fix: make PubChem CAS resolution conservative

.agents/skills/curate-aroma-data/SKILL.md

@@ -12,17 +12,19 @@ Build traceable compound tables through the repository's `aromanexus` CLI. Keep
 1. Inspect the input without modifying it.
    - Run `python .agents/skills/curate-aroma-data/scripts/inspect_workbook.py INPUT` from the repository root.
    - Confirm the row count, exact column names, identifier quality, duplicates, and formula-like cells.
+   - Identify section labels, headers, totals, and other structural rows before provider calls. Define an explicit dataset-specific skip rule; do not assume that text such as `C6` is globally non-chemical.
 2. Choose the smallest provider set that supplies the requested fields.
    - Read [references/provider-matrix.md](references/provider-matrix.md) before any network or browser operation.
    - Prefer PubChem for canonical identity and sourced odor annotations.
    - Use NIST only for the existing retention-index or name-resolution workflows.
    - Use Pyrfume only for explicitly selected archives after reviewing each manifest note.
    - Use M2OR only when receptor bioassay evidence is relevant; label species and assay scope.
 3. Preview the operation.
-   - State the input, new output path, selected provider, expected columns, approximate request count, cache behavior, and material access caveats.
+   - State the input, new output path, selected provider, expected columns, skip patterns, approximate request count, cache behavior, and material access caveats.
    - Write a sibling output by default. Do not pass `--force` or overwrite the input unless the user explicitly requests that exact replacement.
 4. Run one focused command.
    - Identity and odor metadata: `aromanexus pubchem INPUT --identifier-column "CAS Number"`
+   - Name lookup with dataset-specific structural rows: `aromanexus pubchem INPUT --identifier-column "Name" --skip-pattern '^C\d+$'`
    - Retention indices: `aromanexus nist-ri INPUT --cas-column "CAS Number" --calculated-ri-column "Calculated RI"`
    - Names to CAS: `aromanexus resolve-cas INPUT --name-column "Name"`
    - Curated descriptors: `aromanexus pyrfume INPUT --archives aromadb,superscent`
@@ -31,6 +33,8 @@ Build traceable compound tables through the repository's `aromanexus` CLI. Keep
 5. Verify the result.
    - Re-run the inspection script on the output.
    - Confirm identical row order and row count, expected new fields, typed status counts, source URL, retrieval time, version, and license/access fields.
+   - Treat `PubChem Status` as provider execution state, not proof of a uniquely resolved CAS. Check `PubChem CAS Resolution`, candidate count, and `Resolved CAS` separately.
+   - Leave `multiple` and `missing` CAS resolutions unresolved; retain all candidates and route only the affected rows to a targeted fallback source or manual review.
    - Treat `http_error`, `network_error`, `parse_error`, `missing_data`, `data_error`, `partial`, `blocked`, and `skipped` separately from `not_found`.
    - Consult [references/output-schema.md](references/output-schema.md) when reconciling columns or statuses.
 6. Report the output path, provider versions, status counts, partial failures, and any source terms the user must still review.
@@ -43,3 +47,4 @@ Build traceable compound tables through the repository's `aromanexus` CLI. Keep
 - Do not describe the toolkit as AI-powered. Say that structured exports can support downstream statistics, cheminformatics, or machine-learning experiments.
 - Do not bundle or republish downloaded Pyrfume or M2OR data in the repository.
 - Preserve remote text as literal spreadsheet cells to prevent formula execution.
+- Never select the first PubChem CAS candidate merely because the provider status is `ok`.

.agents/skills/curate-aroma-data/references/output-schema.md

@@ -7,6 +7,25 @@
 - Keep CAS as an external identifier and validate its checksum before exact-match providers.
 - Never silently pick an ambiguous name result.
 
