Public record
Software health reportschema 0.11.0 · metrics 1.13.0 · 2026-07-17 03:34 UTC

DataDog / datadog-agent-dev

Tool for developing on the Datadog Agent platform

PythonMIT★ 8 stars⑂ 6 forkssince Sep 2024View on GitHub ↗

DataDog/datadog-agent-dev holds a health index of 66 out of 100, placing it in the Moderate band. It scores highest on Vitality (89/100) and lowest on Community & Adoption (48/100). It was last updated today. A single contributor accounts for most of its recent work.

66
overall / 100
Moderate

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.

66
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

Datadog, Inc.Organization
3,222 followers1,194 public repossince Aug 2010

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIdda0.36.1143,058577 days agoagentdatadog

Metrics by category

Vitality

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

89Excellent · 22% of overall
How it's scored
36/36Push recency — last push 0 days ago
23.5/36Commit cadence — 34/52 weeks with commits
18/18Commit volume — 101 commits in the last year
10/10OpenSSF Scorecard: Maintained — 26 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year101
human_commit_share
days_since_last_push0
active_weeks_last_year34
How it's scored
27/27Ships releases — 62 releases published
36/36Release recency — latest release 7 days ago
27/27Release cadence — a release every ~24.8 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count62
latest_release_tagv0.36.1
releases_from_tagsno
days_since_latest_release7
mean_days_between_releases24.8

Community & Adoption

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

48At risk · 18% of overall
How it's scored
13.7/60Stars — 8 stars
5.8/25Forks — 6 forks
3.9/15Watchers — 6 watchers
Inputs used
forks6
stars8
watchers6
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
has_contributingno
has_issue_templateno
has_code_of_conductno
has_pull_request_templateno
How it's scored
68.7/80Monthly downloads — 143,058 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesdda
dependents
ecosystemspypi
total_downloads
monthly_downloads143,058
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?

62Moderate · 24% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
5.9/22.5Commit distribution — top contributor authored 74% of commits
13.5/13.5Contributor breadth — 19 contributors
10/10OpenSSF Scorecard: Contributors — project has 3 contributing companies or organizations -- score normalized to 10
Inputs used
bus_factor1
contributors_sampled19
top_contributor_share0.738
How it's scored
0/46.8Issue resolution — 0% of issues closed
33.8/38.3PR acceptance — 249/282 decided PRs merged
9/15OpenSSF Scorecard: Code-Review — Found 17/28 approved changesets -- score normalized to 6
Inputs used
merged_prs249
open_issues2
closed_issues0
issue_closed_ratio0
closed_unmerged_prs33
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
25/25Owner reach — 3,222 followers of DataDog
25/25Track record — 1,194 public repos, account ~15 yr old
Inputs used
followers3,222
owner_typeOrganization
is_verified
owner_loginDataDog
public_repos1,194
account_age_days5,814
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 7 days ago
20/20Version history — 57 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesdda
ecosystemspypi
any_deprecatedno
min_days_since_publish7

Engineering Quality

Are baseline engineering and documentation practices in place?

74Good · 20% of overall
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
16/16Linter config — ruff.toml
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — 1 out of 30 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — http://datadoghq.dev/datadog-agent-dev/
10/10Repository description
10/10Topics — 5 topics
0/10Wiki
Inputs used
topicsdatadog, datadog-agent, cli, python, tooling
has_wikino
homepagehttp://datadoghq.dev/datadog-agent-dev/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

52Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
3/7.5Branch-Protection — branch protection is not maximal on development and all release branches
0/2.5CI-Tests — 1 out of 30 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
4.5/7.5Code-Review — Found 17/28 approved changesets -- score normalized to 6
2.5/2.5Contributors — project has 3 contributing companies or organizations -- score normalized to 10
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 — 26 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
4.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 9
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 97 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated18
scorecard_versionv5.5.0
checks_inconclusive0
scorecard_aggregate5.2

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.

58Moderate · 0% of overall
How it's scored
18/45Agent instructions — tests/cli/validate/fixtures/ai_rules/out_of_sync/CLAUDE.md (stub)
0/15Machine-readable docs (llms.txt)
0/40Legible commit history — no data
Inputs used
has_llms_txtno
legible_history_share
agent_instruction_filestests/cli/validate/fixtures/ai_rules/out_of_sync/CLAUDE.md
agent_instruction_max_bytes12
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — ruff.toml
11/11Static type checking — src/dda/py.typed
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no data
0/8Automated maintenance — no data
9/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 9
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configssrc/dda/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/dda/py.typed)
54.8/55Manageable file sizes — 1/253 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes62,597
source_files_sampled253
oversized_source_files1
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

