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trevorotts1/openclaw-onboarding

https://github.com/trevorotts1/openclaw-onboarding · scanned 2026-06-16 00:42 UTC (2 months, 1 week ago)

164 raw signals (0 security + 164 graph)

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Complete repo analysis

Last scanned 2 months, 1 week ago · v1 · 127 actionable findings from 1 signal source. 37 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

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88.9% cov · 127 findings

Severity distribution — click a segment to filter

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Severity: Critical 3 High 5 Medium 34 Low 54 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 127 Crowd 0 Layer: Software 23 Frontend 4 Network 4 Security 12 Cicd 2 Quality 82

Exclude dismissed / FP Exclude test files

Bug-class explainers. Each card groups findings of the same shape — these are the patterns most likely to ship to prod and reappear in future scans unless you systematically fix the cause, not just the instance.

Duplicates & near-duplicates 2 findings

What it is: Same function copy-pasted into multiple modules with minor variations.

Why it matters: Each copy drifts independently — bug fixes apply to one, miss the others.

How AI causes it: AI completes the same pattern in each file rather than refactoring to a shared helper.

Fix approach: Extract the duplicated logic into the most general module both call sites already import. Add tests at the helper level.

2 matching findings on this repo

low Near-duplicate function bodies in 2 places repo-level
low Near-duplicate function bodies in 3 places repo-level

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Legacy markers 6 findings

What it is: TODO, FIXME, XXX, HACK comments. Often indicate a known-broken path the author meant to fix.

Why it matters: Each marker is an unfinished thought. Production code shouldn't ship with debt that's documented but not tracked.

How AI causes it: AI mirrors the style of the codebase, so existing TODOs propagate into new code.

Fix approach: Convert each into a ticket. Delete the comment when the ticket lands. Use a pre-commit hook to block new TODOs without an issue link.

6 matching findings on this repo

low Old/deprecated-named symbol `would_copy` in 23-ai-workforce-blueprint/scripts/r…
low Old/deprecated-named symbol `canonical_legacy` in 23-ai-workforce-blueprint/scr…
low Old/deprecated-named symbol `mac_legacy` in 23-ai-workforce-blueprint/lib/detec…
low Old/deprecated-named symbol `mac_legacy` in shared-utils/detect_platform.py:56
low Old/deprecated-named symbol `sorted_legacy` in shared-utils/migrate_zhc_runner.…
low Old/deprecated-named symbol `mac_legacy` in shared-utils/resolve_injected_core_…

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Commented-out code 29 findings

What it is: Lines of source that were intentionally disabled but never deleted.

Why it matters: Git already remembers history — commented code rots, becomes wrong, and adds noise to diffs.

How AI causes it: AI sometimes comments out broken code instead of fixing it. Reviewers approve out of inertia.

Fix approach: Delete. Trust `git log`. If you really need to remember, save it in a notes file under `docs/`.

12 matching findings on this repo

info Commented-code block (5 lines) in tests/unit/deep-health.test.ts:64
info Commented-code block (6 lines) in scripts/check-floor-count-drift.py:114
info Commented-code block (5 lines) in scripts/generate-trio-roles.py:841
info Commented-code block (6 lines) in 38-conversational-ai-system/_wire_rules_15_16…
info Commented-code block (5 lines) in 38-conversational-ai-system/templates/zhc-pix…
info Commented-code block (7 lines) in 23-ai-workforce-blueprint/scripts/persona-sel…
info Commented-code block (5 lines) in 23-ai-workforce-blueprint/scripts/populate-so…
info Commented-code block (5 lines) in 23-ai-workforce-blueprint/scripts/department-…
info Commented-code block (6 lines) in 23-ai-workforce-blueprint/scripts/_qc_company…
info Commented-code block (5 lines) in 23-ai-workforce-blueprint/scripts/_qc_owner_c…
info Commented-code block (5 lines) in 23-ai-workforce-blueprint/scripts/create_role…
info Commented-code block (7 lines) in 23-ai-workforce-blueprint/scripts/build-workf…

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Config drift 3 findings

What it is: Settings duplicated across env files, Docker compose, K8s, and code defaults, all with slightly different values.

Why it matters: Production behaviour depends on whichever copy your loader reads first. Subtle bugs in staging that don't reproduce in dev.

How AI causes it: AI writes new config from memory rather than reading the existing source.

Fix approach: Pick one source of truth (env vars + a settings module). Have every other place import from there. Lint for duplicates in CI.

3 matching findings on this repo

high Agent instruction/config may expose a secret: 09-context7/SKILL.md 09-context7/SKILL.md:65
high Agent instruction/config may expose a secret: 17-self-improving-agent/upstream-… 17-self-improving-agent/upstream-original/SKILL.md:159
high Agent instruction/config may expose a secret: 28-cinematic-forge/SKILL.md 28-cinematic-forge/SKILL.md:272

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