Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-03 17:48 UTC

JingbiaoMei / Tokdash

Agent Dashboard: Visualization and analytics for Sessions and Quota Usage. Track, analyze, and optimize token usage across providers with heatmaps, cost tracking, token counting and quota resets..

Python · HTMLMIT★ 84 stars⑂ 19 forkssince Feb 2026View on GitHub ↗
KindLibraryCommand-line toolNetwork serviceWeb interfaceTerminal interfacehow this is determined

JingbiaoMei/Tokdash holds a health index of 83 out of 100, placing it in the Excellent band. It scores highest on Vitality (90/100) and lowest on Community & Adoption (56/100). It was last updated today. A single contributor accounts for most of its recent work.

83
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.

83
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 70 is calibrated to 83 on the published index scale (record calibration 2026-08-02).

Ownership

Jingbiao MeiPersonal account
23 followers27 public repossince Feb 2019University of Cambridge

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 publishTags
PyPItokdash2.6.93,4021100 days agotokencostdashboardllmaicodexclaudegeminiantigravitykimi

Metrics by category

Vitality

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

90Excellent · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
20.1/36Commit cadence — 29/52 weeks with commits
18/18Commit volume — 483 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 19 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year483
human_commit_share1
days_since_last_push0
active_weeks_last_year29

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 76 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~1.2 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count76
latest_release_tagv2.6.9
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases1.2
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?

56Moderate · 17% of overall
How it's scored
31.1/60Stars — 84 stars
10.5/25Forks — 19 forks
0/15Watchers — 2 watchers
Inputs used
forks19
stars84
watchers2
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_badges5
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateno
How it's scored
47.1/80Monthly downloads — 3,402 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagestokdash
dependents—
ecosystemspypi
total_downloads—
monthly_downloads3,402
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?

62Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
2.5/22.5Commit distribution — top contributor authored 89% of commits
13.5/13.5Contributor breadth — 12 contributors
6/10OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled12
top_contributor_share0.891
How it's scored
36.9/42Issue resolution — 88% of issues closed
27/30PR acceptance — 118/131 decided PRs merged
8.7/13Newcomer PR acceptance — 16/24 first-time contributors' PRs merged in 30d
4.5/15OpenSSF Scorecard: Code-Review — Found 8/22 approved changesets -- score normalized to 3
Inputs used
merged_prs118
open_issues4
closed_issues29
prs_merged_7d21
prs_decided_7d29
prs_merged_30d52
prs_decided_30d60
issue_closed_ratio0.879
closed_unmerged_prs13
first_time_authors_30d5
first_time_prs_merged_30d16
first_time_prs_decided_30d24
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
9.9/25Owner reach — 23 followers of JingbiaoMei
22.5/25Track record — 27 public repos, account ~7 yr old
Inputs used
followers23
owner_typeUser
is_verified—
owner_loginJingbiaoMei
public_repos27
account_age_days2,788
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 — 110 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagestokdash
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

80Excellent · 19% of overall
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
18/20OpenSSF Scorecard: CI-Tests — 17 out of 18 merged PRs checked by a CI test -- score normalized to 9
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://tokdash.github.io
10/10Repository description
10/10Topics — 17 topics
10/10Wiki
Inputs used
topicsanalytics, anthropic, dashboard, visualization, developer-tools, agent, claude-code, claude-code-plugin, codex, codex-cli, dsh-plugin, kimi-cli, token-efficiency, token-usage, deepseek-harness, opencode, pi
has_wikiyes
homepagehttps://tokdash.github.io
docs_sitehttps://tokdash.github.io
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

57Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
2.2/2.5CI-Tests — 17 out of 18 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
2.2/7.5Code-Review — Found 8/22 approved changesets -- score normalized to 3
1.5/2.5Contributors — project has 2 contributing companies or organizations -- score normalized to 6
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 — 30 commit(s) and 19 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
2/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 4
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
2.2/7.5Vulnerabilities — 7 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5.7
Excluded from scoring (no data or not applicable): Signed-Releases. Remaining weights renormalized.

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.

74Good · 4% of overall
How it's scored
45/45Agent instructions — docs/guides/agents/openclaw_reporting/AGENTS.md, docs/guides/agents/systemd/AGENTS.md
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://dev.meta.ai/llms.txt)
40/40Legible commit history — 83 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://dev.meta.ai/llms.txt
legible_history_share0.83
agent_instruction_filesdocs/guides/agents/openclaw_reporting/AGENTS.md, docs/guides/agents/systemd/AGENTS.md
agent_instruction_max_bytes4,524
How it's scored
12.6/18One-command bootstrap — companion/windows/TokdashCompanion.Tests/TokdashCompanion.Tests.csproj, companion/windows/TokdashCompanion/TokdashCompanion.csproj (toolchain convention, no task runner)
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environment — lockfile
10/10Demonstrated agent practice — 9 of the last 100 commits agent-authored or agent-credited
5/8Automated maintenance — dependency automation configured, none observed in the sampled commits
4/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 4
Inputs used
has_nixno
has_testsyes
lockfilespackages.lock.json
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share0.09
toolchain_manifestscompanion/windows/TokdashCompanion.Tests/TokdashCompanion.Tests.csproj, companion/windows/TokdashCompanion/TokdashCompanion.csproj
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Python without a type-check config
50.7/55Manageable file sizes — 22/279 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes411,622
source_files_sampled279
oversized_source_files22

Key facts

84GitHub stars
12contributors
483commits, last 12 months
0days since last push
76releases
1bus factor
4open 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
  • deps.dev does not index pypi:tokdash@2.6.9; advisories assessed against the repository dependency graph instead

More detail

Star and fork history 0 ★ / 19 ⇿
0Stars
19Forks
72Releases

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.

0481216201922026-032026-062026-09
Major 2Minor 15Patch 43
OpenSSF Scorecard 5.7 / 10
5.7aggregate

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 · 2026-10-03 17:48 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
9CI-Tests17 out of 18 merged PRs checked by a CI test -- score normalized to 9
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3Code-ReviewFound 8/22 approved changesets -- score normalized to 3
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 19 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
4Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 4
0SASTSAST tool is not run on all commits -- score normalized to 0
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
3Vulnerabilities7 existing vulnerabilities detected
Direct dependencies 5
RegistryPackageVersion constraintManifest
PyPIfastapi>=0.115.0pyproject.toml
PyPIuvicorn>=0.32.0pyproject.toml
PyPIpackaging>=21.0pyproject.toml
PyPIzstandard>=0.23pyproject.toml
PyPItextual>=8.0.0,<9pyproject.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

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.