+## PubChem CAS resolution
+
+Keep provider execution and CAS curation in separate columns:
+
+- `PubChem Status`: whether the provider request and record parsing succeeded.
+- `PubChem CAS Numbers`: every checksum-valid candidate retained for review.
+- `PubChem CAS Candidate Count`: the number of distinct valid candidates.
+- `PubChem CAS Resolution`: the conservative resolution decision.
+- `Resolved CAS`: populate only for `query_confirmed` or `unique`.
+
+Interpret `PubChem CAS Resolution` as follows:
+
+- `query_confirmed`: the input was a checksum-valid CAS and PubChem resolved its record.
+- `unique`: a successful name lookup returned exactly one valid CAS candidate.
+- `multiple`: more than one valid candidate remains; keep `Resolved CAS` empty.
+- `missing`: a successful record returned no valid CAS candidate; keep `Resolved CAS` empty.
+- `not_evaluated`: provider failure prevented a defensible CAS decision.
+- `skipped`: an explicit user-supplied rule excluded the row before lookup.
+
 ## Status values
 
 - `ok`: a provider returned a parsed record.
@@ -20,7 +39,7 @@
 - `data_error`: every selected archive failed to load; inspect the per-archive diagnostic message.
 - `partial`: at least one selected source succeeded and at least one failed, or a provider returned usable data with warnings.
 - `blocked`: access policy or missing permission prevented the request.
-- `skipped`: a user deliberately skipped an interactive record.
+- `skipped`: a user deliberately excluded a record through an interactive choice or explicit skip rule.
 
 Do not merge an access, transport, HTTP, snapshot, parse, or partial failure into `not_found`.
 
@@ -38,3 +57,4 @@ After every run, confirm:
 4. Every processed row has a typed status.
 5. Remote strings beginning with `=`, `+`, `-`, or `@` are stored as literal text.
 6. Partial outputs are reported separately if a run is interrupted.
+7. `multiple`, `missing`, `not_evaluated`, and `skipped` PubChem CAS resolutions never contain an automatic `Resolved CAS`.

README-CN.md

@@ -66,6 +66,9 @@ CLI 支持 `.xlsx`、`.csv` 和 `.tsv`。列名均可修改；下面使用默认
 # 规范化身份、理化性质、同义词、CAS 标识符与带来源的气味文本
 aromanexus pubchem compounds.xlsx --identifier-column "CAS Number"
 
+# 在名称查询前跳过当前数据集中的结构标签
+aromanexus pubchem compounds.xlsx --identifier-column "Name" --skip-pattern '^C\d+$'
+
 # 在 NIST 中寻找最接近实验计算值的保留指数
 aromanexus nist-ri data.xlsx \
   --cas-column "CAS Number" \
@@ -112,7 +115,7 @@ aromanexus --cache-dir .cache/aromanexus --timeout 30 pubchem compounds.xlsx
 
 所有表格命令默认在输入文件旁生成新文件，保留原有行序和列，再添加数据源字段。例如，PubChem 会将 `compounds.xlsx` 输出为 `compounds_pubchem.xlsx`。
 
-默认来源记录包括数据源状态、来源 URL、获取时间、是否命中缓存、固定版本、许可 URL 与诊断信息。只有在确实需要旧版形状时才使用 `--no-provenance`。
+默认来源记录包括数据源状态、来源 URL、获取时间、是否命中缓存、固定版本、许可 URL 与诊断信息。PubChem 会单独报告 CAS 解析状态；仅当输入 CAS 得到确认，或只剩一个校验有效的候选时，才填入 `Resolved CAS`。多个或缺失候选会保持未解析。只有在确实需要旧版形状时才使用 `--no-provenance`。
 
 ```bash
 # 明确指定输出位置

README.md

@@ -66,6 +66,9 @@ The CLI accepts `.xlsx`, `.csv`, and `.tsv` tables. Column names are configurabl
 # Canonical identity, properties, synonyms, CAS identifiers, and sourced odor text
 aromanexus pubchem compounds.xlsx --identifier-column "CAS Number"
 
+# Skip dataset-specific structural labels before a name lookup
+aromanexus pubchem compounds.xlsx --identifier-column "Name" --skip-pattern '^C\d+$'
+
 # Closest NIST RI to an experimentally calculated RI
 aromanexus nist-ri data.xlsx \
   --cas-column "CAS Number" \
@@ -112,7 +115,7 @@ aromanexus --cache-dir .cache/aromanexus --timeout 30 pubchem compounds.xlsx
 
 Every table command writes a sibling file by default, keeps the original row order and columns, and adds provider fields. For example, `compounds.xlsx` becomes `compounds_pubchem.xlsx` after a PubChem run.
 
-By default, provenance columns include provider status, source URL, retrieval timestamp, cache hit, pinned version, license URL, and a diagnostic message. Use `--no-provenance` only for legacy-shaped output.
+By default, provenance columns include provider status, source URL, retrieval timestamp, cache hit, pinned version, license URL, and a diagnostic message. PubChem reports CAS resolution separately and populates `Resolved CAS` only when the input is a confirmed CAS or exactly one checksum-valid candidate remains. Multiple or missing candidates stay unresolved. Use `--no-provenance` only for legacy-shaped output.
 
