Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-13 14:27 UTC

MagnivOrg / prompt-layer-library

🍰 PromptLayer - Maintain a log of your prompts and OpenAI API requests. Track, debug, and replay old completions.

PythonApache-2.0★ 787 stars⑂ 95 forkssince Dec 2022View on GitHub ↗

KindCommand-line toolLibraryhow this is determined

#gpt #machine-learning #openai #prompt #prompt-engineering #python

MagnivOrg/prompt-layer-library holds a health index of 90 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (90/100) and lowest on Community & Adoption (65/100). It was last updated 24 days ago. 2 contributors account for most of its recent work.

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.

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)

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 76 is calibrated to 90 on the published index scale (record calibration 2026-08-02).

Ownership

PromptLayerOrganization

80 followers25 public repossince Dec 2021

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

Package ecosystems

Registry	Package	Version	Downloads / mo	Versions	Last publish
PyPI	promptlayer	1.5.16	115,889	205	24 days ago

Metrics by category

Vitality

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

81Excellent · 21% of overall

Development activity

77Good

How it's scored

28.8/36	Push recency — last push 24 days ago
20.1/36	Commit cadence — 29/52 weeks with commits
18/18	Commit volume — 126 commits in the last year
10/10	OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10

Inputs used

commits_last_year	126
human_commit_share	0.94
days_since_last_push	24
active_weeks_last_year	29

Release discipline

88Excellent

How it's scored

16.2/27	Ships releases — 39 version tags (no GitHub releases)
36/36	Release recency — latest release 24 days ago
27/27	Release cadence — a release every ~1.7 days
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count	39
latest_release_tag	v1.5.16
releases_from_tags	yes
days_since_latest_release	24
mean_days_between_releases	1.7

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?

65Good · 17% of overall

Popularity & adoption

67Good

How it's scored

47/60	Stars — 787 stars
16.4/25	Forks — 95 forks
3.9/15	Watchers — 6 watchers

Inputs used

forks	95
stars	787
watchers	6
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

50Moderate

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (Apache-2.0)
0/18	CONTRIBUTING guide
0/13.5	Code of conduct
0/7.2	Issue template
0/6.3	PR template

Inputs used

has_readme	yes
has_license	yes
readme_badges	2
has_contributing	no
has_issue_template	no
has_code_of_conduct	no
readme_badge_services	shields.io
has_pull_request_template	no

Ecosystem adoption (downloads)

84Excellent

How it's scored

67.5/80	Monthly downloads — 115,889 downloads/month across pypi
0/20	Registry dependents — not reported by this ecosystem

Inputs used

packages	promptlayer
dependents	—
ecosystems	pypi
total_downloads	—
monthly_downloads	115,889
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?

73Good · 23% of overall

Maintainer resilience (bus factor)

62Moderate

How it's scored

25.2/54	Bus factor — 2 contributor(s) cover half of all commits
13.3/22.5	Commit distribution — top contributor authored 41% of commits
13.5/13.5	Contributor breadth — 26 contributors
10/10	OpenSSF Scorecard: Contributors — project has 5 contributing companies or organizations

Inputs used

bus_factor	2
contributors_sampled	26
top_contributor_share	0.408

Issue & PR responsiveness

74Good

How it's scored

34.4/42	Issue resolution — 82% of issues closed
24.6/30	PR acceptance — 204/249 decided PRs merged
0/13	Newcomer PR acceptance — 0/4 first-time contributors' PRs merged in 30d
15/15	OpenSSF Scorecard: Code-Review — all changesets reviewed

Inputs used

merged_prs	204
open_issues	18
closed_issues	81
prs_merged_7d	0
prs_decided_7d	0
prs_merged_30d	2
prs_decided_30d	6
issue_closed_ratio	0.818
closed_unmerged_prs	45
first_time_authors_30d	2
first_time_prs_merged_30d	0
first_time_prs_decided_30d	4

Ownership & stewardship

64Moderate

How it's scored

30/30	Ownership backing — organization-owned
0/20	Verified domain
13.7/25	Owner reach — 80 followers of MagnivOrg
19.8/25	Track record — 25 public repos, account ~4 yr old

Inputs used

followers	80
owner_type	Organization
is_verified	no
owner_login	MagnivOrg
public_repos	25
account_age_days	1,726

Package maintenance

100Exceptional

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
35/35	Publish recency — latest publish 24 days ago
20/20	Version history — 205 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	promptlayer
ecosystems	pypi
any_deprecated	no
min_days_since_publish	24

Engineering Quality

Are baseline engineering and documentation practices in place?

