Public record
Software health reportschema 0.12.0 · metrics 1.13.0 · 2026-07-18 14:27 UTC

materialsproject / pymatgen

Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.

Python · PolarCustom license★ 1,926 stars⑂ 959 forkssince Oct 2011View on GitHub ↗

materialsproject/pymatgen holds a health index of 86 out of 100, placing it in the Excellent band. It scores highest on Vitality (92/100) and lowest on AI Readiness (54/100). It was last updated 1 day ago. 5 contributors account for most of its recent work.

86
overall / 100
Excellent

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At risk ceiling of 49. AI Readiness sits outside the overall score.

86
Excellent85-100Exemplary; meets essentially all checked criteria
Good70-84Healthy; minor gaps
Moderate50-69Acceptable with notable gaps; review recommended
At risk30-49Significant weaknesses; adoption warrants caution
Critical1-29Severe 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.

Ownership

Materials ProjectOrganization
909 followers56 public repossince Jun 2011

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIpymatgen2026.5.4763,36741174 days agoabinitvaspanalysiscrystaldiagramselectronicgaussianmaterialsnwchemphaseprojectqchemsciencestructure

Metrics by category

Vitality

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

92Excellent · 22% of overall
How it's scored
36/36Push recency — last push 1 days ago
22.2/36Commit cadence — 32/52 weeks with commits
18/18Commit volume — 284 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year284
human_commit_share
days_since_last_push1
active_weeks_last_year32

Release discipline

100Excellent
How it's scored
27/27Ships releases — 100 releases published
36/36Release recency — latest release 74 days ago
27/27Release cadence — a release every ~42.2 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count100
latest_release_tagv2026.5.4
releases_from_tagsno
days_since_latest_release74
mean_days_between_releases42.2
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?

90Excellent · 18% of overall
How it's scored
53.3/60Stars — 1,926 stars
24.8/25Forks — 959 forks
11.3/15Watchers — 109 watchers
Inputs used
forks959
stars1,926
watchers109
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

86Excellent
How it's scored
22.5/22.5README
16.9/22.5License — license file present, not a recognized license
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
has_contributingyes
has_issue_templateno
has_code_of_conductyes
has_pull_request_templateyes
How it's scored
78.4/80Monthly downloads — 763,367 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagespymatgen
dependents
ecosystemspypi
total_downloads
monthly_downloads763,367
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?

85Excellent · 24% of overall
How it's scored
45.9/54Bus factor — 5 contributor(s) cover half of all commits
15.9/22.5Commit distribution — top contributor authored 29% of commits
13.5/13.5Contributor breadth — 100 contributors
10/10OpenSSF Scorecard: Contributors — project has 26 contributing companies or organizations
Inputs used
bus_factor5
contributors_sampled100
top_contributor_share0.292
How it's scored
42.6/46.8Issue resolution — 91% of issues closed
34.2/38.3PR acceptance — 2,709/3,034 decided PRs merged
4.5/15OpenSSF Scorecard: Code-Review — Found 8/21 approved changesets -- score normalized to 3
Inputs used
merged_prs2,709
open_issues135
closed_issues1,381
issue_closed_ratio0.911
closed_unmerged_prs325
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
21.3/25Owner reach — 909 followers of materialsproject
24.8/25Track record — 56 public repos, account ~15 yr old
Inputs used
followers909
owner_typeOrganization
is_verified
owner_loginmaterialsproject
public_repos56
account_age_days5,504
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 74 days ago
20/20Version history — 411 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagespymatgen
ecosystemspypi
any_deprecatedno
min_days_since_publish74

Engineering Quality

Are baseline engineering and documentation practices in place?

88Excellent · 20% of overall
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
6.4/6.4.editorconfig
6/20OpenSSF Scorecard: CI-Tests — 6 out of 17 merged PRs checked by a CI test -- score normalized to 3
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configyes
has_precommit_configyes

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://pymatgen.org
10/10Repository description
10/10Topics — 5 topics
0/10Wiki
Inputs used
topicsmaterials, science, materials-science, materials-informatics, python
has_wikino
homepagehttps://pymatgen.org
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

75Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
0.8/2.5CI-Tests — 6 out of 17 merged PRs checked by a CI test -- score normalized to 3
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
2.2/7.5Code-Review — Found 8/21 approved changesets -- score normalized to 3
2.5/2.5Contributors — project has 26 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.2/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
2.5/5SAST — SAST tool is not run on all commits -- score normalized to 5
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
7.5/7.5Token-Permissions — GitHub workflow tokens follow principle of least privilege
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate7.5
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? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score.