8GitHub stars
19contributors
101commits, last 12 months
0days since last push
62releases
1bus factor
2open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 5.2 / 10
5.2aggregate

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 · 2026-07-17 03:34 UTC

10Binary-Artifactsno binaries found in the repo
4Branch-Protectionbranch protection is not maximal on development and all release branches
0CI-Tests1 out of 30 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
6Code-ReviewFound 17/28 approved changesets -- score normalized to 6
10Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained26 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
9Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 9
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities97 existing vulnerabilities detected
Direct dependencies 25
RegistryPackageVersion constraintManifest
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All dependencies 202

Full resolved dependency set from the GitHub dependency graph: 25 direct and 177 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

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Raw JSON report machine-readable
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                "key": "openssf_scorecard_signed_releases",
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                "key": "commit_distribution",
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                "key": "openssf_scorecard_contributors",
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                "max_points": 10
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              "merged_prs": 249,
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                "key": "issue_resolution",
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                "key": "pr_acceptance",
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                "max_points": 38.25
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                "key": "openssf_scorecard_code_review",
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          {
            "key": "stewardship",
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            "notes": [],
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            "inputs": {
              "followers": 3222,
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                "key": "verified_domain",
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              },
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                "key": "owner_reach",
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                "key": "track_record",
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        ],
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                "key": "linter_config",
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                "key": "documentation_directory",
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          }
        ],
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                "key": "code_review",
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              },
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                "key": "dangerous_workflow",
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              },
              {
                "key": "dependency_update_tool",
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              },
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                "key": "fuzzing",
                "name": "Fuzzing",
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              },
              {
                "key": "maintained",
                "name": "Maintained",
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                "key": "packaging",
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                "details": [],
                "max_points": 5
              },
              {
                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 9",
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                "max_points": 5
              },
              {
                "key": "sast",
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              },
              {
                "key": "security_policy",
                "name": "Security-Policy",
                "detail": "security policy file not detected",
                "points": 0,
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              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
                "detail": "Project has not signed or included provenance with any releases.",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "detected GitHub workflow tokens with excessive permissions",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "97 existing vulnerabilities detected",
                "points": 0,
                "status": "missed",
                "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": 8
            },
            "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": 58,
        "weight": 0,
        "metrics": [
          {
            "key": "ai_agent_context",
            "band": "at_risk",
            "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": 30,
            "inputs": {
              "has_llms_txt": false,
              "legible_history_share": null,
              "agent_instruction_files": [
                "tests/cli/validate/fixtures/ai_rules/out_of_sync/CLAUDE.md"
              ],
              "agent_instruction_max_bytes": 12
            },
            "components": [
              {
                "key": "agent_instructions",
                "name": "Agent instructions",
                "detail": "tests/cli/validate/fixtures/ai_rules/out_of_sync/CLAUDE.md (stub)",
                "points": 18,
                "status": "partial",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "tests/cli/validate/fixtures/ai_rules/out_of_sync/CLAUDE.md"
                    }
                  },
                  {
                    "code": "agent_instructions_stub",
                    "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": "good",
            "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": 77,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [
                "uv.lock"
              ],
              "has_dockerfile": false,
              "typed_language": false,
              "bootstrap_files": [],
              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [
                "src/dda/py.typed"
              ],
              "agent_commit_share": null,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": null
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "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": "ruff.toml",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "ruff.toml"
                    }
                  }
                ],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
                "name": "Static type checking",
                "detail": "src/dda/py.typed",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "src/dda/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 9",
                "points": 9,
                "status": "partial",
                "details": [],
                "max_points": 10
              }
            ]
          },
          {
            "key": "ai_code_legibility",
            "band": "good",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 82,
            "inputs": {
              "primary_language": "Python",
              "largest_source_bytes": 62597,
              "source_files_sampled": 253,
              "oversized_source_files": 1
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python with type-check config (src/dda/py.typed)",
                "points": 27,
                "status": "partial",
                "details": [
                  {
                    "code": "typecheck_config_language",
                    "params": {
                      "files": "src/dda/py.typed",
                      "language": "Python"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "1/253 source files over 60KB",
                "points": 54.8,
                "status": "partial",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 253,
                      "oversized": 1
                    }
                  }
                ],
                "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": "2026-07-17T03:34:35.224806Z",
  "schema_version": "0.11.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/d/DataDog/datadog-agent-dev.svg",
  "full_name": "DataDog/datadog-agent-dev",
  "license_state": "standard",
  "license_spdx": "MIT"
}

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 v0.11.0 — full methodology · metrics wiki.

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