TheDocumentation Index
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claimcheck command accepts flags that control every aspect of an audit run: where to read lemmas from, which models handle informalization and comparison, how output is formatted, whether Dafny verification is also performed, and which API backend to route requests through. This page documents every flag, its type, its default value, and the conditions under which it applies. A companion command, claimcheck-multi, accepts the same flags and adds multi-file routing for projects with lemmas spread across several .dfy files.
Input
Short form: Required in file mode. Not used in
-m. Path to the mapping JSON file. The file must be an array of objects with requirement and lemmaName fields:--stdin mode.Path to the
.dfy file that contains the lemmas referenced by lemmaName in the mapping. Claimcheck extracts each lemma’s source text from this file before running the audit.Required in file mode. Not used in --stdin mode.Dafny module name (e.g.,
CounterDomain). Optional in file mode; required only when using --verify with module-based .dfy files. Claimcheck passes this name to dafny verify so it can resolve module-scoped lemmas correctly.Short form:
-d. Human-readable name for the domain being audited. Used as the report title and passed to the LLM as context. Defaults to the value of --module if provided, otherwise to the .dfy filename without its extension.Switch to stdin mode. Claimcheck reads a JSON object from standard input instead of extracting lemmas from a Output is always JSON when
.dfy file. The input must follow this shape:--stdin is used, regardless of the --json flag.Output
Emit the audit results as a JSON object on stdout instead of the default markdown report. See Understanding Claimcheck output for the full JSON schema.
Short form:
-v. Log API request/response details and Dafny verification output to stderr. Useful for debugging unexpected verdicts or API errors.Mode
Use single-prompt mode. One LLM call is made per requirement-lemma pair. The model first informalizes the lemma (without seeing the requirement), then compares the back-translation against the requirement in the same call. Produces richer verdicts —
JUSTIFIED, PARTIALLY_JUSTIFIED, NOT_JUSTIFIED, or VACUOUS — and includes vacuity analysis and surprising-restriction flags in the output.Slower and less accurate than the default two-pass mode (86.1% vs 96.3% in benchmarks) but provides more detailed explanations per result.Use naive mode. One LLM call per pair with no structural or prompt-level separation — the model sees the lemma and requirement simultaneously and returns a
JUSTIFIED or NOT_JUSTIFIED verdict with a brief explanation. Intended for comparison baselines, not production audits.Models
Model ID for single-prompt mode and naive mode. Has no effect in the default two-pass mode (use
--informalize-model and --compare-model instead).Model ID for the back-translation (informalization) step in two-pass mode. This model reads Dafny lemma signatures and produces English descriptions without seeing any requirements. Defaults to
us.anthropic.claude-haiku-4-5-20251001-v1:0 when --bedrock is active.Model ID for the comparison step in two-pass mode. This model receives the back-translated lemma descriptions alongside the original requirements and renders match verdicts. Defaults to
us.anthropic.claude-sonnet-4-6 when --bedrock is active.Verification
Run
dafny verify on each extracted lemma before the LLM audit. Lemmas that fail verification are reported with status verify-failed and are excluded from the LLM round-trip. Requires dafny to be available in PATH. For module-based .dfy files, also pass --module so the verifier can resolve the correct scope.Backend
Route API calls through Vertex AI instead of the Anthropic API. Requires
--vertex-project or the GOOGLE_CLOUD_PROJECT_ID environment variable. Mutually exclusive with --bedrock. Can also be enabled by setting USE_VERTEX=1 in the environment.Google Cloud project ID for Vertex AI. Required when
--vertex is active. Falls back to the GOOGLE_CLOUD_PROJECT_ID environment variable.Vertex AI region. Falls back to the
GOOGLE_CLOUD_REGION environment variable.Route API calls through AWS Bedrock instead of the Anthropic API. Credentials are resolved from the standard AWS credential chain (environment variables,
~/.aws/credentials, SSO, IMDS). Mutually exclusive with --vertex. Can also be enabled by setting USE_BEDROCK=1 in the environment.Default model IDs switch to cross-region inference profile prefixed IDs when Bedrock is active:- Informalize:
us.anthropic.claude-haiku-4-5-20251001-v1:0 - Compare:
us.anthropic.claude-sonnet-4-6
AWS region for Bedrock. Falls back to the
AWS_REGION environment variable.Claude Code
Route API calls through
claude -p (Claude Code) instead of the Anthropic API directly. Uses your existing Claude Code authentication and model routing — no ANTHROPIC_API_KEY required.Usage examples
Two-pass audit (default)
Two-pass audit with Dafny verification
Single-prompt audit with JSON output
Stdin mode (programmatic / CI)
Vertex AI backend
AWS Bedrock backend
Custom models
To audit lemmas spread across multiple
.dfy files, use claimcheck-multi with a mapping that includes a file field on each entry. See Run modes for details.