mlc-ai/mlc-llm
What happens to a stranger's pull request here, in the Porchlamp snapshot of 17 October 2026.
For mlc-ai/mlc-llm, the reply time has too small a sample to measure (0 pull requests counted; 10 needed). 61% of 41 outside pull requests got no reply within 14 days (20 April to 17 October 2026). It ranks 2,206 of 3,219 overall. For first-time contributors it ranks 1,219 of 1,525 (the bottom 21%).
| Rank | 2,206 of 3,219 |
|---|---|
| Score | 45.24 |
| Tier | C |
| Median first reply | — |
| 14-day no-reply share | 61% |
| First-timer rank | 1,219 of 1,525 |
| Ecosystem | Python |
| Window | 20 April to 17 October 2026 |
Composite
- Rank
- 2,206 of 3,219
- Score
- 45.24
- Tier
- C
- Coverage
- 70% · Ceiling B
- Quadrant
- Nursery
Coordinates: leverage 40.2 (coverage 68%), friction 49.5 (coverage 73%)
Five pillars
| Pillar | Score | Coverage |
|---|---|---|
| Responsiveness | 42.5 | 45% |
| Criticality | 37.4 | 35% |
| Governance | 59.3 | 100% |
| Rigor | 32.0 | 100% |
| Accessibility | 57.5 | 100% |
The measured parameters
Responsiveness
| Parameter | Value | Score | Count | Window | Source |
|---|---|---|---|---|---|
| Decision Rate (90d)Share of outside pull requests that were merged or closed within 90 days. | Not shown: Insufficient sample size | ||||
| PR Ghost Rate (14d)Share of outside pull requests with no maintainer response, merge or close within 14 days. | 61.0% | 0.0 | 41 | 20 April to 17 October 2026 | primaryraw/pr_window/mlc-ai__mlc-llm.json |
| First-timer Merge RateShare of first-time outside authors' decided pull requests that were merged. | 50.0% | 62.5 | 16 | — | primaryraw/author_history/mlc-ai__mlc-llm.json |
| Time to First ResponseMedian hours from an outside pull request opening to its first substantive human reply. | Not shown: Insufficient sample size | ||||
| Time to Merge (p90)Hours within which 90% of merged outside pull requests were merged. | 192.7 hours (8 days) | 66.1 | 17 | 18 April to 15 October 2026 | primaryraw/pr_window/mlc-ai__mlc-llm.json |
Criticality
| Parameter | Value | Score | Count | Window | Source |
|---|---|---|---|---|---|
| DependentsPackages in the registry that depend on this project, counted once each. | Not shown: Third-party data unavailable | ||||
| Monthly DownloadsDownloads from the package registry in a month. | Not shown: Third-party data unavailable | ||||
| OpenSSF CriticalityOpenSSF criticality score from 0 to 1, computed from the project's public activity signals. | 0.3741 | 37.4 | — | — | proxy:no_dependents_signalraw/github_meta/mlc-ai__mlc-llm.json |
Governance
| Parameter | Value | Score | Count | Window | Source |
|---|---|---|---|---|---|
| Elephant FactorThe fewest organisations that account for half of the last year's commits. | 2 | 50.0 | 99 | — | primaryraw/commits_365d/mlc-ai__mlc-llm.json |
| Legal IP RegimeThe contributor licence regime: DCO, none, a foundation CLA or a corporate CLA. | No CLA or sign-off found | 85.0 | — | — | primaryraw/governance/mlc-ai__mlc-llm.json |
| Promotion LadderHow openly a contributor can become a maintainer, from closed to verified. | No written path to becoming a maintainer | 40.0 | — | — | primaryraw/governance/mlc-ai__mlc-llm.json |
Rigor
| Parameter | Value | Score | Count | Window | Source |
|---|---|---|---|---|---|
| AI Policy PostureWhether the project has a written policy on AI-assisted contributions. | No written AI policy | 40.0 | — | — | primaryraw/governance/mlc-ai__mlc-llm.json |
| Pipeline DefensesHow well the project's build and review pipeline defends against bad changes, 0 to 100. | 50 | 50.0 | 24 | — | proxy:review_ciraw/pr_window/mlc-ai__mlc-llm.json |
| Substantive Review RateShare of decided pull requests that received a substantive review. | 0.0% | 0.0 | 24 | 18 April to 15 October 2026 | primaryraw/pr_window/mlc-ai__mlc-llm.json |
Accessibility
| Parameter | Value | Score | Count | Window | Source |
|---|---|---|---|---|---|
| Developer ExperienceDeveloper experience, 0 to 100: half CI run time, half setup signals. | 50 | 50.0 | 30 | — | primaryraw/actions_runs/mlc-ai__mlc-llm.json |
| Newcomer ConversionShare of first-time authors whose first pull request merged within 180 days. | 62.5% | 100.0 | 16 | — | primaryraw/author_history/mlc-ai__mlc-llm.json |
| Newcomer Issue SupplyOpen, unassigned, up-to-date issues marked for newcomers. | 0 | 0.0 | — | — | primaryraw/gfi/mlc-ai__mlc-llm.json |
| Newcomer Return RateShare of those merged first-time authors who sent a second pull request within 90 days. | 50.0% | 100.0 | 10 | — | primaryraw/author_history/mlc-ai__mlc-llm.json |
Persona view
| Persona | Rank | Score | Tier | Status |
|---|---|---|---|---|
| Balanced | 2,206 of 3,219 | 45.24 | C | Rated |
| First-timer | 1,219 of 1,525 | 47.94 | C | Rated |
| Career capital | This repository's production-criticality signal is not yet high enough for career-capital ranking. | |||
| Senior systems | Fewer than 3 organizations account for most commits (not multi-vendor). | |||
| AI-assisted | 2,920 of 3,696 | 41.81 | C | Rated |
Integrity
- Snapshot
- 2026-10-17
- Raw hash
- d18ab0aae98edff34b965adddf83353b16703f20df9d17603eb665553b49d7bb
No suspicion flags on this repository.
The full record is in data/2026-10-17/repos/f6.json, under the key mlc-ai/mlc-llm.
How every number is measured: Porchlamp methodology.
Open an issue about this record and say what looks wrong.
Porchlamp (2026). mlc-ai/mlc-llm. Snapshot 2026-10-17. https://porchlamp.org/projects/mlc-ai/mlc-llm/. CC BY 4.0.
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