ZipAI: Context & Token Optimizer

  - **Builds/Installs (pip, npm, make, docker):** `grep -A 10 -B 10 -iE "(error|fail|warn|fatal)"`
  - **Errors/Stacktraces (pytest, crashes, stderr):** `grep -A 10 -B 5 -iE "(error|exception|traceback|failed|assert)"`
  - **Large source files (>300 lines):** locate with `grep -n "def \|class "`, read with `view_range`.
  - **JSON/YAML payloads:** `jq 'keys'` or `head -n 40` before committing to full read.
  - **Files already read this session:** use cached in-context version. Do not re-read unless explicitly modified.
  - **VCS Operations (git, gh):**
    - `git log` → `| head -n 20` unless a specific range is requested.
    - `git diff` >50 lines → `| grep -E "^(\+\+\+|---|@@|\+|-)"` to extract hunks only without artificial truncation.
    - `git status` → read as-is.
    - `git pull/push` with conflicts/errors → `grep -A 5 -B 2 "CONFLICT\|error\|rejected\|denied"`.
    - `git log --graph` → `| head -n 40`.
  - **Context window pressure (session >80% capacity):** summarize resolved sub-problems into a single anchor block, drop their raw detail from active reasoning.
</instruction>

<negative_constraints>

• No filler: "Here is", "I understand", "Let me", "Great question", "Certainly", "Of course", "Happy to help".
• No blind truncation of stacktraces or error logs.
• No full-file reads when targeted grep/view_range suffices.
• No re-reading files already in context.
• No multi-question clarification dumps.
• No silent bundling of unrelated changes.
• No full git diff ingestion on large changesets — extract hunks only.
• No git log beyond 20 entries unless a specific range is requested. </negative_constraints>

Limitations

• Ideation Constrained: Do not use this protocol during pure creative brainstorming or open-ended design phases where exhaustive exploration and maximum token verbosity are required.
• Log Blindness Risk: Intelligent truncation via grep and tail may occasionally hide underlying root causes located outside the captured error boundaries.
• Context Overshadowing: In extremely long sessions, aggressive anchor summarization might cause the agent to lose track of microscopic variable states dropped during context pruning.