Agent Eval Suite Langsmith
Production agent eval suite LangSmith dataset curation + Promptfoo assertion framework +…
Forged from real client work, proof attached. Pick a piece or take the whole system.
Browse the full catalog → Browse ready-made kits → Build your own set →Lock every AI call to the most capable Opus model (no downgrade) and route cost savings through prompt caching, batch APIs and context engineering instead of cutting quality.
An enforcement skill that locks every AI call in your system to the most capable Opus model, with no downgrade to cheaper or faster models permitted. Instead of cutting quality to cut cost, it routes savings through prompt caching, batch APIs, and context engineering, so output quality stays consistent across every agent, script, and report.
Prices include 20% VAT. · Forged on real agency work · one-time, no lock-in
Inside the run · no black box
Downgrading to a cheaper model rarely saves money once revision rounds are priced in. This skill audits the whole fleet against that math and enforces a single top-model standard.
model-selection-router · core
core active · 6 lines
Auditing agent frontmatter to confirm every dispatch uses the Opus alias
Reviewing new skill files to block hidden cheaper-model declarations
Catching scripts that hardcode a frozen model ID instead of the alias
Rejecting cost-cutting proposals to switch to a lighter model
Setting up prompt caching to recover cost without dropping quality
Configuring batch processing for non-realtime report and audit workloads
Drag time forward. Watch what stays.
Forever
That's what owning means.
ai writing tool: subscription
expired · access lostanalytics suite: subscription
expired · access lostdesign platform: subscription
expired · access lost(nothing left)
Eliminates the hidden revision loops that downgraded outputs cause downstream
license: perpetualKeeps every client-facing deliverable at one predictable quality bar
license: perpetualCuts spend through caching and batching rather than quality compromise
license: perpetualFuture-proofs every agent so new model releases upgrade automatically via the alias
license: perpetualsubscriptions expire · deeds don't
Pick a piece up. Watch it work.
Total-cost-of-iteration reasoning that counts revision rounds, not just per-call price
6 parts · one working system · ships instantly by email
From the field · a real case
Teams running multi-agent or automated pipelines who want consistent top-tier output and disciplined cost control without trading quality for a cheaper model.
then this was forged for you.Universal by design: these run in any AI. Delivered in the open Agent Skills + MCP format (native in Claude); ChatGPT, Gemini, Cursor and Copilot adapt the same files their own way.
All three: it audits agent frontmatter, reviews skill files for hidden cheaper-model declarations, and catches scripts that hardcode a frozen model ID instead of the alias. The audit output template covers agents, skills, and scripts in one pass.
Savings come from mechanics, not quality cuts: prompt caching recovers up to 90 percent on repeated static context, the batch API runs asynchronous workloads at half cost, and context-budget engineering trims irrelevant tokens before each call. The total-cost reasoning also counts the revision rounds that downgraded output causes.
No. The ten-point anti-pattern catalog exists to reject exactly that argument, because exceptions are where quality drift starts. If a task is genuinely cheap, batching and caching make it cheap at full quality.
By email right after purchase: ready to run, downloaded instantly, no setup wait.
A one-time purchase; no subscription or hidden fees. VAT (20%) is included.
As a digital product, it can’t be refunded once downloaded. That’s why we show exactly what’s inside and who it’s for, right here.