Tantivy is a full-text search engine library inspired by Apache Lucene and written in Rust
This report presents the forensic synthetic code analysis of quickwit-oss/tantivy, a Rust project with 15,549 GitHub stars. SynthScan v2.0 examined 153,407 lines of code across 490 source files, recording 493 pattern matches distributed across 7 syntactic categories. The overall adjusted score of 3.6 places this repository in the Likely human-written band.
The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).
This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.
Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.
This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.
The scanner identified 493 distinct pattern matches across 7 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.
Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | cliff.toml | 61 | COMMENT | |
| LOW | columnar/src/dynamic_column.rs | 241 | pub fn open(&self) -> io::Result<DynamicColumn> { | COMMENT |
| LOW | columnar/src/lib.rs | 1 | //! # Tantivy-Columnar | COMMENT |
| LOW | columnar/src/value.rs | 101 | 1 => Ok(NumericalType::U64), | COMMENT |
| LOW | columnar/src/dictionary.rs | 21 | COMMENT | |
| LOW | columnar/src/columnar/merge/mod.rs | 61 | /// If several columns with the same name are conflicting with the numerical types in the | COMMENT |
| LOW | columnar/src/columnar/merge/tests.rs | 41 | let columnar2 = make_columnar("numbers", &[2u64]); | COMMENT |
| LOW | columnar/src/column_index/multivalued_index.rs | 101 | } | COMMENT |
| LOW | columnar/src/column_index/multivalued_index.rs | 241 | } | COMMENT |
| LOW | columnar/src/column_index/multivalued_index.rs | 281 | pub fn num_docs(&self) -> u32 { | COMMENT |
| LOW | columnar/src/column_index/mod.rs | 141 | row_start..row_end | COMMENT |
| LOW | columnar/src/column_index/optional_index/mod.rs | 41 | pub fn num_bytes_in_block(&self) -> u32 { | COMMENT |
| LOW | columnar/src/column_index/optional_index/mod.rs | 61 | /// block] | COMMENT |
| LOW | columnar/src/column_values/monotonic_mapping.rs | 21 | fn from_u64(val: u64) -> Self; | COMMENT |
| LOW | columnar/src/column_values/mod.rs | 41 | COMMENT | |
| LOW | columnar/src/column_values/mod.rs | 141 | if value_range.contains(&val) { | COMMENT |
| LOW | …values/u128_based/compact_space/build_compact_space.rs | 101 | let saved_bits = (amplitude_bits - amplitude_new_bits) as usize * total_num_values as usize; | COMMENT |
| LOW | …mnar/src/column_values/u128_based/compact_space/mod.rs | 1 | /// This codec takes a large number space (u128) and reduces it to a compact number space. | COMMENT |
| LOW | columnar/src/column_values/u64_based/line.rs | 41 | // This is outside of realm we handle. | COMMENT |
| LOW | columnar/src/column_values/u64_based/line.rs | 81 | return Line::default(); | COMMENT |
| LOW | columnar/src/column_values/u64_based/line.rs | 101 | // Without sorting our values, this is a difficult problem. | COMMENT |
| LOW | columnar/src/column_values/u64_based/mod.rs | 21 | use crate::iterable::Iterable; | COMMENT |
| LOW | query-grammar/src/query_grammar.rs | 1061 | fn ast(inp: &str) -> IResult<&str, UserInputAst> { | COMMENT |
| LOW | sstable/src/block_match_automaton.rs | 41 | for kb in &start_key[0..common_prefix_len] { | COMMENT |
| LOW | sstable/src/block_match_automaton.rs | 61 | // e.* | | COMMENT |
| LOW | sstable/src/block_match_automaton.rs | 81 | // p | COMMENT |
| LOW | sstable/src/lib.rs | 1 | //! `tantivy_sstable` is a crate that provides a sorted string table data structure. | COMMENT |
| LOW | sstable/src/lib.rs | 21 | //! builder.insert(b"banana", &2).unwrap(); | COMMENT |
| LOW | sstable/src/streamer.rs | 261 | /// If the end of the stream as been reached, and `.next()` | COMMENT |
| LOW | sstable/src/dictionary.rs | 21 | /// to any kind of typed values. | COMMENT |
