Leaderboard github.com
jlcases/mamerto
Give Claude Code a voice. Stop hook that synthesizes every response into a human summary and speaks it via ElevenLabs TTS. Zero dependencies.
unreviewed-ai-risk
AI provenance
100%
explicit
- Confidence
- 70%
- Coverage
- 100%
Estimated share of AI-generated code. Explicit attribution is a lower bound.
Code quality
32/100
poor
- Confidence
- 90%
- Coverage
- 100%
Complexity, duplication, lint density, tests, CI, docs and review process.
Security
79/100
adequate
- Confidence
- 85%
- Coverage
- 100%
Secrets, static analysis, vulnerable dependencies, CI and supply-chain posture.
AI provenance
100% explicit
Explicit AI attribution on 100% of first-party code added; an estimated 100% including velocity signals.
How the score is built
- Explicitly attributed share100%
- Unattributed share in AI-pace bursts0%
- Estimated AI-generated share100%
- AI tool configuration files0
- Work sessions at AI pace0
- Releases at AI pacenot measured
- Coding-style index (1.0+ means possible)0.00
Attributed AI tools
| Tool | Commits | Lines added | First seen | Last seen |
|---|---|---|---|---|
| Claude Code | 1 | 314 | 2026-04-25 | 2026-04-25 |
Lines added per month all AI-attributed share
- 2026-04314 · 100% AI
Findings in AI-attributed lines vs the rest
From git blame: 314 lines trace to AI-attributed commits, 0 to others. Too few lines in one group for a fair comparison. Reported, not scored.
| Findings per 1,000 lines | AI-attributed | Other | Ratio |
|---|---|---|---|
| Code quality | 6.37 | — | — |
| Security | 3.19 | — | — |
Evidence by analyzer
Explicit AI attributionok2 items
- Claude Code: 1 attributed commits, 314 lines added
- Claude Code: committer Claude
- attributed_commit_share
- 100.0%
- attributed_commits
- 1
- attributed_loc
- 314
- attributed_loc_share
- 100.0%
- commits
- 1
- effective_loc
- 314
- tools_detected
- 1
AI tool configurationok
- artifacts
- 0
- tools_configured
- 0
- workflow_agents
- 0
Commit velocityok
- excluded_import_loc
- 0
- flagged_loc
- 0
- flagged_loc_share
- 0.0%
- flagged_units
- 0
- max_loc_per_hour
- 78.50
- measured_loc
- 314
- median_loc_per_hour
- 78.50
- pr_timed_units
- 0
- pre_ai_era_burst_loc
- 0
- pre_ai_era_bursts
- 0
- pre_ai_era_measured_loc
- 0
- work_units
- 1
Release velocityskipped
Coding styleok
- count:assistant_voice
- 0
- count:emoji_in_code
- 0
- count:narrated_steps
- 0
- count:placeholder
- 0
- files:assistant_voice
- 0
- files:emoji_in_code
- 0
- files:narrated_steps
- 0
- files:placeholder
- 0
- index
- 0
- lines_scanned
- 314
- per_kloc:assistant_voice
- 0
- per_kloc:emoji_in_code
- 0
- per_kloc:narrated_steps
- 0
- per_kloc:placeholder
- 0
Findings in AI-written linesok
- ai_lines
- 314
- blame_failures
- 0
- files_blamed
- 1
- other_lines
- 0
- quality:ai_findings
- 2
- quality:ai_per_kloc
- 6.37
- quality:other_findings
- 0
- security:ai_findings
- 1
- security:ai_per_kloc
- 3.19
- security:other_findings
- 0
Code quality
32 poor
Code quality is poor: test-to-source ratio 0.00, no CI test run detected; 48% of function code in complex or long functions; 0% duplicated lines. Weakest area: testing.
