claude-codeandClaude Opus 5.5
f9ad6763c8
A changed file, or the old path of a renamed one, that matches [hard_orange] paths gives ORANGE with one aggregated reason; such a file is not listed under the YELLOW tiers. The section is required; the repository layer only adds paths. hsadmin-ng and werkprobe move RBAC, authentication and secrets to [hard_orange]. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
56 lines
2.2 KiB
TOML
56 lines
2.2 KiB
TOML
# werkrevisor host config for reviewing werkrevisor itself on git.javagil.de.
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# It holds only what the host decides: model, prices, budget, gate, engine and the classifier endpoint.
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# The review rules of the repository are in .werkrevisor.toml at the repository root.
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# The PR never changes this file; Werkator passes its path in WERKREVISOR_CONFIG.
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[model]
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# The trial chose Sonnet: gemini-3.8-flash missed an obvious resource leak that Sonnet found.
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id = "openrouter/anthropic/claude-sonnet-5.5"
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# Operator-maintained prices in USD per 1M tokens.
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input_price_usd_per_mtok = 2.00
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output_price_usd_per_mtok = 10.00
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# Longer prompts degrade the review even within the context window of a frontier model.
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# The budget derives a lower input limit: 2 attempts × (input × 2.00 + 4000 × 10.00) / 1M ≤ 0.40 USD gives 80000 tokens.
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max_context_tokens = 150000
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# Includes reasoning tokens.
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max_output_tokens = 4000
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reasoning_effort = "low"
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timeout_seconds = 120
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max_retries = 1
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# Anthropic counts more tokens than o200k_base; calibrate with prompt_tokens / counted_raw_tokens of the usage records.
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# On werkrevisor PR#10 the factor 1.15 gave 49841 tokens, Anthropic reported 65792: 1.15 × 65792 / 49841 ≈ 1.52.
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token_count_factor = 1.55
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[budget]
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max_usd_per_review = 0.40
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min_key_remaining_usd = 0.50
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[hard_orange]
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# .werkrevisor.toml adds the critical paths of werkrevisor.
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paths = []
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[mechanical]
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# A changed file whose every changed line is an import, a whitespace change or a rename does not go to the model.
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# The built-in rules apply; .werkrevisor.toml may adjust them.
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enabled = true
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[gate]
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# Branch protection requires one approval from {bot, human_reviewers}; see the README.
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yellow_gate = "approval"
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human_reviewers = ["mi"]
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assessment_context = "ai-review/assessment"
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[engine]
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# "llm": the LLM review alone; "classifier": Jev alone, no LLM; "combined": Jev, then the LLM with Jev's hints.
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mode = "combined"
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[classifier]
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endpoint = "https://api.typesafe.ai/v1/systemone"
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model = "jev-latest"
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# Operator-maintained price in USD per 1M input tokens; Jev's output is free.
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input_price_usd_per_mtok = 0.042
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# Jev reads about 32000 tokens of state; a larger unit is not sent and makes the review YELLOW.
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max_state_chars = 60000
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max_units = 80
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timeout_seconds = 20
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