Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-20 13:26 UTC

Eigenwise / atomic-agents

Building AI agents, atomically

PythonMIT★ 6,287 stars⑂ 559 forkssince Jun 2024View on GitHub ↗
KindPluginLibraryCommand-line toolMCP serverTerminal interfacehow this is determined

Eigenwise/atomic-agents holds a health index of 89 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (95/100) and lowest on Security (28/100). It was last updated today. A single contributor accounts for most of its recent work.

89
overall / 100
Excellent

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.

89
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 75 is calibrated to 89 on the published index scale (record calibration 2026-08-02).

Ownership

Kenny VaneetveldePersonal account
183 followers22 public repossince Mar 2019

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIatomic-agents2.13.111,711910 days ago

Metrics by category

Vitality

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

93Exceptional · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
26.3/36Commit cadence — 38/52 weeks with commits
18/18Commit volume — 306 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year306
human_commit_share1
days_since_last_push0
active_weeks_last_year38

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 70 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~7.8 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count70
latest_release_tagv2.14.0
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases7.8

Community & Adoption

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

79Good · 17% of overall
How it's scored
60/60Stars — 6,287 stars
22.9/25Forks — 559 forks
9.7/15Watchers — 56 watchers
Inputs used
forks559
stars6,287
watchers56
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges12
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesbadge.fury.io, github.com, shields.io
has_pull_request_templateno
How it's scored
54.2/80Monthly downloads — 11,711 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesatomic-agents
dependents—
ecosystemspypi
total_downloads—
monthly_downloads11,711
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?

67Good · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
5.2/22.5Commit distribution — top contributor authored 77% of commits
13.5/13.5Contributor breadth — 48 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor1
contributors_sampled48
top_contributor_share0.768
How it's scored
41.3/42Issue resolution — 98% of issues closed
25.4/30PR acceptance — 148/175 decided PRs merged
9/13Newcomer PR acceptance — 9/13 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs148
open_issues2
closed_issues117
prs_merged_7d17
prs_decided_7d17
prs_merged_30d27
prs_decided_30d32
issue_closed_ratio0.983
closed_unmerged_prs27
first_time_authors_30d11
first_time_prs_merged_30d9
first_time_prs_decided_30d13
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
16.3/25Owner reach — 183 followers of Eigenwise
21.9/25Track record — 22 public repos, account ~7 yr old
Inputs used
followers183
owner_typeUser
is_verified—
owner_loginEigenwise
public_repos22
account_age_days2,765
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

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 — 91 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesatomic-agents
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

95Exceptional · 19% of overall
How it's scored
24/24CI workflows — 2 workflow(s)
24/24Tests present
16/16Linter config — .flake8, pyproject.toml ([tool.black])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://eigenwise.github.io/atomic-agents/
10/10Repository description
10/10Topics — 7 topics
10/10Wiki
Inputs used
topicsai, artificial-intelligence, large-language-model, large-language-models, llms, openai, openai-api
has_wikiyes
homepagehttps://eigenwise.github.io/atomic-agents/
docs_sitehttps://eigenwise.github.io/atomic-agents/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

28At Risk · 16% of overall
How it's scored
0/30Security policy (SECURITY.md)
0/25Dependabot config
25/25Dependency lockfiles — uv.lock
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfilesuv.lock
manifestspyproject.toml, requirements.txt, setup.py
has_codeql_workflowno
has_security_policyno
has_dependabot_configno
How it's scored
5.3/35Direct dependencies free of known advisories — 3 affected: gitpython 3.1.45 (critical 9.8), litellm 1.80.9 (critical 9.8), mcp 1.22.0 (high 7.5)
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
23.8/40No advisories left outstanding — 3 advisory-carrying package(s) unaddressed past 90 days; oldest published 321 days ago
Inputs used
sourceosv
advisories384
affected_packages35
assessed_packages284
unassessed_packages43
affected_by_severitycritical 10, high 15, moderate 9, low 1
direct_affected_packages3
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories. Remaining weights renormalized. Matched 284 resolved dependencies against OSV. 43 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. 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.

92Excellent · 4% of overall
How it's scored
45/45Agent instructions — .aider.conf.yml, AGENTS.md, claude-plugin/atomic-agents/skills/framework/references/agents.md, docs/api/agents.md
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://eigenwise.github.io/atomic-agents/llms.txt)
33.6/40Legible commit history — 63 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://eigenwise.github.io/atomic-agents/llms.txt
legible_history_share0.63
agent_instruction_files.aider.conf.yml, AGENTS.md, claude-plugin/atomic-agents/skills/framework/references/agents.md, docs/api/agents.md
agent_instruction_max_bytes14,846
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
11/11Lint / format config — .flake8, pyproject.toml ([tool.black])
11/11Static type checking — pyrightconfig.json
10/10Reproducible environment — lockfile
10/10Demonstrated agent practice — 50 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configspyrightconfig.json
agent_commit_share0.5
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
27/45Type-checkable code — Python with type-check config (pyrightconfig.json)
54.8/55Manageable file sizes — 1/224 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes130,517
source_files_sampled224
oversized_source_files1
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
20/20MCP server
40/40Runnable examples — examples
Inputs used
example_dirsexamples
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

