Linter + profiler + coverage — for agent context

Know what your agent actually loads.

ctxlint audits, profiles, and scores AGENTS.md, CLAUDE.md, .cursor/rules, and every other context file steering your AI coding agents — then shows what it costs you in tokens, on every single request.

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~/dev/your-app

npx @tqakdev/ctxlint scan

Scanning agent context… 14 files · 4 tools

CLAUDE.md6,410
AGENTS.md3,120
.cursor/rules/ (9 files)7,860
.github/copilot-instructions.md1,240
duplicate-rule“use pnpm, never npm” copied in 3 files
stale-referenceCLAUDE.md:41 → src/utils/api.ts (deleted)
contradictiontabs (AGENTS.md:12) vs spaces (style.mdc:3)
buried-criticalsecurity rule at line 214 of 230

Context Health 0/100 · 3 errors · 11 warnings · 6 info

npx @tqakdev/ctxlint fix --write

merged 3 duplicates · removed 6 dead rules · pruned stale refs

Context per request18,630 tokens−60% ▼

Psst… this is what a real scan looks like

Stop confusing your AI.

Every duplicated, drifted, or contradictory rule silently taxes every request — in tokens you pay for and in output quality you don’t get. ctxlint answers the questions nobody could answer about your repo.

What loads?

Per tool, per directory, in load order — see exactly what each agent reads, and why.

What does it cost?

Token totals for the context injected into every request — per file, per tool, no guessing.

What’s broken?

Duplicates, contradictions, drifted copies, dead file references, and rules buried 200 lines deep.

Does it help?

Judge recent commits against your rules — catch violations, and dead rules that never fire.

one command in CI · zero config

ctxlint scanctxlint fix --writectxlint compliance--ciGitHub ActionHealth Score 0–100text · json · md

Free forever.
Fueled by supporters.

ctxlint is MIT-licensed and always will be. If it saved you tokens — or sanity — a one-time donation funds the open-source team building new detectors, better profiling, and fewer confused agents.

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