Make every coding agent
follow the right instructions.
Audit AGENTS.md, CLAUDE.md, skills, and tool policies. Remove unnecessary always-on context, compile the durable rules into portable policy, and verify that important behaviour survives.
Runs locally in your browser. No signup. No source upload.
The instructions drifted. The agent did not tell you.
None of these announce themselves. They show up as an agent that used to be reliable and now needs watching — which reads as the model getting worse, not as the instructions around it accumulating.
- Important rules get ignored.
- Different coding agents receive different policies.
- Old project decisions stay loaded forever.
- Destructive actions have no clear approval boundary.
- The same instruction appears in several files.
- Nobody can explain why a rule activated.
- Shortening an instruction file quietly removes capability.
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.
A build pipeline for agent instructions.
Measurement comes first. Safe transformation and behavioral evidence come before distribution.
Collect. Pull the instruction files, skills, and MCP configs your agents actually load — the real always-on surface, not the intended one.
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.
Measure, audit, optimize, validate.
Not every optimization deserves the same trust.
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.
Parsing, hashing, exact duplication and manifests should not spend model tokens.
Static context estimates, provider telemetry and behavioral parity are separate evidence classes.
Safety boundaries, destructive-operation gates and downstream contracts are not casually compressed.
Provenance, source commit and optimization plans remain attached to compiled artifacts.
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 waitlistWhat 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.
The workspace the founding cohort gets.
Saved audit history, context scores over time, and a compiler that turns findings into conservative optimizations. Explore the screens — this is a live preview with illustrative data, not the product API.
Saved audits
24
Average context score
71
Best score
94
Est. monthly savings
$412
claude-code · CLAUDE.md
Aug 18
cursor rules · monorepo
Aug 16
support-agent system prompt
Aug 14
mcp servers · 6 enabled
Aug 12
review-bot instructions
Aug 09
Start measuring in the next sixty seconds.
Every tool runs free in your browser — no signup, and pasted text never leaves your machine. Every number carries its source.
Audit
Team favoriteLiveAgent Config Audit
Score and conservatively optimize always-on agent instruction files in the browser.
Open tool →
Optimize
Team favoriteLivePersonal AI Rider
Compile your durable working conditions, technology policy, and action boundaries into one portable rider, then export adapters for Claude Code, Cursor, Copilot, and AGENTS.md.
Open tool →
Measure
Team favoriteLiveAI Token Calculator
Estimate LLM cost from input, output, and cache tokens using maintained per-million pricing. Estimates only — verify against your provider invoice.
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Measure
Team favoriteLiveModel Price Comparison
Provider-by-provider view of per-million input and output rates with context windows, sourced from provider pricing pages.
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Optimize
LiveSkill Compiler
Start with Prompt → Skill today; inspect the full roadmap for repo audits, structural builds, host packages, provenance, and behavioral validation.
Open tool →
Optimize
LiveTechnology and Action Register
Review all twenty-one capability decisions as one sortable table and every action an agent may take on your behalf, with the authorization level each one sits at. States policy; the host enforces it.
Open tool →