| LOW | sstable/src/dictionary.rs | 161 | block_addr: BlockAddr, | COMMENT |
| LOW | sstable/src/dictionary.rs | 421 | /// lower_bound: Bound::Included(aaa) => Included(0) // "Next" term id | COMMENT |
| LOW | sstable/src/index/v3.rs | 561 | max_slope_idx = index; | COMMENT |
| LOW | stacker/src/fastcmp.rs | 1 | /// fastcmp employs a trick to speed up the comparison of two slices of bytes. | COMMENT |
| LOW | stacker/src/arena_hashmap.rs | 1 | use super::{Addr, MemoryArena}; | COMMENT |
| LOW | stacker/src/arena_hashmap.rs | 61 | } | COMMENT |
| LOW | stacker/src/expull.rs | 1 | use std::mem; | COMMENT |
| LOW | stacker/src/expull.rs | 21 | /// It combines the idea of the unrolled linked list and tries to address the | COMMENT |
| LOW | stacker/src/shared_arena_hashmap.rs | 41 | fn is_empty(&self) -> bool { | COMMENT |
| LOW | stacker/src/shared_arena_hashmap.rs | 281 | let v = memory_arena.read(val_addr); | COMMENT |
| LOW | stacker/src/memory_arena.rs | 1 | //! 32-bits Memory arena for types implementing `Copy`. | COMMENT |
| LOW | stacker/src/memory_arena.rs | 21 | //! access them as references. | COMMENT |
| LOW | tokenizer-api/src/lib.rs | 1 | //! Tokenizer are in charge of chopping text into a stream of tokens | COMMENT |
| LOW | common/src/group_by.rs | 1 | use std::cell::RefCell; | COMMENT |
| LOW | common/src/lib.rs | 41 | fn len(&self) -> usize { | COMMENT |
| LOW | common/src/lib.rs | 61 | /// | COMMENT |
| LOW | common/src/lib.rs | 81 | /// For simplicity, tantivy internally handles `f64` as `u64`. | COMMENT |
| LOW | common/src/file_slice.rs | 281 | COMMENT | |
| LOW | common/src/datetime.rs | 21 | Milliseconds, | COMMENT |
| LOW | common/src/bitset.rs | 161 | // `trailing_zeros` and the bit-clear in parallel instead of | COMMENT |
| LOW | examples/index_from_multiple_threads.rs | 1 | // # Indexing from different threads. | COMMENT |
| LOW | examples/iterating_docs_and_positions.rs | 1 | // # Iterating docs and positions. | COMMENT |
| LOW | examples/iterating_docs_and_positions.rs | 41 | // (Because we indexed a very small number of documents over one thread | COMMENT |
| LOW | examples/iterating_docs_and_positions.rs | 101 | // and the [`Postings`](https://docs.rs/tantivy/~0/tantivy/trait.Postings.html) trait | COMMENT |
| LOW | examples/deleting_updating_documents.rs | 1 | // # Deleting and Updating (?) documents | COMMENT |
| LOW | examples/deleting_updating_documents.rs | 41 | COMMENT | |
| LOW | examples/deleting_updating_documents.rs | 101 | // # Update = Delete + Insert | COMMENT |
| LOW | examples/faceted_search.rs | 1 | // # Faceted Search | COMMENT |
| LOW | examples/aggregation.rs | 21 | // category, stock and price will be fast fields as that's the requirement | COMMENT |
| LOW | examples/aggregation.rs | 181 | // In this Aggregation we want to get the average price for different groups, depending on how | COMMENT |
| 389 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | .claude/skills/simple-pr/SKILL.md | 11 | ## Step 1: Check workspace state | COMMENT |
| LOW⚡ | .claude/skills/simple-pr/SKILL.md | 19 | ## Step 2: Ensure main is up to date | COMMENT |
| LOW⚡ | .claude/skills/simple-pr/SKILL.md | 25 | ## Step 3: Review staged changes | COMMENT |
| LOW⚡ | .claude/skills/simple-pr/SKILL.md | 31 | ## Step 4: Generate commit message | COMMENT |
| LOW⚡ | .claude/skills/simple-pr/SKILL.md | 37 | ## Step 5: Create a new branch | COMMENT |
| LOW⚡ | .claude/skills/simple-pr/SKILL.md | 45 | ## Step 6: Commit changes | COMMENT |
| LOW⚡ | .claude/skills/simple-pr/SKILL.md | 52 | ## Step 7: Push and open a PR | COMMENT |
| LOW⚡ | .claude/skills/rationalize-deps/SKILL.md | 18 | ## Step 1: Identify the target | COMMENT |
| LOW⚡ | .claude/skills/rationalize-deps/SKILL.md | 25 | ## Step 2: Analyze current dependencies | COMMENT |
| LOW⚡ | .claude/skills/rationalize-deps/SKILL.md | 33 | ## Step 3: For each candidate dependency | COMMENT |
