FailproofAI/failproofai - Open Source PR Review Scorecard

Observability and enforcement for AI agent harnesses. Capture every run and runtime reliability with policy enforcement.

C-Rank Grade: A (Welcoming) - 67/100

External PR Merge Rate: 68%

Response Time: -

First Timer Success: 42%

Frequently Asked Questions

Is FailproofAI/failproofai welcoming to first-time open-source contributors?

FailproofAI/failproofai has a recorded first-timer success rate of 41.7%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.

How fast can I expect code review feedback on my pull request?

Maintainers in FailproofAI/failproofai respond to incoming external pull requests in approximately 0.0 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 66.5 C-Rank™ score (A Tier) represent?

The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 66.5 places FailproofAI/failproofai in the A tier.

What is the external contributor pull request merge rate for FailproofAI/failproofai?

The external contributor pull request merge rate for FailproofAI/failproofai is 68.2%, based on public PR activity from non-core contributors.

Are there Good First Issues available in FailproofAI/failproofai?

FailproofAI/failproofai currently has 7 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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FailproofAI/failproofai

5,273
InactiveA•Welcoming(67/100)TypeScript

Observability and enforcement for AI agent harnesses. Capture every run and runtime reliability with policy enforcement.

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AI Maintainer Review Guidelines

Review Persona

Empathetic Technical Mentor

Warmth Score
7.5/10
Patience Score
8.2/10
Nitpick Rate
20%

Collaborative maintainer environment in FailproofAI/failproofai. Reviews community pull requests with focus on project quality.

Top PR Submission Do's

  • •Ensure code complies with the project coding style
  • •Keep PRs scoped to a single concern
  • •Include context and link to the related issue

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit PRs without linking an issue
  • •Do not break existing tests without fixing them
  • •Do not mix unrelated refactors in a single PR
Response Velocity
-
No reviewer activity recorded

Average Response Latency

Tracks hours until a maintainer leaves a review, comment, or PR response.

Merge Efficiency
68.2%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
41.7%
Accepts new contributor PRs

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
8 core
Highly collaborative maintainer core
Diagnostic Health HUD
68.2%
Merge Gauge
41.7%
1st-Timer
Community Vibe40/100

Embed C-Rank Badge

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GetMerged C-Rank badge for FailproofAI/failproofai
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Active Good First Issues (5)

View on GitHub

CHANGELOG.md currently contains 76 entries ending in a literal (#PR) instead of a pull-request number: grep -c '(#PR)' CHANGELOG.md # 76 The very first entry in the file — ## 1.0.1-beta.0 — 2026-08-12 — is one of them, so it's the first thing anyone reading the changelog sees. CONTRIBUTING.md asks every entry to end with its PR number (e.g. (#123)). (#PR) is the placeholder people write before the PR exists, and it's being forgotten on the way out. Two parts, both beginner-friendly 1. Backfill the numbers. For each (#PR), find the PR that introduced the entry and substitute the number. git log -S'<a distinctive phrase from the entry>' -- CHANGELOG.md will point you at the commit, and the merge commit or gh pr list --search gets you the number. Where an entry genuinely never had a PR, drop the (#PR) rather than inventing one. This is mechanical but not blind — take it in batches and note anything ambiguous in the PR description rather than guessing. 2. Add a CI guard so it can't

📅 Opened Aug 13, 2026💬 1 comment
Quality: 90/100Contribute

COPILOT_TOOL_MAP in src/hooks/types.ts canonicalises GitHub Copilot's tool names so that policies written against canonical names (Bash, Read, Task, …) fire on Copilot sessions. Two documented Copilot tools are missing from it: task and web_search. Why it matters Unmapped tool names pass through uncanonicalised. So a policy matching toolName === "Task" silently never fires on Copilot — no warning, no error, it simply doesn't run. For a guardrail tool that's the worst failure mode: the user believes they're protected and they aren't. Where to fix Add to COPILOT_TOOL_MAP in src/hooks/types.ts: task: "Task", web_search: "WebSearch", The existing web_fetch: "WebFetch" entry sits right there as a model to follow. One small judgement call Copilot also documents an ask_user tool. It has no filesystem or shell reach, so it's arguably benign and needs no entry at all. We genuinely haven't decided — form a view and say which way you went in the PR description. Either answer is fine if it's