54Moderate · 0% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit history — no data
Inputs used
has_llms_txtno
legible_history_share
agent_instruction_files
agent_instruction_max_bytes
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
11/11Lint / format config
11/11Static type checking — src/pymatgen/py.typed
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no data
0/8Automated maintenance — no data
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesGemfile.lock, uv.lock
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configssrc/pymatgen/py.typed
agent_commit_share
toolchain_manifests
dependency_bot_commit_share
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.
How it's scored
27/45Type-checkable code — Python with type-check config (src/pymatgen/py.typed)
53/55Manageable file sizes — 9/249 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes116,065
source_files_sampled249
oversized_source_files9
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)
0/20MCP server
40/40Runnable examples — examples
Inputs used
example_dirsexamples
has_mcp_signalno
api_schema_files

Key facts

1,926GitHub stars
100contributors
284commits, last 12 months
1days since last push
100releases
5bus factor
135open issues
PyPI, RubyGemspackage ecosystems

More detail

OpenSSF Scorecard 7.5 / 10
7.5aggregate

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 · 2026-07-18 14:27 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
3CI-Tests6 out of 17 merged PRs checked by a CI test -- score normalized to 3
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3Code-ReviewFound 8/21 approved changesets -- score normalized to 3
10Contributorsproject has 26 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
10Maintained30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
5SASTSAST tool is not run on all commits -- score normalized to 5
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 9
RegistryPackageVersion constraintManifest
RubyGemsminima~> 2.5docs/Gemfile
RubyGemsgithub-pagesdocs/Gemfile
RubyGemsjekyll-feed~> 0.12docs/Gemfile
RubyGemstzinfo>= 1docs/Gemfile
RubyGemstzinfo-datadocs/Gemfile
RubyGemswdm~> 0.1.1docs/Gemfile
RubyGemshttp_parser.rb~> 0.6.0docs/Gemfile
RubyGemswebrick~> 1.8docs/Gemfile
PyPIpymatgen-core>=2026.7.16pyproject.toml
All dependencies 353

Full resolved dependency set from the GitHub dependency graph: 7 direct and 346 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

