Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-17 20:14 UTC

cisco-ai-defense / skill-scanner

Security Scanner for Agent Skills

PythonCustom license★ 2,529 stars⑂ 321 forkssince Jan 2026View on GitHub ↗
KindCommand-line toolLibraryNetwork serviceTerminal interfacehow this is determined

cisco-ai-defense/skill-scanner holds a health index of 94 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (95/100) and lowest on Security (70/100). It was last updated 11 days ago. 4 contributors account for most of its recent work.

94
overall / 100
Exceptional

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.

94
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 81 is calibrated to 94 on the published index scale (record calibration 2026-08-02).

Ownership

Cisco AI DefenseOrganization
565 followers17 public repossince Jul 2025

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

Package ecosystems

Metrics by category

Vitality

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

82Excellent · 21% of overall
How it's scored
28.8/36Push recency — last push 11 days ago
13.2/36Commit cadence — 19/52 weeks with commits
18/18Commit volume — 104 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year104
human_commit_share1
days_since_last_push11
active_weeks_last_year19

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 20 releases published
36/36Release recency — latest release 12 days ago
27/27Release cadence — a release every ~18.2 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count20
latest_release_tag2.1.0
releases_from_tagsno
days_since_latest_release12
mean_days_between_releases18.2
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?

86Excellent · 17% of overall
How it's scored
55.2/60Stars — 2,529 stars
20.9/25Forks — 321 forks
5.6/15Watchers — 11 watchers
Inputs used
forks321
stars2,529
watchers11
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
readme_badges7
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateyes
How it's scored
73.8/80Monthly downloads — 340,595 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagescisco-ai-skill-scanner
dependents—
ecosystemspypi
total_downloads—
monthly_downloads340,595
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?

75Good · 23% of overall
How it's scored
43.2/54Bus factor — 4 contributor(s) cover half of all commits
13.2/22.5Commit distribution — top contributor authored 41% of commits
13.5/13.5Contributor breadth — 41 contributors
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor4
contributors_sampled41
top_contributor_share0.413
How it's scored
40/42Issue resolution — 95% of issues closed
24.4/30PR acceptance — 121/149 decided PRs merged
0/13Newcomer PR acceptance — 0/5 first-time contributors' PRs merged in 30d
7.5/15OpenSSF Scorecard: Code-Review — Found 16/30 approved changesets -- score normalized to 5
Inputs used
merged_prs121
open_issues3
closed_issues61
prs_merged_7d0
prs_decided_7d0
prs_merged_30d34
prs_decided_30d40
issue_closed_ratio0.953
closed_unmerged_prs28
first_time_authors_30d5
first_time_prs_merged_30d0
first_time_prs_decided_30d5
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
19.8/25Owner reach — 565 followers of cisco-ai-defense
11.5/25Track record — 17 public repos, account ~1 yr old
Inputs used
followers565
owner_typeOrganization
is_verifiedno
owner_logincisco-ai-defense
public_repos17
account_age_days429

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 11 days ago
20/20Version history — 19 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagescisco-ai-skill-scanner
ecosystemspypi
any_deprecatedno
min_days_since_publish11

Engineering Quality

Are baseline engineering and documentation practices in place?

95Exceptional · 19% of overall
How it's scored
24/24CI workflows — 9 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
18/20OpenSSF Scorecard: CI-Tests — 28 out of 30 merged PRs checked by a CI test -- score normalized to 9
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://cisco-ai-defense.github.io/docs/skill-scanner
10/10Repository description
10/10Topics — 3 topics
10/10Wiki
Inputs used
topicsagent, agent-skills, security
has_wikiyes
homepagehttps://cisco-ai-defense.github.io/docs/skill-scanner
docs_sitehttps://cisco-ai-defense.github.io/docs/skill-scanner
has_readmeyes
has_docs_diryes
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-Artifacts — no binaries found in the repo
6/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.2/2.5CI-Tests — 28 out of 30 merged PRs checked by a CI test -- score normalized to 9
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
3.8/7.5Code-Review — Found 16/30 approved changesets -- score normalized to 5
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.2/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 0 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
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 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 advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages94
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:cisco-ai-skill-scanner@2.1.0 runtime dependency closure — what installing the published package pulls in — 94 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.

