conflict-detector
Skill4 starsChanged 24 days agoMITView on GitHub
Cross-document conflict detector. Use when the user has two or more documents, datasets, or extracted fact tables and wants to find contradictions between them. Triggers on "detect conflicts", "find contradictions", "do these documents agree", "cross-check claims", "inconsistency check", or when comparing a claim across multiple sources. Runs three detection levels: entity (numeric / boolean mismatch on the same key), clause (categorical mismatch), and argument (free-text disagreement). Emits a machine-readable conflict report in JSON / CSV / Markdown.
- Installs packages
1 other project uses a version of this.
Adopted by
Most recently taken up by
- JiamingShi-JsPhys/chelate-shelltheir own version, first seen Oct 25, 2026
Other versions1 project uses a version of this.
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Wrote their own version · 1
- JiamingShi-JsPhys/chelate-shell★ 10same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository6 other files it gives its agents.
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The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 1 is distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 57
Before the first run, probe the runtime deps for this skill:
- Very specific: line 63
If PyYAML is missing and the input is YAML, tell the user and ask whether to pip install pyyaml.
- Very specific: line 77
Verify every documents[].value / documents[].path is reachable.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
conflict-detector
A self-contained skill that finds **contradictions across a set of
documents**. Each document is loaded (path / inline text / inline JSON),
its facts are extracted, and a cross-document rule engine pairs claims by
canonical key and flags mismatches.
MANDATORY WORKFLOW
Dependency bootstrap (run on first use)
Before the first run, probe the runtime deps for this skill:
- Core: pure standard library — no install required.
- Optional:
PyYAML(only when the config / input is a.yaml; JSON inputs work with the standard library alone).
If PyYAML is missing and the input is YAML, tell the user and ask
whether to pip install pyyaml; install only after they confirm. Never
install into the global environment without explicit consent.
- Load the YAML config (
config/examples/two_docs.yamlas reference). - Verify every
documents[].value/documents[].pathis reachable. python -m src.cli run --config <path> [--format json,csv,md].Report the per-level conflict count and point the user at
./conflicts/conflicts_<run_id>.*.
When to use
Two or more documents, datasets, or extracted fact tables must be checked
against each other for contradictions.
The user asks to "detect conflicts", "find contradictions", "cross-check
claims", or asks "do these documents agree".
A single claim (a number, a status, a named fact) appears in several
sources and must be compared across them.
A fact table extracted from documents must be audited for internal
consistency before it is relied on.
Usage examples
# Validate a config before running it (fast, no report written).
python -m src.cli validate --config config/examples/two_docs.yaml
# List the document sources a config resolves to.
python -m src.cli list-docs --config config/examples/two_docs.yaml
# Run a detection; pick the output formats (default: json).
python -m src.cli run --config config/examples/two_docs.yaml --format json,csv,md
Reports are written to ./conflicts/conflicts_<run_id>.{json,csv,md}; the
JSON is the machine-readable contract.
Failure handling
Config invalid (
validateexits non-zero) - fix the reported fieldand re-validate; do not hand-edit around a schema violation.
A document source is unreachable - the run aborts naming the
offending
documents[]entry; verify the path or inline value, retry.No conflicts found - a valid, reportable result (an empty report),
not an error; say so explicitly instead of re-running.
Unexpected exit code - report the message verbatim; do not fall back
to comparing the documents by hand.
Detection levels
| Level | Kind | Severity | Example |
| --- | --- | --- | --- |
| entity | numeric_mismatch, boolean | high | speed = 10 vs speed = 20 |
| clause | categorical | medium | status = "active" vs status = "archived" |
| argument | categorical (text) | low | free-text lines that disagree |
Limitations
Extraction is key-value oriented; free-text paragraphs only participate
at the
argumentlevel (line-level comparison).Unit normalisation is table-driven (
unit_map); custom unit rules mustbe supplied via the config.
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