 ```bash
 # Choose an output explicitly

aromanexus/__init__.py

@@ -3,4 +3,4 @@
 from aromanexus.models import LookupResult
 
 __all__ = ["LookupResult"]
-__version__ = "0.3.0"
+__version__ = "0.3.1"

aromanexus/cli.py

@@ -99,6 +99,18 @@ def build_parser() -> argparse.ArgumentParser:
     )
     _add_table_arguments(pubchem)
     pubchem.add_argument("--identifier-column", default="CAS Number")
+    pubchem.add_argument(
+        "--skip-pattern",
+        action="append",
+        default=[],
+        metavar="REGEX",
+        help="Skip identifiers matching this regex before lookup; repeat for multiple patterns",
+    )
+    pubchem.add_argument(
+        "--resolved-cas-column",
+        default="Resolved CAS",
+        help="Output column populated only for query-confirmed or unique CAS resolution",
+    )
     pubchem.add_argument("--no-odor", action="store_true", help="Skip PUG-View odor annotations")
     pubchem.set_defaults(handler=_handle_pubchem)
 
@@ -199,6 +211,8 @@ def _handle_pubchem(args: argparse.Namespace) -> RunSummary:
         args.input,
         client,
         identifier_column=args.identifier_column,
+        resolved_cas_column=args.resolved_cas_column,
+        skip_patterns=args.skip_pattern,
         include_odor=not args.no_odor,
         **_common_kwargs(args),
     )

aromanexus/workflows.py

@@ -3,6 +3,7 @@
 from __future__ import annotations
 
 import json
+import re
 import time
 from collections import Counter
 from collections.abc import Callable, Iterable
@@ -18,6 +19,7 @@
     require_columns,
     write_table,
 )
+from aromanexus.identifiers import clean_text, is_valid_cas, normalize_cas
 from aromanexus.models import LookupResult
 from aromanexus.sources.chemicalbook import ManualVerificationRequired
 
