openrouter

Files (6)

• SKILL.md
• api-field-map.md · references/
• media-and-tools.md · references/
• reasoning-and-output.md · references/
• reliability.md · references/
• routing-cost-speed.md · references/

SKILL.md (first lines)

# OpenRouter

Make model behavior explicit. Preserve the user's quality, cost, privacy, and reliability requirements across every route and retry.

## Before changing configuration

1. Inspect the actual outgoing request, SDK version, existing configuration, and user preferences. Redact credentials and content. A setting in a UI or config file does not prove the SDK sends it.
2. Verify exact model IDs and live capabilities through the [models API](https://openrouter.ai/api/v1/models). Inspect the selected model's provider endpoints too. Check input/output modalities, context and output limits, supported parameters, reasoning options, prices, and provider availability for **both primary and fallback models**.
3. Choose and record an explicit reasoning setting for each reasoning model. Use the user's requested effort. If unspecified, choose a supported value for the task and state the choice; do not silently inherit a provider default or impose one effort on every model. Read [reasoning and output](references/reasoning-and-output.md) before setting these fields.
4. Set an output ceiling, total deadline, bounded retry policy, and cost limits appropriate to the workload. Reasoning uses output tokens too. A model's context window is not its maximum output length.
5. Read the relevant reference below. Consult current official docs for unfamiliar fields; do not invent model IDs, provider slugs, parameter support, or SDK syntax.

## Rules that prevent expensive mistakes

- Use the unified `reasoning` object. `reasoning.exclude: true` hides reasoning; it does **not** turn reasoning off or make it free. Mandatory reasoning models cannot be disabled.
- Check every fallback against the same required capabilities and privacy/cost constraints. A single `models` request shares configuration across candidates. If models need different efforts or budgets, implement bounded application-level attempts with separate configs.
- Separate provider failover from model fallback. `provider.order` is a preference; `only` restricts providers; `ignore` excludes them. Use `provider.require_parameters: true` when silently dropping requested parameters would break correctness. Recheck endpoint support; this is not a semantic guarantee.
- Match routing to the real goal: `provider.sort: "price"` for price, `"latency"` for TTFT, `"throughput"` for tokens/second. `:nitro` also permits priority tiers; `:floor` also permits flex tiers. They can change price or availability beyond plain sorting.
- HTTP 200 is not application success. Check errors, finish reason, expected output type, schema, and task-specific validity. Null text may be a valid tool call. A truncated or unreviewed answer must not become a successful artifact.
- Do not repeat a deterministic failure unchanged. On a confirmed output-limit failure, consider a supported lower effort, smaller task, or compatible fallback within the quality budget. Increasing the cap is one option, not the automatic answer. Preserve fail-closed validation on every attempt.
- Keep keys server-side. Log diagnostic metadata, not prompts, attachments, raw reasoning, or provider errors that may contain private content. Never weaken safety/privacy restrictions just to get a successful response.

## Read only what the task needs

- [Reasoning and output](references/reasoning-and-output.md): effort selection, token budgets, schemas, empty answers, adaptive retries, Python request example.
- [Routing, cost, and speed](references/routing-cost-speed.md): model fallbacks, provider filters, suffixes, tiers, performance thresholds, caching.
- [Images, other media, and tools](references/media-and-tools.md): image generation and aspect ratios, URL/base64 attachments, PDFs/audio/video, tool loops, reasoning preservation.
- [Reliability and observability](references/reliability.md): error handling, SSE, deadlines, billing, telemetry, privacy, deployment checks.
- [API field map and sources](references/api-field-map.md): endpoint selection, request parameter families, SDK passthrough, live schemas and authoritative sources.

## Verify the integration

Capture the serialized request in a redacted local test. Verify explicit reasoning, output limits, fallbacks, and routing constraints survive SDK serialization. Test the actual failure boundary: limit reached, null/tool output, malformed JSON, missing required capability, or mid-stream error. Run a small real smoke test when inference is authorized; do not describe mock validation as a production test.

For tuning, compare representative tasks using **valid-result rate, cost per valid result, time to first visible answer, and total duration**. Include retries and failed attempts. Lower effort or a faster route is acceptable only if required quality and safety still pass.

Report the chosen primary/fallback models, explicit effort and caps, routing goal, and what was verified. Distinguish confirmed API evidence from hypotheses.

From davidondrej/skills, MIT.

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