90Excellent · 19% of overall

Engineering practices

100Exceptional

How it's scored

24/24	CI workflows — 3 workflow(s)
24/24	Tests present
16/16	Linter config — pyproject.toml ([tool.ruff])
9.6/9.6	Pre-commit hooks
6.4/6.4	.editorconfig
20/20	OpenSSF Scorecard: CI-Tests — 18 out of 18 merged PRs checked by a CI test -- score normalized to 10

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	yes
has_linter_config	yes
has_precommit_config	yes

Documentation

75Good

How it's scored

30/30	README
0/25	Documentation directory
15/15	Documentation / homepage site — https://www.promptlayer.com
10/10	Repository description
10/10	Topics — 6 topics
10/10	Wiki

Inputs used

topics	gpt, machine-learning, openai, prompt, prompt-engineering, python
has_wiki	yes
homepage	https://www.promptlayer.com
docs_site	https://www.promptlayer.com
has_readme	yes
has_docs_dir	no
has_description	yes

Security

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

69Good · 16% of overall

Security posture

61Moderate

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
3.8/7.5	Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5	CI-Tests — 18 out of 18 merged PRs checked by a CI test -- score normalized to 10
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
7.5/7.5	Code-Review — all changesets reviewed
2.5/2.5	Contributors — project has 5 contributing companies or organizations
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5	Dependency-Update-Tool — update tool detected
0/5	Fuzzing — project is not fuzzed
2.5/2.5	License — license file detected
7.5/7.5	Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
0/5	Packaging — no data
0/5	Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
5/5	SAST — SAST tool is run on all commits
0/5	Security-Policy — security policy file not detected
0/7.5	Signed-Releases — no data
0/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5	Vulnerabilities — 82 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	16
scorecard_version	v5.5.0
checks_inconclusive	2
scorecard_aggregate	6.1

Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional

How it's scored

35/35	Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25	Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40	No advisories left outstanding — no advisory carries a publication date

Inputs used

source	osv
advisories	0
affected_packages	0
assessed_packages	43
unassessed_packages	0
affected_by_severity	none
direct_affected_packages	0

Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:promptlayer@1.5.16 runtime dependency closure — what installing the published package pulls in — 43 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.

68Good · 4% of overall

Agent context & guidance

55Moderate

How it's scored

0/45	Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
15/15	Machine-readable docs (llms.txt) — llms.txt served by the project website (https://www.promptlayer.com/llms.txt)
40/40	Legible commit history — 73 of 94 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	yes
llms_txt_url	https://www.promptlayer.com/llms.txt
legible_history_share	0.777
agent_instruction_files	—
agent_instruction_max_bytes	—

Verify loop (build / test / typecheck)

71Good

How it's scored

18/18	One-command bootstrap — Makefile
22/22	Automated tests
11/11	Lint / format config — pyproject.toml ([tool.ruff])
0/11	Static type checking
10/10	Reproducible environment — devcontainer, lockfile
10/10	Demonstrated agent practice — 10 of the last 100 commits agent-authored or agent-credited
0/8	Automated maintenance — no automated dependency updates observed
0/10	OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0

Inputs used

has_nix	no
has_tests	yes
lockfiles	poetry.lock, uv.lock
has_dockerfile	no
typed_language	no
bootstrap_files	Makefile
has_devcontainer	yes
has_linter_config	yes
typecheck_configs	—
agent_commit_share	0.1
toolchain_manifests	—
dependency_bot_commit_share	0

Code legibility for models

54Moderate

How it's scored

0/45	Type-checkable code — Python without a type-check config
54.2/55	Manageable file sizes — 2/137 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	109,917
source_files_sampled	137
oversized_source_files	2

Machine-readable interfaces

100Exceptional

How it's scored

0/40	API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20	MCP server — not applicable to this kind of software
40/40	Runnable examples — examples

Inputs used

example_dirs	examples
has_mcp_signal	no
api_schema_files	—
interfaces_expected_of	—

Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

787GitHub stars

26contributors

126commits, last 12 months

24days since last push

39releases

2bus factor

18open issues

PyPIpackage ecosystems

Data collection warnings

Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 95 ⇿

0Stars

95Forks

39Releases

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.

Major 0Minor 5Patch 34

Each point covers 4 days.