@@ -217,25 +219,99 @@ def run_resolve_cas(
 }
 
 
+def _compile_skip_patterns(patterns: Iterable[str] | str | None) -> tuple[re.Pattern[str], ...]:
+    raw_patterns = (patterns,) if isinstance(patterns, str) else patterns or ()
+    compiled: list[re.Pattern[str]] = []
+    for pattern in raw_patterns:
+        try:
+            compiled.append(re.compile(pattern))
+        except re.error as exc:
+            raise ValueError(f"Invalid --skip-pattern regex {pattern!r}: {exc}") from exc
+    return tuple(compiled)
+
+
+def _valid_cas_candidates(value: Any) -> list[str]:
+    if isinstance(value, (list, tuple, set)):
+        raw_candidates = value
+    elif value is None:
+        raw_candidates = ()
+    else:
+        raw_candidates = (value,)
+
+    candidates: list[str] = []
+    for candidate in raw_candidates:
+        normalized = normalize_cas(candidate)
+        if is_valid_cas(normalized) and normalized not in candidates:
+            candidates.append(normalized)
+    return candidates
+
+
+def _apply_pubchem_resolution(
+    frame: pd.DataFrame,
+    index: Any,
+    identifier: Any,
+    result: LookupResult,
+    *,
+    resolved_cas_column: str,
+) -> None:
+    candidates = _valid_cas_candidates(result.values.get("cas_numbers"))
+    resolved_cas = ""
+    if result.status == "skipped":
+        resolution = "skipped"
+    elif result.status != "ok":
+        resolution = "not_evaluated"
+    else:
+        query_cas = normalize_cas(identifier)
+        if is_valid_cas(query_cas):
+            resolution = "query_confirmed"
+            resolved_cas = query_cas
+        elif len(candidates) == 1:
+            resolution = "unique"
+            resolved_cas = candidates[0]
+        elif candidates:
+            resolution = "multiple"
+        else:
+            resolution = "missing"
+
+    _set_cell(frame, index, "PubChem CAS Resolution", resolution)
+    _set_cell(frame, index, "PubChem CAS Candidate Count", len(candidates))
+    _set_cell(frame, index, resolved_cas_column, resolved_cas)
+
+
 def run_pubchem(
     input_path: str | Path,
     client: Any,
     *,
     output_path: str | Path | None = None,
     identifier_column: str = "CAS Number",
+    resolved_cas_column: str = "Resolved CAS",
+    skip_patterns: Iterable[str] | str | None = None,
     include_odor: bool = True,
     include_provenance: bool = True,
     checkpoint_every: int = 25,
     force: bool = False,
     progress: ProgressCallback = console_progress,
 ) -> RunSummary:
+    compiled_skip_patterns = _compile_skip_patterns(skip_patterns)
     frame, destination = _prepare_run(input_path, output_path, suffix="_pubchem", force=force)
     require_columns(frame, identifier_column)
     statuses: Counter[str] = Counter()
     total = len(frame)
     for current, index, row in _indices(frame):
         identifier = row[identifier_column]
-        result = client.lookup(identifier, include_odor=include_odor)
+        identifier_text = clean_text(identifier)
+        matching_pattern = next(
+            (pattern for pattern in compiled_skip_patterns if pattern.search(identifier_text)),
+            None,
+        )
+        if matching_pattern is not None:
+            result = LookupResult.failure(
+                "PubChem",
+                status="skipped",
+                message=f"Identifier matched --skip-pattern {matching_pattern.pattern!r}",
+            )
+        else:
+            result = client.lookup(identifier, include_odor=include_odor)
         _apply_result(
             frame,
             index,
@@ -244,6 +320,13 @@ def run_pubchem(
             prefix="PubChem",
             key_map=PUBCHEM_COLUMN_MAP,
         )
+        _apply_pubchem_resolution(
+            frame,
+            index,
+            identifier,
+            result,
+            resolved_cas_column=resolved_cas_column,
+        )
         statuses[result.status] += 1
         progress(current, total, f"PubChem: {identifier} -> {result.status}")
         _checkpoint(frame, destination, current, checkpoint_every)

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "aromanexus"
-version = "0.3.0"
+version = "0.3.1"
 description = "Provenance-aware integration for odorant, flavor-molecule, and olfactory-receptor data"
 readme = "README.md"
 license = "MIT"

tests/test_cli.py

@@ -13,3 +13,39 @@ def test_missing_input_returns_user_error(capsys, tmp_path):
     code = main(["pubchem", str(tmp_path / "missing.xlsx")])
     assert code == 2
     assert "does not exist" in capsys.readouterr().err
+
+
+def test_pubchem_cli_forwards_repeatable_skip_patterns_and_resolved_column(monkeypatch, tmp_path):
+    input_path = tmp_path / "input.csv"
+    input_path.write_text("Name\nC6\n", encoding="utf-8")
+    captured = {}
+
+    monkeypatch.setattr("aromanexus.sources.pubchem.PubChemClient", lambda **_kwargs: object())
+
+    def fake_run_pubchem(input_file, client, **kwargs):
+        captured["input"] = input_file
+        captured["client"] = client
+        captured["kwargs"] = kwargs
+        return 0
+
+    monkeypatch.setattr("aromanexus.cli.run_pubchem", fake_run_pubchem)
+
+    code = main(
+        [
+            "pubchem",
+            str(input_path),
+            "--identifier-column",
+            "Name",
+            "--skip-pattern",
+            r"^C\d+$",
+            "--skip-pattern",
+            "^Total$",
+            "--resolved-cas-column",
+            "Curated CAS",
+        ]
+    )
+
+    assert code == 0
+    assert captured["input"] == input_path
+    assert captured["kwargs"]["skip_patterns"] == [r"^C\d+$", "^Total$"]
+    assert captured["kwargs"]["resolved_cas_column"] == "Curated CAS"