| LOW | .claude/skills/rationalize-deps/SKILL.md | 76 | ## Step 4: Document findings | COMMENT |
| LOW | .claude/skills/rationalize-deps/SKILL.md | 84 | ## Step 5: Verify full build | COMMENT |
| LOW⚡ | .claude/skills/update-changelog/SKILL.md | 10 | ## Step 1: Determine the changelog scope | COMMENT |
| LOW⚡ | .claude/skills/update-changelog/SKILL.md | 16 | ## Step 2: Find merged PRs not yet in the changelog | COMMENT |
| LOW⚡ | .claude/skills/update-changelog/SKILL.md | 26 | ## Step 3: Consolidate related PRs | COMMENT |
| LOW | .claude/skills/update-changelog/SKILL.md | 38 | ## Step 4: Review the actual code diff | COMMENT |
| LOW | .claude/skills/update-changelog/SKILL.md | 49 | ## Step 5: Categorize each PR group | COMMENT |
| LOW | .claude/skills/update-changelog/SKILL.md | 61 | ## Step 6: Format entries | COMMENT |
| LOW⚡ | .claude/skills/update-changelog/SKILL.md | 75 | ## Step 7: Present changes to the user | COMMENT |
| LOW⚡ | .claude/skills/update-changelog/SKILL.md | 79 | ## Step 8: Update CHANGELOG.md | COMMENT |
| LOW⚡ | .claude/skills/update-changelog/SKILL.md | 85 | ## Step 9: Verify | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | examples/snippet.rs | 22 | // # Defining the schema | COMMENT |
| MEDIUM | examples/json_field.rs | 13 | // # Defining the schema | COMMENT |
| MEDIUM | examples/index_from_multiple_threads.rs | 36 | // # Defining the schema | COMMENT |
| MEDIUM | examples/deleting_updating_documents.rs | 43 | // # Defining the schema | COMMENT |
| MEDIUM | examples/basic_search.rs | 26 | // # Defining the schema | COMMENT |
| MEDIUM | examples/ip_field.rs | 12 | // # Defining the schema | COMMENT |
| MEDIUM | examples/custom_collector.rs | 123 | // # Defining the schema | COMMENT |
| MEDIUM | examples/custom_tokenizer.rs | 1 | // # Defining a tokenizer pipeline | COMMENT |
| MEDIUM | examples/custom_tokenizer.rs | 12 | // # Defining the schema | COMMENT |
| MEDIUM | examples/fuzzy_search.rs | 25 | // # Defining the schema | COMMENT |
| MEDIUM | examples/date_time_field.rs | 11 | // # Defining the schema | COMMENT |
| MEDIUM | src/query/fuzzy_query.rs | 194 | // # Defining the schema | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | src/aggregation/bucket/term_agg/term_histogram.rs | 233 | // value count. (Essentially always true here: the column is full, so its value count | COMMENT |
| MEDIUM | src/schema/mod.rs | 101 | //! Some queries may leverage Fast fields when run on a field that is not indexed. This can be | COMMENT |
| MEDIUM | src/schema/text_options.rs | 192 | /// Essentially, should we store the term frequency and/or the positions (See | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | src/functional_test.rs | 132 | const LOREM: &str = "Doc Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod \ | CODE |
| LOW | src/functional_test.rs | 132 | const LOREM: &str = "Doc Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod \ | CODE |
| LOW | src/indexer/index_writer.rs | 844 | const LOREM: &str = "Doc Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do \ | CODE |
| LOW | src/indexer/index_writer.rs | 844 | const LOREM: &str = "Doc Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do \ | CODE |
| LOW | src/store/mod.rs | 68 | const LOREM: &str = "Doc Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do \ | CODE |
| LOW | src/store/mod.rs | 68 | const LOREM: &str = "Doc Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do \ | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | src/postings/recorder.rs | 408 | // ── TermFrequencyRecorder ───────────────────────────────────────────────── | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | src/query/phrase_query/phrase_scorer.rs | 570 | // So the cost estimation would be the number of times we need to check if a doc is a hit * | COMMENT |