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              {
                "key": "repository_description",
                "name": "Repository description",
                "detail": null,
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
              },
              {
                "key": "topics",
                "name": "Topics",
                "detail": "5 topics",
                "points": 10,
                "status": "met",
                "details": [
                  {
                    "code": "topics_count",
                    "params": {
                      "count": 5
                    }
                  }
                ],
                "max_points": 10
              },
              {
                "key": "wiki",
                "name": "Wiki",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 10
              }
            ]
          }
        ],
        "description": "Are baseline engineering and documentation practices in place?"
      },
      {
        "key": "security",
        "band": "good",
        "name": "Security",
        "value": 75,
        "weight": 0.16,
        "metrics": [
          {
            "key": "security_posture",
            "band": "good",
            "name": "Security posture",
            "note": "Excluded from scoring (no data or not applicable): Branch-Protection, Signed-Releases. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "branch_protection",
                    "signed_releases"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 75,
            "inputs": {
              "source": "openssf_scorecard",
              "checks_evaluated": 16,
              "scorecard_version": "v5.5.0",
              "checks_inconclusive": 2,
              "scorecard_aggregate": 7.5
            },
            "components": [
              {
                "key": "binary_artifacts",
                "name": "Binary-Artifacts",
                "detail": "no binaries found in the repo",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "branch_protection",
                "name": "Branch-Protection",
                "detail": "internal 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",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 7.5
              },
              {
                "key": "ci_tests",
                "name": "CI-Tests",
                "detail": "6 out of 17 merged PRs checked by a CI test -- score normalized to 3",
                "points": 0.8,
                "status": "partial",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "cii_best_practices",
                "name": "CII-Best-Practices",
                "detail": "no effort to earn an OpenSSF best practices badge detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "code_review",
                "name": "Code-Review",
                "detail": "Found 8/21 approved changesets -- score normalized to 3",
                "points": 2.2,
                "status": "partial",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "contributors",
                "name": "Contributors",
                "detail": "project has 26 contributing companies or organizations",
                "points": 2.5,
                "status": "met",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "dangerous_workflow",
                "name": "Dangerous-Workflow",
                "detail": "no dangerous workflow patterns detected",
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
              },
              {
                "key": "dependency_update_tool",
                "name": "Dependency-Update-Tool",
                "detail": "update tool detected",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "fuzzing",
                "name": "Fuzzing",
                "detail": "project is not fuzzed",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "license",
                "name": "License",
                "detail": "license file detected",
                "points": 2.2,
                "status": "partial",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "maintained",
                "name": "Maintained",
                "detail": "30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "packaging",
                "name": "Packaging",
                "detail": "packaging workflow detected",
                "points": 5,
                "status": "met",
                "details": [],
                "max_points": 5
              },
              {
                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "sast",
                "name": "SAST",
                "detail": "SAST tool is not run on all commits -- score normalized to 5",
                "points": 2.5,
                "status": "partial",
                "details": [],
                "max_points": 5
              },
              {
                "key": "security_policy",
                "name": "Security-Policy",
                "detail": "security policy file detected",
                "points": 5,
                "status": "met",
                "details": [],
                "max_points": 5
              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
                "detail": "no releases found",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 7.5
              },
              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "GitHub workflow tokens follow principle of least privilege",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "0 existing vulnerabilities detected",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              }
            ]
          },
          {
            "key": "high_risk_jurisdiction_exposure",
            "band": "excellent",
            "name": "High-Risk Jurisdiction Exposure",
            "note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
            "notes": [
              {
                "code": "jurisdiction_evidence_limits",
                "params": {}
              }
            ],
            "value": 100,
            "inputs": {
              "meaning": "self-published location evidence; not nationality or citizenship",
              "red_flag": false,
              "exposures": [],
              "policy_countries": [
                "Russia",
                "Iran",
                "North Korea"
              ],
              "review_only_matches": 0,
              "assessed_self_published_locations": 7
            },
            "components": [
              {
                "key": "policy_exposure_multiplier",
                "name": "Policy exposure multiplier",
                "detail": "no confirmed policy-scope location match",
                "points": 100,
                "status": "met",
                "details": [
                  {
                    "code": "jurisdiction_no_match",
                    "params": {}
                  }
                ],
                "max_points": 100
              }
            ]
          }
        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
      },
      {
        "key": "ai_readiness",
        "band": "moderate",
        "name": "AI Readiness",
        "value": 54,
        "weight": 0,
        "metrics": [
          {
            "key": "ai_agent_context",
            "band": "critical",
            "name": "Agent context & guidance",
            "note": "Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "legible_commit_history"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 1,
            "inputs": {
              "has_llms_txt": false,
              "legible_history_share": null,
              "agent_instruction_files": [],
              "agent_instruction_max_bytes": null
            },
            "components": [
              {
                "key": "agent_instructions",
                "name": "Agent instructions",
                "detail": "no CLAUDE.md / AGENTS.md / editor rules",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_agent_instructions",
                    "params": {}
                  }
                ],
                "max_points": 45
              },
              {
                "key": "machine_readable_docs_llms_txt",
                "name": "Machine-readable docs (llms.txt)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 15
              },
              {
                "key": "legible_commit_history",
                "name": "Legible commit history",
                "detail": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
            "band": "excellent",
            "name": "Verify loop (build / test / typecheck)",
            "note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "demonstrated_agent_practice",
                    "automated_maintenance"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 88,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [
                "Gemfile.lock",
                "uv.lock"
              ],
              "has_dockerfile": false,
              "typed_language": false,
              "bootstrap_files": [
                "docs/Makefile"
              ],
              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [
                "src/pymatgen/py.typed"
              ],
              "agent_commit_share": null,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": null
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": "docs/Makefile",
                "points": 18,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "docs/Makefile"
                    }
                  }
                ],
                "max_points": 18
              },
              {
                "key": "automated_tests",
                "name": "Automated tests",
                "detail": null,
                "points": 22,
                "status": "met",
                "details": [],
                "max_points": 22
              },
              {
                "key": "lint_format_config",
                "name": "Lint / format config",
                "detail": null,
                "points": 11,
                "status": "met",
                "details": [],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
                "name": "Static type checking",
                "detail": "src/pymatgen/py.typed",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "src/pymatgen/py.typed"
                    }
                  }
                ],
                "max_points": 11
              },
              {
                "key": "reproducible_environment",
                "name": "Reproducible environment",
                "detail": "lockfile",
                "points": 10,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "lockfile"
                    }
                  }
                ],
                "max_points": 10
              },
              {
                "key": "demonstrated_agent_practice",
                "name": "Demonstrated agent practice",
                "detail": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 10
              },
              {
                "key": "automated_maintenance",
                "name": "Automated maintenance",
                "detail": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 8
              },
              {
                "key": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 10
              }
            ]
          },
          {
            "key": "ai_code_legibility",
            "band": "good",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 80,
            "inputs": {
              "primary_language": "Python",
              "largest_source_bytes": 116065,
              "source_files_sampled": 249,
              "oversized_source_files": 9
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python with type-check config (src/pymatgen/py.typed)",
                "points": 27,
                "status": "partial",
                "details": [
                  {
                    "code": "typecheck_config_language",
                    "params": {
                      "files": "src/pymatgen/py.typed",
                      "language": "Python"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "9/249 source files over 60KB",
                "points": 53,
                "status": "partial",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 249,
                      "oversized": 9
                    }
                  }
                ],
                "max_points": 55
              }
            ]
          },
          {
            "key": "ai_interfaces",
            "band": "at_risk",
            "name": "Machine-readable interfaces",
            "note": null,
            "notes": [],
            "value": 40,
            "inputs": {
              "example_dirs": [
                "examples"
              ],
              "has_mcp_signal": false,
              "api_schema_files": []
            },
            "components": [
              {
                "key": "api_schema_openapi_graphql_proto",
                "name": "API schema (OpenAPI/GraphQL/proto)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 40
              },
              {
                "key": "mcp_server",
                "name": "MCP server",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 20
              },
              {
                "key": "runnable_examples",
                "name": "Runnable examples",
                "detail": "examples",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "examples"
                    }
                  }
                ],
                "max_points": 40
              }
            ]
          }
        ],
        "description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
      }
    ],
    "metrics_version": "1.13.0"
  },
  "warnings": [],
  "report_type": "repository",
  "generated_at": "2026-07-18T14:27:57.670313Z",
  "schema_version": "0.12.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/m/materialsproject/pymatgen.svg",
  "full_name": "materialsproject/pymatgen",
  "license_state": "custom",
  "license_spdx": null
}

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 v1.13.0, schema v0.12.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.