OpenSSF Scorecard 6.1 / 10

6.1aggregate

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 · 2026-09-13 14:26 UTC

10	Binary-Artifacts	no binaries found in the repo
5	Branch-Protection	branch protection is not maximal on development and all release branches
10	CI-Tests	18 out of 18 merged PRs checked by a CI test -- score normalized to 10
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
10	Code-Review	all changesets reviewed
10	Contributors	project has 5 contributing companies or organizations
10	Dangerous-Workflow	no dangerous workflow patterns detected
10	Dependency-Update-Tool	update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
10	Maintained	30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
n/a	Packaging	packaging workflow not detected
0	Pinned-Dependencies	dependency not pinned by hash detected -- score normalized to 0
10	SAST	SAST tool is run on all commits
0	Security-Policy	security policy file not detected
n/a	Signed-Releases	no releases found
0	Token-Permissions	detected GitHub workflow tokens with excessive permissions
0	Vulnerabilities	82 existing vulnerabilities detected

Direct dependencies 20

Registry	Package	Version constraint	Manifest
PyPI	requests	`^2.31.0`	pyproject.toml
PyPI	opentelemetry-api	`—`	pyproject.toml
PyPI	opentelemetry-sdk	`—`	pyproject.toml
PyPI	opentelemetry-exporter-otlp-proto-http	`—`	pyproject.toml
PyPI	aiohttp	`^3.10.10`	pyproject.toml
PyPI	httpx	`^0.28.1`	pyproject.toml
PyPI	nest-asyncio	`^1.6.0`	pyproject.toml
PyPI	centrifuge-python	`^0.4.1`	pyproject.toml
PyPI	tenacity	`^9.1.2`	pyproject.toml
PyPI	cachetools	`^5.0.0`	pyproject.toml
PyPI	openrouter	`^1.1.2`	pyproject.toml
PyPI	openai-agents	`^0.3.3`	pyproject.toml
PyPI	claude-agent-sdk	`>=0.1.45,<1.0.0`	pyproject.toml
PyPI	opentelemetry-instrumentation-genai-openai	`>=1.0b0,<1.1b0`	pyproject.toml
PyPI	opentelemetry-instrumentation-genai-anthropic	`>=1.0b0,<1.1b0`	pyproject.toml
PyPI	opentelemetry-instrumentation-google-genai	`>=1.0b1,<1.1b0`	pyproject.toml
PyPI	opentelemetry-instrumentation-botocore	`0.65b0`	pyproject.toml
PyPI	eval-type-backport	`^0.3.1`	pyproject.toml
PyPI	jinja2	`^3.1.6`	pyproject.toml
PyPI	rich	`>=13.0.0`	pyproject.toml

