Automated summary
Verifies per-token AI model pricing against official provider pages, updates backend/core/providers/pricing.py and regenerates the PRICING.md report, but only inside the Chatty repo.
Strengths
- Enforces two explicit guards: it refuses to act outside the Chatty repo, and it skips re-fetching when pricing was already verified earlier in the same conversation.
- Forbids fabrication: a model whose rate is missing from the official page is left out of MODEL_PRICING and reported as unknown instead of guessed.
- Regenerates PRICING.md from the updated code (with per-model source URL and verification date) rather than letting hand-written numbers drift.
- Also prices newly surfaced dynamic models by taking the union of existing keys and each provider's current model list.
Limitations
- Tightly coupled to the Chatty repo: file paths, provider set and identity guard are hard-coded, so it is not portable to other projects.
- Relies on WebFetch against four vendor pricing pages whose layout can change or become unreachable, which may leave models unverifiable.
- Covers only the STANDARD tier and the four listed providers (Anthropic, OpenAI, Google, Together); other tiers or providers are not handled.
Run it on any PR that adds or changes models or touches core/providers/ or core/agents/usage/, or when someone explicitly asks whether pricing is current.
Don't use it outside the Chatty repo, or when you need rates for providers or billing tiers this skill does not cover.
Security analysis
SafeThe skill is narrowly scoped to the Chatty repository and only edits pricing metadata files. It explicitly forbids secret handling, avoids destructive commands, and uses network access solely to read public pricing pages. The automatic git commit is a mild operational concern but not a security risk.
- •Automatically commits changes to git without an explicit user confirmation step, though it is guarded to a specific repo and files.
- •Uses WebFetch against external pricing pages and may call local provider model-list endpoints if credentials are configured, but does not send secrets out.
Examples
I just added Gemini 2.5 Flash to the provider model list — run price-check and show me the diff table before I open the PR.Check prices: is our model pricing current? Refresh pricing.py and PRICING.md if anything changed.Is pricing current? If any model's rate isn't on the official page, leave it out and tell me which ones are unknown.name: price-check description: Verify and refresh AI model pricing in Chatty's pricing.py from official provider pricing pages, and regenerate PRICING.md. Run during any PR that touches providers or usage. Skips re-fetching if pricing was already verified earlier in the current chat. Only operates inside the Chatty repo.
price-check
Keeps backend/core/providers/pricing.py (MODEL_PRICING + PRICING_SOURCES) current with published per-token rates and regenerates the reviewable report backend/core/providers/PRICING.md. No provider's models API exposes price, so this skill is the maintenance mechanism that keeps the usage/cost dashboard accurate as new models are added dynamically.
When to run
- During any PR that adds/changes models or touches
core/providers/orcore/agents/usage/(required by the projectCLAUDE.md→ Model Pricing). - On request: "check prices", "refresh model pricing", "is pricing current?".
Guard 1 — ship only in the Chatty repo
Before writing or committing anything, confirm this is the Chatty repo:
git remote -vcontainswwilson1017/chatty, ORCLAUDE.mdstarts with# ChattyANDbackend/core/providers/pricing.pyexists.
If neither holds, STOP: report that price-check only runs in the Chatty repo, and make no changes.
Guard 2 — skip if already verified this chat
If model pricing was already fetched/verified earlier in THIS conversation, or backend/core/providers/PRICING.md already shows Last verified: <today> with no pending diff, do NOT re-fetch. Reuse the in-session results and report "already current". Re-fetching wastes calls and risks rate limits.
Procedure
- Model set. Union of the keys in
MODEL_PRICINGand each provider's current model list — the fallback*_MODELSconstants, plus (if credentials are configured) whatGET /api/providers/{provider}/modelsreturns. This prices newly-surfaced dynamic models, not just legacy ones. - Fetch current STANDARD-tier rates (USD per 1M input / output tokens) via WebFetch from the official pages:
- Anthropic —
https://platform.claude.com/docs/en/about-claude/models/overview - OpenAI —
https://developers.openai.com/api/docs/pricing - Google —
https://ai.google.dev/gemini-api/docs/pricing - Together —
https://www.together.ai/pricingRecord tier caveats (e.g. Gemini 2.5 Pro is the ≤200K-prompt tier) in a code comment.
- Anthropic —
- Diff against the current
MODEL_PRICING; classify each model: added / changed / unchanged / unverifiable. - Never fabricate. If a model's rate isn't on the official page, leave it OUT of
MODEL_PRICINGand report it as "unknown" — the usage dashboard already flags unpriced paid models (is_priced/ per-agenthas_unknown_pricing). Do NOT guess from memory or community posts. - Write
backend/core/providers/pricing.py:MODEL_PRICING[model] = (input, output)PRICING_SOURCES[model] = (source_url, "<YYYY-MM-DD>")— use the current session date. Keep proven legacy entries (the dashboard prices historical rows by model id via longest-prefix match).
- Regenerate
backend/core/providers/PRICING.mdfrom the updatedpricing.py(do not hand-author divergent numbers): a header lineLast verified: <YYYY-MM-DD> (price-check)followed by a per-provider tablemodel | input $/M | output $/M | source | verified. - Report a concise diff table to the user. When run during a PR, also place the diff in the PR description.
Commit
- Commit
pricing.pyandPRICING.mdtogether, e.g.Refresh model pricing (price-check <YYYY-MM-DD>). - No
Co-Authored-Byor "Generated with Claude Code" footers (repo policy). - Never commit secrets; never run
gcloud secrets/--set-secretscommands.
Notes
- The session date is authoritative for the
verifieddate — read it from the environment context, don't compute it in code. - This skill is committed into the Chatty repo so it travels with the project; it is the canonical place to evolve the pricing-refresh workflow.
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