📅 Opened Aug 13, 2026💬 0 comments
Quality: 80/100Contribute

writeCacheEntry() in lib/codex-sessions.ts does a read-modify-write with no atomic rename: function writeCacheEntry(sessionId: string, path: string): void { try { mkdirSync(dirname(CACHE_PATH), { recursive: true }); const cache = readCache(); cache[sessionId] = path; writeFileSync(CACHE_PATH, JSON.stringify(cache), "utf-8"); // not atomic } catch { // Cache is best-effort } } The dashboard fans out Codex session lookups in parallel on the projects page, so these writes can interleave. Why it matters A lost entry isn't the problem — that's just a cache miss, and the next lookup rescans and repopulates it. The problem is a torn file. If a write is interrupted partway, readCache() hits invalid JSON, throws, and the entire cache map is lost — not one entry. That turns a harmless race into a full cache wipe. Where to fix lib/codex-sessions.ts: Write to a process-unique temp path — ${CACHE_PATH}.${process.pid}.tmp renameSync() it into place (atomic on the s

📅 Opened Aug 13, 2026💬 0 comments
Quality: 80/100Contribute

failproofai policies prints ANSI colour even when NO_COLOR=1 is set, and there is no --no-color flag at all. Most of the CLI already gets this right — install-prompt.ts, audit/report.ts and audit/cli.ts all honour it. src/hooks/manager.ts is the holdout, and it happens to be the output people most often pipe into CI logs. Reproduce Under a real TTY (piping hides it, because a non-TTY disables colour anyway): script -qec "failproofai policies" /dev/null | grep -aoP '\x1B\[' | wc -l # 32 script -qec "env NO_COLOR=1 failproofai policies" /dev/null | grep -aoP '\x1B\[' | wc -l # 32 ← should be 0 The green ✓ marks come out as ESC[32m✓ESC[0m regardless. Where to fix src/hooks/manager.ts hardcodes ANSI escapes at 16 sites. Route them through paint() from src/hooks/tui.ts, which already gates on NO_COLOR through colorsEnabled(). src/hooks/install-prompt.ts:261 is a worked example of the pattern: const { dim, bold, guide: teal, pink, pinkBold } = paint(!process.env.NO_COLOR); Then ad

📅 Opened Aug 13, 2026💬 0 comments
Quality: 80/100Contribute

Description In the Hook Logs table (app/components/session-hooks-panel.tsx:329), a row is expanded only via <tr onClick={() => toggleRow(i)}> with cursor-pointer. The row has no tabIndex, no role="button", and no onKeyDown, and the disclosure indicator is a bare <ChevronDown> icon (:342), not a button. Interaction is mouse-only. Steps to Reproduce Open a session's Hook Logs panel in the dashboard. Using only the keyboard (Tab / Enter / Space), try to expand a row to see its details (Session ID, CWD, full reason, matched policies). There is no focusable control — the detail panel is unreachable without a mouse. Screen-reader users get no affordance that the row is interactive. Expected Behavior Row expansion should be operable by keyboard and announced to assistive tech — e.g. Tab to focus, Enter/Space to toggle, with aria-expanded reflecting state. Failproof AI Version 0.0.14-beta.1 Node.js / Bun Version Bun 1.3+ Operating System macOS Additional Context Approachable a11y starter

📅 Opened Jul 16, 2026💬 1 comment
Quality: 80/100Contribute
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Contributor Compatibility & Review Speed Analysis for FailproofAI/failproofai

When evaluating whether to contribute to FailproofAI/failproofai, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.

Currently, maintainers of FailproofAI/failproofai acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 68.2% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to FailproofAI/failproofai

01

Is FailproofAI/failproofai welcoming to first-time open-source contributors?

FailproofAI/failproofai has a recorded first-timer success rate of 41.7%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.

02

How fast can I expect code review feedback on my pull request?

The initial maintainer response time averages ~-. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 66.5 C-Rank™ score represent?

The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 66.5 places FailproofAI/failproofai in the Welcoming tier.

04

What is the external contributor pull request merge rate for FailproofAI/failproofai?

The external pull request merge rate is 68.2%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.

05

Are there beginner Good First Issues open in FailproofAI/failproofai?

Yes, FailproofAI/failproofai currently has 7 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for FailproofAI/failproofai are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.