All dependencies 108

Full resolved dependency set from the GitHub dependency graph: 14 direct and 94 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	aiohttp	`3.10.10`	direct
PyPI	cachetools	`5.5.2`	direct
PyPI	centrifuge-python	`0.4.1`	direct
PyPI	claude-agent-sdk	`0.1.49`	direct
PyPI	eval-type-backport	`0.3.1`	direct
PyPI	httpx	`0.28.1`	direct
PyPI	jinja2	`3.1.6`	direct
PyPI	nest-asyncio	`1.6.0`	direct
PyPI	openai-agents	`0.3.3`	direct
PyPI	opentelemetry-api	`1.26.0`	direct
PyPI	opentelemetry-exporter-otlp-proto-http	`1.26.0`	direct
PyPI	opentelemetry-sdk	`1.26.0`	direct
PyPI	requests	`2.31.0`	direct
PyPI	tenacity	`9.1.2`	direct
PyPI	ably	`2.1.1`	indirect
PyPI	aioboto3	`13.4.0`	indirect
PyPI	aiobotocore	`2.18.0`	indirect
PyPI	aiofiles	`24.1.0`	indirect
PyPI	aiohappyeyeballs	`2.4.3`	indirect
PyPI	aioitertools	`0.12.0`	indirect
PyPI	aiosignal	`1.3.1`	indirect
PyPI	annotated-types	`0.7.0`	indirect
PyPI	anthropic	`0.84.0`	indirect
PyPI	anyio	`4.8.0`	indirect
PyPI	async-timeout	`4.0.3`	indirect
PyPI	attrs	`23.2.0`	indirect
PyPI	boto3	`1.36.1`	indirect
PyPI	botocore	`1.36.1`	indirect
PyPI	certifi	`2024.2.2`	indirect
PyPI	cffi	`2.0.0`	indirect
PyPI	charset-normalizer	`3.3.2`	indirect
PyPI	click	`8.3.1`	indirect
PyPI	colorama	`0.4.6`	indirect
PyPI	cryptography	`46.0.5`	indirect
PyPI	deprecated	`1.2.14`	indirect
PyPI	distro	`1.9.0`	indirect
PyPI	docstring-parser	`0.17.0`	indirect
PyPI	exceptiongroup	`1.2.1`	indirect
PyPI	frozenlist	`1.4.1`	indirect
PyPI	google-auth	`2.38.0`	indirect
PyPI	google-genai	`1.46.0`	indirect
PyPI	googleapis-common-protos	`1.73.0`	indirect
PyPI	griffe	`1.14.0`	indirect
PyPI	h11	`0.14.0`	indirect
PyPI	h2	`4.1.0`	indirect
PyPI	hpack	`4.0.0`	indirect
PyPI	httpcore	`1.0.5`	indirect
PyPI	httpx-sse	`0.4.3`	indirect
PyPI	hyperframe	`6.0.1`	indirect
PyPI	idna	`3.7`	indirect
PyPI	importlib-metadata	`8.0.0`	indirect
PyPI	iniconfig	`2.0.0`	indirect
PyPI	jiter	`0.8.2`	indirect
PyPI	jmespath	`1.0.1`	indirect
PyPI	jsonschema	`4.26.0`	indirect
PyPI	jsonschema-specifications	`2025.9.1`	indirect
PyPI	markupsafe	`3.0.3`	indirect
PyPI	mcp	`1.26.0`	indirect
PyPI	methoddispatch	`3.0.2`	indirect
PyPI	msgpack	`1.1.0`	indirect
PyPI	multidict	`6.0.5`	indirect
PyPI	openai	`1.109.1`	indirect
PyPI	opentelemetry-exporter-otlp-proto-common	`1.26.0`	indirect
PyPI	opentelemetry-processor-baggage	`0.61b0`	indirect
PyPI	opentelemetry-proto	`1.26.0`	indirect
PyPI	opentelemetry-semantic-conventions	`0.47b0`	indirect
PyPI	packaging	`24.0`	indirect
PyPI	pluggy	`1.5.0`	indirect
PyPI	propcache	`0.2.0`	indirect
PyPI	protobuf	`4.25.8`	indirect
PyPI	pyasn1	`0.6.1`	indirect
PyPI	pyasn1-modules	`0.4.1`	indirect
PyPI	pycparser	`3.0`	indirect
PyPI	pydantic	`2.11.7`	indirect
PyPI	pydantic-core	`2.33.2`	indirect
PyPI	pydantic-settings	`2.10.1`	indirect
PyPI	pyee	`11.1.1`	indirect
PyPI	pyjwt	`2.12.1`	indirect
PyPI	pytest	`8.2.0`	indirect
PyPI	pytest-asyncio	`0.23.6`	indirect
PyPI	pytest-network	`0.0.1`	indirect
PyPI	pytest-parametrize-cases	`0.1.2`	indirect
PyPI	python-dateutil	`2.9.0.post0`	indirect
PyPI	python-dotenv	`1.1.1`	indirect
PyPI	python-multipart	`0.0.22`	indirect
PyPI	pywin32	`311`	indirect
PyPI	pyyaml	`6.0.2`	indirect
PyPI	referencing	`0.37.0`	indirect
PyPI	rpds-py	`0.30.0`	indirect
PyPI	rsa	`4.9`	indirect
PyPI	s3transfer	`0.11.3`	indirect
PyPI	six	`1.16.0`	indirect
PyPI	sniffio	`1.3.1`	indirect
PyPI	sse-starlette	`3.3.2`	indirect
PyPI	starlette	`0.52.1`	indirect
PyPI	tomli	`2.0.1`	indirect
PyPI	tqdm	`4.66.4`	indirect
PyPI	types-requests	`2.31.0.6`	indirect
PyPI	types-urllib3	`1.26.25.14`	indirect
PyPI	typing-extensions	`4.14.0`	indirect
PyPI	typing-inspection	`0.4.1`	indirect
PyPI	urllib3	`1.26.20`	indirect
PyPI	uvicorn	`0.42.0`	indirect
PyPI	vcrpy	`6.0.2`	indirect
PyPI	websockets	`15.0.1`	indirect
PyPI	wrapt	`1.16.0`	indirect
PyPI	yarl	`1.15.2`	indirect
PyPI	zipp	`3.19.2`	indirect

Dependency advisories 0

Installing pypi:promptlayer@1.5.16 pulls in 43 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.

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.

Software health index

Score profile

Ownership

Package ecosystems

Metrics by category

Key facts

Data collection warnings

More detail

Feedback

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