measure twice — code once

Stop loading instructions
you don't need.

Know what your agents are loading, why they are loading it, what it costs, and whether it can be packaged better. tokencheat audits instruction architecture, extracts reusable workflows into skills, and reduces unnecessary context without blindly removing capability.

$prompt → portable skilllive Optimize for context exposure, not just shorter prompts.
instruction architecture — context exposure
The stronger optimization model

Don't ask only how to make the prompt shorter.

Ask which instructions must be active now and which only need to be discoverable later. The cheapest instruction is the one loaded only when needed, in the smallest form that preserves required behavior.

illustrative architecture
Always-on core ............. 420
Skill discovery ............. 90
On-demand workflow ....... 2,100
Deferred references ...... 1,150
Waste / obsolete ........... 240
Typical active exposure ≈ 510 tokens
Illustrative example — not provider-measured usage.
The tokencheat loop

A build pipeline for agent instructions.

Measurement comes first. Safe transformation and behavioral evidence come before distribution.

01
Collect
02
Audit
03
Score
04
Classify
05
Optimize
06
Package
07
Evaluate
08
Distribute
Runtime / Policy / Capability

Separate the framework from the expertise.

Runtime

Session setup, state, host behavior, checkpoints, artifact paths and operating mechanics. Repeated runtime is a strong structural optimization target when evidence is clear.

Policy

Cross-cutting safety, evidence, completeness, interaction and output rules. Share or defer policy only when required behavior remains explicit.

Capability

The domain methodology that makes a skill valuable. tokencheat protects capability aggressively instead of treating every long instruction as waste.

Optimization levels

Not every optimization deserves the same trust.

L0
Audit only
No transformation
L1
Structural deduplication
Low risk
L2
Progressive disclosure
Low–medium risk
L3
Semantic compression
Evaluation required
L4
Lite build
Intentional capability reduction
Evidence before claims

A compiler people can inspect.

Every recommendation should include evidence, confidence, expected context reduction, behavior risk, evaluation requirements and a rollback path. A plan exists before mutation.

Deterministic first

Parsing, hashing, exact duplication and manifests should not spend model tokens.

Estimated ≠ measured

Static context estimates, provider telemetry and behavioral parity are separate evidence classes.

Critical constraints stay locked

Safety boundaries, destructive-operation gates and downstream contracts are not casually compressed.

Reversible builds

Provenance, source commit and optimization plans remain attached to compiled artifacts.

Pricing

Free today. Founding pricing for the waitlist.

Every tool on this site is free to use in your browser today. Paid plans — saved reports, API and CLI access, team governance — open to the founding waitlist first, at founding pricing locked in before public launch.

Join the founding waitlist
FAQ

What tokencheat means by optimization.

Is tokencheat just a prompt minifier?+

No. tokencheat optimizes context exposure: what must be active now, what can be discovered on demand, what belongs in references, and what is truly waste. Shorter text matters only if required behavior survives.

What is Context Exposure Reduction?+

It compares typical active instruction context before and after an architectural change. It remains an estimate until provider-reported usage is measured, so estimated, measured and behavioral claims stay separate.

What is the Instruction Architecture Score?+

A diagnostic composite of always-on efficiency, duplication, progressive disclosure, trigger specificity, cohesion, portability, freshness, tool overhead, provenance and validation coverage. It is not a promise of causal dollar savings.

Will tokencheat rewrite third-party skills automatically?+

Not by default. Early optimization is conservative and structural. Unknown or restrictive licenses remain analysis-only for public distribution, and semantic changes require evaluation before an Optimized label.

Is the marketplace the main product?+

No. Measurement, compilation, validation and provenance come first. Distribution is the output of a trustworthy build system, not the starting point.

Audit the architecture before you add more context.

Start with your always-on agent config, then extract reusable workflows into portable skills.