fewer starting-map tokens
1,402 → 230 tokens per task
OPEN-SOURCE CODEX CONTEXT PLUGIN
Compact Context replaces a long repository map with five short file hints. Codex still has access to every file. In 68 public tasks, the shorter hint included the eventual edit file 50 times; the longer baseline did so 48 times.
MIT licensed · no separate service · no embeddings · does not rewrite source
> fix the receipt marker race in turn_start.py and context_receipt.py
FIVE STARTING SUGGESTIONS — NOT A FILE LIMIT
Codex can still search every repository file after this hint · inspect receipt data ↗
WHAT THE SAVING MEANS
Both methods suggest up to five files where Codex should begin. Compact Context sends much less text to make that suggestion.
Codex still has access to the complete repository and continues its normal search after the hint.PUBLIC BENCHMARK · 68 TASKS
Two ways of suggesting where Codex should start were compared across ten public repositories. Neither method restricted which files Codex could inspect afterward.
1,402 → 230 tokens per task
used before normal repository search
longer baseline map: 48/68
WHAT 50/68 MEANS
For each task, the benchmark knew which file needed changing and checked whether it appeared in the five starting suggestions. Compact Context included it in 50 of 68 tasks; the longer lexical map included it in 48 of 68. Both could still search the whole repository afterward. This measures the initial hint—not task completion or code quality.
WHAT RUNS BEFORE THE MODEL
Compact Context suggests useful places to begin. It does not summarize source, block files, or replace Codex’s normal repository search.
Read tracked and non-ignored untracked files. Skip dependencies, build output, binaries, symlinks, oversized files, and credential-shaped content.
Record paths, file roles, symbols, signatures, imports, frequent identifiers, hashes, and resolved local dependencies.
Exact paths and symbols carry the most weight. Imports, rare identifiers, dependents, and related tests add cross-file evidence.
A greedy selector takes up to five useful candidates, rewards linked files and different roles, and penalizes duplicate evidence.
The automatic map is capped at 650 estimated tokens. Weak matches, small direct repositories, and failures leave the normal Codex turn untouched.
MAP-COMPARISON RECEIPT
When Compact Context supplies a starting hint, the normal Codex response ends with the estimated input saved for that hint. It does not claim a saving for the complete task.
The public benchmark uses exact o200k counts. The live receipt uses a clearly labeled characters ÷ 4 estimate and does not claim complete-session savings.
0.5.0-BETA.7
Paste one Terminal command. It installs the plugin, opens the Codex hook review, and takes you directly to the two approvals.
The installer is open source and verifies the downloaded ZIP against the published SHA-256 before installation.
OPEN RESEARCH LEDGER · SEPARATE LLM-IR EXPERIMENT
v0.0.8 fixed most of the parser failure exposed by the first frozen run, then faced a new untouched slice. Qwen still produced only 4/20 correct LIR solutions at Pass@1 versus 17/20 in Python. No breakthrough, no-quality-loss, or token-saving claim is supported.
IR means intermediate representation. The model writes a small code-like notation, a compiler turns it into JavaScript, and tests run the result. We tested whether that detour would use fewer tokens than ordinary Python. It did not.
WHAT THE FAILURE TAUGHT US
First-attempt compiler failures fell from 20/20 in v0.0.7 to 2/20 in v0.0.8. The remaining losses were unsupported operations and incorrect algorithms from the unfamiliar grammar.
LIR used about 5.02× as many session-amortized tokens per correct solution as Python. The target was at least 25% fewer.
This language experiment is separate from Compact Context’s shipped repository-routing benchmark above. The negative result does not change the measured 1,402 → 230 map-token comparison; it prevents a broader model-efficiency claim.
PRODUCTION CLAIM STATUS
That test uses matched completed tasks, native provider billing, hidden tests, 450 runs, and three unrelated model families. The 30% full-workload claim will ship only after it passes.