6,287GitHub stars
48contributors
306commits, last 12 months
0days since last push
70releases
1bus factor
2open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • First-time contributor figures cover 12 of 17 authors (cap 12)
  • deps.dev does not index pypi:atomic-agents@2.13.1; advisories assessed against the repository dependency graph instead
  • Advisory severity resolved for 120 of 138 advisories (lookup cap); the remainder are reported as unknown severity
  • OpenSSF Scorecard did not return a usable result (killed by SIGKILL — most likely the container's memory limit); skipping Scorecard checks

More detail

Star and fork history 0 ★ / 559 ⇿
0Stars
559Forks
65Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

0100200300400500600556172024-062025-082026-10
Major 0Minor 13Patch 51

Each point covers 3 days.

Direct dependencies 10
RegistryPackageVersion constraintManifest
PyPIinstructor>=1.17.0,<2pyproject.toml
PyPIpydantic>=2.11.4,<3.0.0pyproject.toml
PyPIrich>=13.7.1,<14.0.0pyproject.toml
PyPIgitpython>=3.1.43,<4.0.0pyproject.toml
PyPIpyfiglet>=1.0.2,<2.0.0pyproject.toml
PyPItextual>=5.3.0,<6.0.0pyproject.toml
PyPIpyyaml>=6.0.2,<7.0.0pyproject.toml
PyPIrequests>=2.32.3,<3.0.0pyproject.toml
PyPImcp>=1.8.0,<2pyproject.toml
PyPIlitellm>=1.50.0,<2.0.0pyproject.toml
All dependencies 327

Full resolved dependency set from the GitHub dependency graph: 19 direct and 308 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
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PyPItyper-slim0.20.0indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.2indirect
PyPItzdata—indirect
PyPItzdata2025.2indirect
PyPItzlocal5.3.1indirect
PyPIuc-micro-py1.0.3indirect
PyPIuritemplate4.2.0indirect
PyPIurllib32.8.0indirect
PyPIuvicorn—indirect
PyPIuvicorn0.38.0indirect
PyPIuvloop0.22.1indirect
PyPIvirtualenv20.35.4indirect
PyPIwatchfiles1.1.1indirect
PyPIweather-tool1.0.0indirect
PyPIweb-search-agent1.0.0indirect
PyPIwebpage-scraper1.0.0indirect
PyPIwebsocket-client1.9.0indirect
PyPIwebsockets15.0.1indirect
PyPIwget—indirect
PyPIwget3.2indirect
PyPIwikipedia-search1.0.0indirect
PyPIwrapt1.17.3indirect
PyPIxmltodict1.0.4indirect
PyPIxxhash3.6.0indirect
PyPIyarl1.25.1indirect
PyPIyoutube-summarizer1.0.0indirect
PyPIyoutube-to-recipe1.0.0indirect
PyPIyoutube-transcript-api—indirect
PyPIyoutube-transcript-api1.2.3indirect
PyPIyoutube-transcript-scraper1.0.0indirect
PyPIzipp3.23.0indirect
Dependency advisories 35

This repository publishes no package the index resolves, so its own dependency graph was assessed — 284 packages, which also include development and test pins that never ship: 35 carry known advisories, of which 3 are direct. 43 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
gitpython3.1.45directcritical593.1.62
litellm1.80.9directcritical451.96.2
anyio4.11.0indirectcritical44.14.2
authlib1.6.5indirectcritical161.7.1
black24.10.0indirectcritical326.3.1
chromadb1.3.5indirectcritical8—
cryptography46.0.3indirectcritical1350.0.0
fastmcp2.13.3indirectcritical93.2.0
pillow12.0.0indirectcritical3812.3.0
pyjwt2.10.1indirectcritical312.15.0
mcp1.22.0directhigh72.2.0
fsspec2025.10.0indirecthigh22026.6.0
httplib20.31.0indirecthigh20.32.0
json-repair0.54.2indirecthigh10.60.1
lxml5.4.0indirecthigh26.1.0
lxml-html-clean0.4.3indirecthigh60.4.5
mako1.3.10indirecthigh61.4.2
orjson3.11.4indirecthigh23.11.6
protobuf6.33.1indirecthigh26.33.5
pyasn10.6.1indirecthigh100.6.4
pypdf6.10.2indirecthigh536.19.0
python-multipart0.0.20indirecthigh140.0.31
soupsieve2.8indirecthigh82.9.0
starlette0.50.0indirecthigh101.3.1
virtualenv20.35.4indirecthigh1021.7.13
diskcache5.6.3indirectmoderate2—
filelock3.20.0indirectmoderate43.20.3
h24.3.0indirectmoderate24.4.1
hpack4.1.0indirectmoderate24.2.0
multidict6.7.0indirectmoderate26.9.1
oauthlib3.3.1indirectmoderate44.0.0
pydantic-settings2.12.0indirectmoderate12.14.2
pytest8.4.2indirectmoderate29.0.3
python-dotenv1.2.1indirectmoderate21.2.2
pygments2.19.2indirectlow22.20.0

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

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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.