Techtide fetch foundation model pricing
Skill TechTideOhio/techtide-harness-kit/skills/finops/techtide-fetch-foundation-model-pricing
Trust contracts for AI agent skills: JSON Schema risk tiers, tool permissions, deny-by-default egress, approval gates, prompt-injection fixtures, ~28 CI validation gates. Apache-2.0.
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Fetch live per-token, per-image, and per-GPU-hour prices for foundation models across Anthropic, OpenAI, Google, AWS Bedrock, Azure OpenAI, OCI Generative AI, and Vertex AI. Supports single-model lookup and comparative multi-provider tables. Every price is labeled with source URL and ISO 8601 fetch timestamp. No credentials accepted.
SKILL.md
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Fetch Foundation Model Pricing
Purpose
Retrieve current public pricing for foundation models across the major AI/cloud providers and return structured, provenance-labeled output. Supports two modes:
- Single-model lookup: fetch the current price for a specific model and deployment target (e.g., Claude Sonnet 4.5 on Anthropic direct, or on Bedrock).
- Comparative table: build a side-by-side price comparison across two or more models or providers for the same task type (text, image, embedding, or GPU-hour).
When to use
Use this skill when:
- The user asks "how much does model X cost per token / per image / per GPU-hour"
- The user wants to compare inference costs across two or more providers for the same model family or equivalent capability tier
- The user needs to estimate monthly AI inference spend given a volume projection
- The user wants to understand how context caching or batch pricing changes the effective cost curve
- The user wants a FOCUS-aware cost breakdown (BilledCost, EffectiveCost) for AI inference line items
Operating rules
- Fetch live prices first. Use WebFetch to retrieve prices from each provider's public pricing page before relying on any internal knowledge. AI model pricing changes frequently; stale numbers mislead.
- Label every price. Each price value must carry exactly one provenance label:
live-price- fetched from a provider's public pricing page or API within this session; include source URL and ISO 8601 timestamp.documentation-based- sourced from official documentation when a live fetch was not possible; note the documentation URL and its visible publication date.assumed- derived from an analogous model or tier when no direct published price exists; state the assumption explicitly.excluded- pricing that exists but was intentionally omitted from the output; state why.
- Include source URL and timestamp. For every live-price value, state the exact URL fetched and the UTC timestamp of the fetch to the minute (e.g.,
2026-05-13T14:32Z). - On-demand pricing only unless told otherwise. Do not apply reserved capacity, committed use, or enterprise negotiated pricing unless the user explicitly requests it.
- No credentials required or accepted. All provider pricing pages are public and unauthenticated. Never ask for API keys, billing account IDs, or tenant-specific data.
- FOCUS column mapping. Where a cost estimate is produced, note the corresponding FOCUS v1.2 columns:
BilledCost(what the provider charges),EffectiveCost(after credits or discounts),ServiceCategory(AI and Machine Learning),ChargeCategory(Usage),SkuId(model ID + deployment tier),SkuPriceId(price dimension: input-token / output-token / cached-token / image / gpu-hour). - Load references only when needed.
Pricing dimensions
| Dimension | Unit | Applies to |
|---|---|---|
| Input tokens | per 1M tokens | All text models |
| Output tokens | per 1M tokens | All text models |
| Cached input tokens | per 1M tokens | Models with context caching (Anthropic, Gemini, Bedrock) |
| Batch input tokens | per 1M tokens | Models with async batch mode (Anthropic, OpenAI, Bedrock) |
| Batch output tokens | per 1M tokens | Models with async batch mode |
| Images (input) | per image or per 1K images | Multimodal models |
| GPU-hour | per hour per GPU type | Self-hosted / dedicated endpoints (Vertex AI, Bedrock provisioned throughput, Azure PTU) |
Providers in scope
| Provider | Deployment target | Reference |
|---|---|---|
| Anthropic | Direct API | references/providers.md |
| OpenAI | Direct API | references/providers.md |
| Vertex AI | references/providers.md | |
| AWS | Bedrock | references/providers.md |
| Azure | Azure OpenAI Service | references/providers.md |
| OCI | Generative AI Service | references/providers.md |
Response minimum
Return, at minimum:
- confirmed model name(s), provider(s), and deployment target(s)
- pricing dimensions covered (input, output, cached, batch, image, GPU-hour)
- line-item price table: model | provider | dimension | unit price | provenance label | source URL | fetch timestamp
- for comparative tables: a summary row noting the cheapest and most expensive option per dimension
- key assumptions (on-demand, no reserved/committed pricing, USD unless stated)
- FOCUS column mapping for any cost estimate produced
References
Load these only when needed:
- Provider pricing URLs - public pricing page URLs per provider for live WebFetch.
- Token economics - input/output/cached/batch pricing model, $/M token math, and context caching cost curve.