How the score is built
- Complexity24
- Duplication100
- Lint and smells22
- Tests and CI0
- Documentation40
- Type safety40
- Review processnot measured
Evidence by analyzer
Complexity (lizard)ok2 items
- _scan_reply_to_last_user in narrator.py: complexity 20, 39 lines
- main in narrator.py: complexity 16, 76 lines
- complex_functions
- 2
- function_nloc
- 238
- functions
- 9
- long_functions
- 0
- many_param_functions
- 0
- mean_ccn
- 8.44
- p90_ccn
- 20
- risky_nloc_share
- 48.3%
Duplication (jscpd)ok
- compared_lines
- 253
- duplicated_lines
- 0
- duplicated_share
- 0.0%
- files
- 1
Lintok
- category:best-practice
- 1
- category:correctness
- 1
- findings
- 2
- scanned_lines
- 314
- weighted_findings
- 6
Tests and CIok
- check:ci_present
- no
- check:ci_runs_lint
- no
- check:ci_runs_tests
- no
- check:has_tests
- no
- check:test_ratio
- no
- check:tests_cochange
- no
- ci_files
- 0
- cochange_commits
- 1
- cochange_share
- 0.0%
- source_lines
- 314
- test_lines
- 0
- test_ratio
- 0
Documentationok1 item
- README.md
README.md
- check:changelog
- no
- check:contributing
- no
- check:license
- no
- check:readme
- yes
- readme_lines
- 132
Type safetyok
- check:low_escape_density
- yes
- check:strict_config
- no
- escapes
- 0
- escapes_per_kloc
- 0
Security
79 adequate
Security posture is adequate: no high-impact findings. Weakest area: posture.
How the score is built
- Secrets100
- Static analysis (SAST)92
- Vulnerable dependenciesnot measured
- CI workflowsnot measured
- Security posture0
- OpenSSF Scorecardnot measured
Evidence by analyzer
OpenSSF Scorecardskipped
no published OpenSSF Scorecard result for this repo
Package registriesskipped
no registry dependencies declared
Secrets (gitleaks)ok
- secrets_current
- 0
- secrets_history
- 0
- secrets_low_confidence
- 0
- secrets_nonprod
- 0
Static analysis (opengrep)ok
- findings
- 1
- findings_high
- 0
- findings_low
- 0
- findings_medium
- 1
- parse_errors
- 0
- scanned_lines
- 314
- weighted_findings
- 0.25
Dependencies (osv-scanner)skipped
CI workflows (zizmor)skipped
Security postureok
- check:dependency_updates
- no
- check:lockfiles
- yes
- check:security_policy
- no
- check:signed_commits
- no
- signed_commit_share
- 0.0%
- unpinned_manifests
- 0
Release downloadsok
- binary_assets
- 0
- signals
- 0
- suspicious
- 0
Findings
2 high1 medium
| Severity | Rule | Location | Message | Tool |
|---|---|---|---|---|
| high | opengrep/python.lang.best-practice.arbitrary-sleep |
narrator.py:150 | time.sleep() call; did you mean to leave this in? | Lint |
| high | opengrep/python.lang.correctness.tempfile.tempfile-without-flush |
narrator.py:292 | Using 'f.name' without '.flush()' or '.close()' may cause an error because the file may not exist when 'f.name' is used. Use '.flush()' or close the file before using 'f.name'. | Lint |
| medium | opengrep/python.lang.security.audit.dynamic-urllib-use-detected |
narrator.py:218 | Detected a dynamic value being used with urllib. urllib supports 'file://' schemes, so a dynamic value controlled by a malicious actor may allow them to read arbitrary files. Audit uses of urllib calls to ensure user data cannot control... | Static analysis (opengrep) |
Tools and coverage
Every analyzer that ran on this commit. A failed or skipped tool is a coverage gap: its share of the score is left out and the coverage figure drops.
| Analyzer | Pillar | Status | Version | Findings | Note |
|---|---|---|---|---|---|
| AI tool configuration | AI provenance | ok | signatures-v1 | 0 | |
| Explicit AI attribution | AI provenance | ok | signatures-v1 | 0 | |
| Release velocity | AI provenance | skipped | — | 0 | |
| Coding style | AI provenance | ok | — | 0 | |
| Commit velocity | AI provenance | ok | prov-4 | 0 | |
| Findings in AI-written lines | AI provenance | ok | git-blame | 0 | |
| Complexity (lizard) | Code quality | ok | lizard 1.25.1 | 0 | |
| Documentation | Code quality | ok | — | 0 | |
| Duplication (jscpd) | Code quality | ok | repotrust-dup-w6 | 0 | |
| Lint | Code quality | ok | opengrep 1.33.1; rules f1d2b562b414 | 2 | |
| Tests and CI | Code quality | ok | — | 0 | |
| Type safety | Code quality | ok | — | 0 | |
| CI workflows (zizmor) | Security | skipped | — | 0 | |
| Dependencies (osv-scanner) | Security | skipped | — | 0 | |
| Release downloads | Security | ok | — | 0 | |
| Security posture | Security | ok | — | 0 | |
| Package registries | Security | skipped | — | 0 | no registry dependencies declared |
| Static analysis (opengrep) | Security | ok | opengrep 1.33.1; rules f1d2b562b414 | 1 | |
| OpenSSF Scorecard | Security | skipped | — | 0 | no published OpenSSF Scorecard result for this repo |
| Secrets (gitleaks) | Security | ok | gitleaks 8.30.1 | 0 |
Score history
Scores from different scoring versions aren't directly comparable.
