antoinezambelli/forge

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https://github.com/antoinezambelli/forge.git · scanned 2026-05-21 14:10 UTC (2 weeks ago) · 10 languages

138 findings (80 legacy + 58 scanner) 99th percentile · Python · medium (20-100K LoC) Scanner says 96 (lower by 5)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 weeks ago · v2 · 109 findings from 2 sources. Findings combine the legacy security pipeline AND the multi-layer engine (atlas, wiring, flows, ranked) AND verified AI agent contributions.

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Score breakdown â 2026-05-18-v5

Component	Sub-score	Weight	Contribution
`structure_score`	100.0	0.15	15.00
`security_score`	100.0	0.25	25.00
`testing_score`	100.0	0.20	20.00
`documentation_score`	100.0	0.15	15.00
`practices_score`	75.0	0.15	11.25
`code_quality`	43.1	0.10	4.31
Overall		1.00	90.6

Severity distribution — click a segment to filter

Active filters: excluding tests × Reset all

Severity: Critical 1 High 65 Medium 2 Low 25 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Legacy 80 9-layer 29 Crowd 0 Layer: Quality 95 Software 10 Api 1 Security 1 Cicd 2

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.

Fragile runtime 75 findings

What it is: Code that runs but breaks under predictable input — division by zero, missing keys, unbounded loops, off-by-one slicing.

Why it matters: Reaches production undetected because happy-path tests pass. First user with a weird input crashes the request.

How AI causes it: AI loves writing the happy path; doesn't probe edge cases unless explicitly asked.

Fix approach: Add property-based tests. Wrap external inputs with explicit validators. Use the framework's typed deserializer (Pydantic, attrs).

12 matching findings on this repo

medium [COMP001] High cognitive complexity: Function `_phase1` has cognitive complexit… src/forge/context/strategies.py:204
medium Bare except continues silently src/forge/proxy/server.py:98
medium Bare except continues silently src/forge/core/runner.py:324
medium Bare except continues silently src/forge/core/slot_worker.py:137
medium Bare except continues silently tests/eval/batch_eval.py:473
medium Bare except continues silently tests/eval/eval_runner.py:303
medium Bare except continues silently tests/eval/eval_runner.py:293
medium Bare except continues silently tests/eval/eval_runner.py:613
medium Bare except continues silently tests/eval/eval_runner.py:338
low [COMP001] High cognitive complexity: Function `mock_backend_with_health` has co… scripts/smoke_test_proxy.py:71
low Duplicated implementation block across source files tests/eval/scenarios/_stateful_plumbing.py:7
low Duplicated implementation block across source files tests/eval/scenarios/_stateful_model_quality.py:8

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Legacy markers 4 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.

4 matching findings on this repo

low Legacy-named symbol `compensation_v2` in tests/unit/test_data_gap_recovery_exte…
low Legacy-named symbol `test_known_model_returns_copy` in tests/unit/test_sampling…
low Legacy-named symbol `compensation_v2` in tests/eval/scenarios/_model_reasoning.…
low Legacy-named symbol `compensation_v2` in tests/eval/scenarios/_stateful_model_r…

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Commented-out code 8 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/`.

8 matching findings on this repo

info Commented-code block (9 lines) in tests/unit/test_grounded_synthesis.py:351
info Commented-code block (9 lines) in tests/eval/report.py:445
info Commented-code block (12 lines) in tests/eval/scenarios/_model_reasoning.py:66
info Commented-code block (5 lines) in src/forge/server.py:511
info Commented-code block (8 lines) in src/forge/clients/sampling_defaults.py:44
info Commented-code block (5 lines) in src/forge/clients/llamafile.py:19
info Commented-code block (5 lines) in src/forge/core/inference.py:186
info Commented-code block (7 lines) in src/forge/prompts/templates.py:130

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Config drift 2 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.

2 matching findings on this repo

low File has no detected symbols: tests/eval/dashboard/vite.config.ts
low File has no detected symbols: tests/eval/dashboard/eslint.config.js

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