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ravsau/awesome-ai-cost-optimization

https://github.com/ravsau/awesome-ai-cost-optimization · scanned 2026-06-15 23:47 UTC (2 months, 3 weeks ago)

15 raw signals (11 security + 4 graph)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 months, 3 weeks ago · v1 · 12 actionable findings from 2 signal sources. 13 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

JSON
Combined
94.5
/100
Security checks
95
8 findings
System graph
95
77.8% cov · 4 findings
Critical
2
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Agents
10
0 votes
Crowd
0
reported
Severity distribution — click a segment to filter
Active filters: excluding tests × Reset all
Severity: Critical 2 High 3 Medium 5 Low 1 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 8 System graph 4 Crowd 0 Layer: Quality 8 Security 2 Frontend 1 Cicd 1
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Scan summary Repository scanned at 94.5/100 with 77.8% coverage. It contains 23 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 4 findings — concentrated in frontend (1), security (1), cicd (1). Risk profile is low: 0 critical, 0 high, 2 medium. Recommended next step: open the frontend layer findings first — that's where the highest-impact wins live.

Showing 11 of 12 actionable findings. 25 raw detector signals were grouped into reader-sized issues. Click TP / FP to vote on a finding's accuracy — votes adjust the confidence weighting and improve detection across the platform.

critical Security checks quality Practices conf 0.82 2 occurrences Foundry mined mock as real or placeholder: ravsau/awesome-ai-cost-optimization
Graph query export: Mock, sample, placeholder, or self-attested behavior treated as real Query id: mock_as_real_or_placeholder Query type: motif_query Intent: Hard negatives for fake completeness and missing real data paths. Motif: mock_as_real_or_placeholder Training usage: hard_negative Graph gol…
2 occurrences
repo-level (2 hits)
critical Security checks security auth conf 0.78 Foundry mined security auth guardrail gaps: ravsau/awesome-ai-cost-optimization
Graph query export: Security/auth changes without enough guardrails Query id: security_auth_guardrail_gaps Query type: motif_query Intent: Assumption-check security/auth examples requiring stronger tests or CI. Motif: security_auth_without_guardrails Training usage: assumption_check Graph gold labe…
high Security checks quality Practices conf 0.84 3 occurrences Foundry mined bad chains: ravsau/awesome-ai-cost-optimization
Comment chain pattern product: bad_chains Repo: ravsau/awesome-ai-cost-optimization Thread: ravsau/awesome-ai-cost-optimization#7 Outcome: not_resolved_or_not_observed Thread label: thread_has_human_issue_without_fix_context Source graph label: source_artifact_without_verification_graph Reasons: so…
3 occurrences
repo-level (3 hits)
high Security checks quality Practices conf 0.80 3 occurrences Foundry mined docs only runtime fix: ravsau/awesome-ai-cost-optimization
Graph query export: Docs-only response to runtime or integration issue Query id: docs_only_runtime_fix Query type: motif_query Intent: Assumption-check examples where docs or claims are not enough proof. Motif: docs_only_runtime_fix Training usage: assumption_check Graph gold label: weak_supervisio…
3 occurrences
repo-level (3 hits)
high Security checks quality Testing conf 0.78 Foundry mined test ci gap after feedback: ravsau/awesome-ai-cost-optimization
Graph query export: Feedback exposes missing tests or CI Query id: test_ci_gap_after_feedback Query type: motif_query Intent: Hard negatives for feedback/fix chains without adequate guardrails. Motif: test_ci_gap_after_feedback Training usage: hard_negative Graph gold label: weak_supervision_needs_…
medium Security checks quality Practices conf 0.62 6 occurrences Foundry mined assumption checks: ravsau/awesome-ai-cost-optimization
Comment chain pattern product: assumption_checks Repo: ravsau/awesome-ai-cost-optimization Thread: ravsau/awesome-ai-cost-optimization#9 Outcome: ambiguous_needs_more_evidence Thread label: thread_has_human_issue_and_fix_context Source graph label: source_artifact_without_verification_graph Reasons…
6 occurrences
repo-level (6 hits)
medium Security checks quality maintenance conf 0.70 4 occurrences Foundry mined blueprint gap alignment: ravsau/awesome-ai-cost-optimization
Graph query export: Human feedback aligned with blueprint or architecture gaps Query id: blueprint_gap_alignment Query type: motif_query Intent: Curriculum-gap examples connecting issue threads to helicopter-view gaps. Motif: blueprint_gap_alignment Training usage: curriculum_gap Graph gold label: …
4 occurrences
repo-level (4 hits)
medium Security checks quality Practices conf 0.70 Foundry mined unresolved feedback: ravsau/awesome-ai-cost-optimization
Graph query export: Human feedback without linked fix evidence Query id: unresolved_feedback Query type: motif_query Intent: Negative/unresolved examples that should not be hallucinated into fixes. Motif: unlinked_feedback_needs_evidence Training usage: negative_or_unresolved Graph gold label: need…
medium System graph security Coverage conf 1.00 No auth library detected
The scanner did not find any standard auth library (JWT, OAuth, NextAuth, Auth0, etc.). The repo has auth/admin/session surface indicators, so auth may live in custom code, in a separate service, or be missing.
auth
medium System graph cicd CI/CD security conf 1.00 No CI/CD pipelines detected
No GitHub Actions, GitLab CI, or CircleCI configs found. Without CI you can't gate deploys on tests/lints.
CI/CD securityCoverage
low System graph quality Provenance conf 1.00 Shallow git history limits provenance confidence
The repository is a shallow clone. Origin/evolution analysis cannot distinguish fresh generation, imported legacy code, or long-lived human code with high confidence.
Git historyGenerated repo pattern
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