ago
19.8/27Release cadencea release every ~87.2 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count2
latest_release_tagv0.8.2
releases_from_tagsno
days_since_latest_release64
mean_days_between_releases87.2
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?

36Weak · 17% of overall
How it's scored
0/60Stars0 stars
0/25Forks0 forks
0/15Watchers0 watchers
Inputs used
forks0
stars0
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
18/18CONTRIBUTING guide
0/13.5Code 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_conductno
readme_badge_servicesshields.io
has_pull_request_templateyes

Sustainability & Governance

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

29At Risk · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
0/22.5Commit distributiontop contributor authored 100% of commits
1.4/13.5Contributor breadth1 contributors
0/10OpenSSF Scorecard: Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled1
top_contributor_share1
How it's scored
0/42Issue resolution0% of issues closed
29.7/30PR acceptance91/92 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 0/18 approved changesets -- score normalized to 0
Inputs used
merged_prs91
open_issues5
closed_issues0
prs_merged_7d1
prs_decided_7d1
prs_merged_30d15
prs_decided_30d15
issue_closed_ratio0
closed_unmerged_prs1
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.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domain
5.6/25Owner reach5 followers of nousergon
10.7/25Track record24 public repos, account ~0 yr old
Inputs used
followers5
owner_typeOrganization
is_verifiedno
owner_loginnousergon
public_repos24
account_age_days90

Engineering Quality

Are baseline engineering and documentation practices in place?

86Excellent · 19% of overall
How it's scored
24/24CI workflows10 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage sitehttps://pypi.org/project/flow-doctor/
10/10Repository description
10/10Topics20 topics
10/10Wiki
Inputs used
topicsalerting, anthropic, claude, devops, error-handling, error-monitoring, exception-handling, incident-management, llm, monitoring, observability, pipeline, python, self-hosted, slack, telegram, auto-fix, error-tracking, notifications, sentry-alternative
has_wikiyes
homepagehttps://pypi.org/project/flow-doctor/
docs_sitehttps://pypi.org/project/flow-doctor/
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

70Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
2.2/7.5Branch-Protectionbranch protection is not maximal on development and all release branches
2.5/2.5CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-ReviewFound 0/18 approved changesets -- score normalized to 0
0/2.5Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained30 commit(s) and 5 issue activity found in the last 90 days -- score normalized to 10
5/5Packagingpackaging workflow detected
1.5/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 3
5/5SASTSAST tool is run on all commits
2/5Security-Policysecurity policy file detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate6.2
Excluded from scoring (no data or not applicable): Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages8
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:flow-doctor@0.16.2 runtime dependency closure — what installing the published package pulls in — 8 packages. Reachability is not analyzed.

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.

56Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history74 of 75 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.987
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config
11/11Static type checkingflow_doctor/py.typed
0/10Reproducible environment
10/10Demonstrated agent practice51 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance15 of the last 100 commits are automated dependency updates
3/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 3
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configsflow_doctor/py.typed
agent_commit_share0.51
toolchain_manifests
dependency_bot_commit_share0.15
How it's scored
27/45Type-checkable codePython with type-check config (flow_doctor/py.typed)
54.5/55Manageable file sizes1/113 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes93,934
source_files_sampled113
oversized_source_files1
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)
0/20MCP server
40/40Runnable examplesexamples
Inputs used
example_dirsexamples
has_mcp_signalno
api_schema_files
interfaces_expected_ofnetwork-service

Key facts

0GitHub stars
1contributors
164commits, last 12 months
0days since last push
2releases
1bus factor
5open issues
PyPIpackage ecosystems

Data collection warnings

  • pypi package 'flow-doctor' points at a different repository (https://github.com/cipher813/flow-doctor); excluded from ecosystem scoring

More detail

OpenSSF Scorecard 6.2 / 10
6.2aggregate

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 · 2026-09-09 03:06 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 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 0/18 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 5 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
3Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 3
10SASTSAST tool is run on all commits
4Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 5
RegistryPackageVersion constraintManifest
PyPIpyyaml>=6.0pyproject.toml
PyPIpydantic>=2.0pyproject.toml
PyPIpydantic-settings>=2.0pyproject.toml
PyPIpython-dotenv>=1.0pyproject.toml
PyPItyping_extensions>=4.5pyproject.toml
All dependencies 13

Full resolved dependency set from the GitHub dependency graph: 5 direct and 8 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIpydanticdirect
PyPIpydantic-settingsdirect
PyPIpython-dotenvdirect
PyPIpyyamldirect
PyPItyping-extensionsdirect
PyPIboto3indirect
PyPIclaude-agent-sdkindirect
PyPIcoverageindirect
PyPIkrepisindirect
PyPIopenaiindirect
PyPIpytestindirect
PyPIrequestsindirect
PyPIsetuptoolsindirect
Dependency advisories 0

Installing pypi:flow-doctor@0.16.2 pulls in 8 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

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.

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 statisticsPyPI.