| Scored | Commit | Scoring | AI provenance | Quality | Security |
|---|---|---|---|---|---|
| 2026-11-14 | 9b47fca78cf8 | prov-5+qual-2+sec-2 | 100% | 32 | 79 |
| 2026-11-14 | 9b47fca78cf8 | prov-4+qual-2+sec-2 | 100% | 32 | 79 |
Full text report
- Repository: https://github.com/jlcases/mamerto
- Commit:
9b47fca78cf85a37f8bc88f4f7ec0881bad0db7b - Generated: 2026-11-14T14:52:05+00:00
- Scorer 0.1.0, scoring prov-5+qual-2+sec-2, report schema v2
Scores
Unreviewed AI code risk: a large share of this code is explicitly AI-attributed, and its tests or review process are weak while quality or security scores are low.
| Pillar | Score | Signal | Confidence | Coverage |
|---|---|---|---|---|
| AI provenance (estimated AI-generated share) | 100 | explicit | 70% | 100% |
| Code quality | 32 | poor | 90% | 100% |
| Security | 79 | adequate | 85% | 100% |
AI provenance
Explicit AI attribution on 100% of first-party code added; an estimated 100% including velocity signals.
- Explicitly attributed share (lower bound): 100.0%
- Unattributed share in AI-consistent velocity bursts: 0.0%
- Estimated AI-generated share: 100.0%
| AI tool | Attributed commits | Lines added |
|---|---|---|
| Claude Code | 1 | 314 |
Current source lines last changed by AI-attributed commits: 314 of 314.
Too few lines in one group to compare finding densities.
| Month | Lines added | Attributed to AI |
|---|---|---|
| 2026-04 | 314 | 100% |
Evidence
- Claude Code: committer Claude (9b47fca78cf8)
AI provenance describes how code was produced; it is not a quality judgment. Unless attribution is explicit, these are signals consistent with AI generation, not proof. Squash/rebase workflows, imported code, and rewritten history reduce accuracy.
Code quality
Code quality is poor: test-to-source ratio 0.00, no CI test run detected; 48% of function code in complex or long functions; 0% duplicated lines. Weakest area: testing.
| Area | Score |
|---|---|
| Complexity (lizard) | 24 |
| Duplication | 100 |
| Code smells (Opengrep) | 22 |
| Tests and CI | 0 |
| Documentation | 40 |
| Type safety | 40 |
| Process (Scorecard review/maintenance) | n/a |
- Functions: 9; mean complexity 8.4, 90th percentile 20; 2 complex and 0 long functions
- Duplicated lines: 0.0% of 253 compared
- Tests: 0 test lines for 314 source lines (ratio 0.00); CI test commands: none detected; 0% of recent source commits also change tests
- Docs missing or thin: license, contributing, changelog
Most complex functions:
- _scan_reply_to_last_user in narrator.py: complexity 20, 39 lines
- main in narrator.py: complexity 16, 76 lines
Security
Security posture is adequate: no high-impact findings. Weakest area: posture.
| Area | Score |
|---|---|
| Secrets (gitleaks, tree + history) | 100 |
| Static analysis (Opengrep) | 92 |
| Vulnerable dependencies (OSV) | n/a |
| CI workflows (zizmor) | n/a |
| Posture (policy, updates, signing, lockfiles) | 0 |
| OpenSSF Scorecard | n/a |
- Posture checks passed: lockfiles; missing: security policy, dependency updates, signed commits
Top findings
| Severity | Finding | Location |
|---|---|---|
| medium | opengrep/python.lang.security.audit.dynamic-urllib-use-detected: Detected a dynamic value being used with urllib. urllib supports 'file://' schemes, so a dynamic value controlled by a malicious actor may allow them to read arbitrary files. Audit uses of urllib calls to ensure user data cannot control the URLs, or consider using the 'requests' library instead. [confidence low] |
narrator.py:218 |
Static signals only: the scorer never runs the project's code. Secret findings are pattern matches that were not verified, and secret values are never stored.
Repository profile
- Source lines: 314; test lines: 0
| Language | Lines |
|---|---|
| Python | 314 |