78Good · 4% of overall
How it's scored
45/45Agent instructions — .cursor/rules/codeguard-0-additional-cryptography.mdc, .cursor/rules/codeguard-0-framework-and-languages.mdc, .cursor/rules/codeguard-0-iac-security.mdc, .cursor/rules/codeguard-0-mobile-apps.mdc, .cursor/rules/codeguard-0-supply-chain-security.mdc, .cursor/rules/codeguard-1-crypto-algorithms.mdc, .cursor/rules/codeguard-1-digital-certificates.mdc, .cursor/rules/codeguard-1-hardcoded-credentials.mdc, .cursor/rules/no-cursor-co-author.mdc
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://docs.cursor.com/llms.txt)
40/40Legible commit history — 96 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://docs.cursor.com/llms.txt
legible_history_share0.96
agent_instruction_files.cursor/rules/codeguard-0-additional-cryptography.mdc, .cursor/rules/codeguard-0-framework-and-languages.mdc, .cursor/rules/codeguard-0-iac-security.mdc, .cursor/rules/codeguard-0-mobile-apps.mdc, .cursor/rules/codeguard-0-supply-chain-security.mdc, .cursor/rules/codeguard-1-crypto-algorithms.mdc, .cursor/rules/codeguard-1-digital-certificates.mdc, .cursor/rules/codeguard-1-hardcoded-credentials.mdc, .cursor/rules/no-cursor-co-author.mdc
agent_instruction_max_bytes6,285
How it's scored
18/18One-command bootstrap — Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environment — lockfile
10/10Demonstrated agent practice — 12 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesgo.sum, uv.lock
has_dockerfileno
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0.12
toolchain_manifeststools/cel_runtime/go.mod
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Python without a type-check config
51.8/55Manageable file sizes — 23/399 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes251,874
source_files_sampled399
oversized_source_files23
How it's scored
40/40API schema (OpenAPI/GraphQL/proto) — skill_scanner/core/semantic/scan_facts.proto
0/20MCP server
40/40Runnable examples — examples
Inputs used
example_dirsexamples
has_mcp_signalno
api_schema_filesskill_scanner/core/semantic/scan_facts.proto
interfaces_expected_ofnetwork-service

Key facts

2,529GitHub stars
41contributors
104commits, last 12 months
11days since last push
20releases
4bus factor
3open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

More detail

Star and fork history 0 ★ / 321 ⇿
0Stars
321Forks
20Releases

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.

0125250375320172026-012026-052026-09
Major 2Minor 1Patch 16
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 · 2026-09-17 20:13 UTC

10Binary-Artifactsno binaries found in the repo
8Branch-Protectionbranch protection is not maximal on development and all release branches
9CI-Tests28 out of 30 merged PRs checked by a CI test -- score normalized to 9
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
5Code-ReviewFound 16/30 approved changesets -- score normalized to 5
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
10Maintained30 commit(s) and 0 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
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 21
RegistryPackageVersion constraintManifest
PyPIPyYAML>=6.0,<7pyproject.toml
PyPIpython-frontmatter>=1.1,<2pyproject.toml
PyPIrich>=14.0,<15pyproject.toml
PyPItextual>=7.0,<9pyproject.toml
PyPItabulate>=0.9,<1pyproject.toml
PyPIpydantic>=2.10,<3pyproject.toml
PyPIprotobuf>=5.29,<7pyproject.toml
PyPIfastapi>=0.115,<1pyproject.toml
PyPIuvicorn>=0.34,<1pyproject.toml
PyPIpython-multipart>=0.0.31,<0.1pyproject.toml
PyPIyara-x>=1.10,<2pyproject.toml
PyPIpython-dotenv>=1.0,<2pyproject.toml
PyPIhttpx>=0.27,<1pyproject.toml
PyPImagika>=1.0,<2pyproject.toml
PyPIpdfid>=1.1,<2pyproject.toml
PyPIoletools>=0.60,<1pyproject.toml
PyPIconfusable-homoglyphs>=3.3,<4pyproject.toml
PyPIanthropic>=0.50,<1pyproject.toml
PyPIopenai>=2.0,<3pyproject.toml
PyPIlitellm>=1.84.0,<2pyproject.toml
PyPIclick>=8.3.3pyproject.toml
All dependencies not collected

The resolved dependency set could not be collected for this report: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

Dependency advisories 0

Installing pypi:cisco-ai-skill-scanner@2.1.0 pulls in 94 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 statistics — PyPI.