YuanyuanMa03/dsh-funnel

dsh-funnel

Curate tool output before it enters the model’s context — keep the lines that matter, spill the rest to disk with a pointer. Faster turns, smaller context, sharper attention, for every tool.

The problem

Every tool result is appended to the conversation and re-sent on every subsequent model request. A npm test run that prints 500 lines rides along for the rest of the session: you pay for it on each turn, it fills the context window, and it buries the one AssertionError the model actually needs.

The existing layers don’t cover this:

Compaction-time pruning cleans up after the budget is already blown; dsh-funnel keeps it from being blown. They compose.

What you get

1. Install and forget. One command, zero configuration. The plugin covers every tool that returns text — bash, file reads, web fetch, search — and results under the threshold pass through byte-identical, so you never notice it until it saves you.

2. A ~24× smaller model view, measured. In a real headless session, a 2001-line (8,893-byte) bash result reached the model as 370 characters: head, tail, and every error/warning line kept:

   - [2001 lines of raw output]
   + [dsh-funnel] output curated: 2001 lines → 40 kept (head 15, tail 25, 0 pattern-matched). Full output: .dsh-funnel/2026-08-15T09-21-56-548Z-bash-1.log
   + 1 … 15
   + [dsh-funnel] … 1959 similar lines omitted …
   + 1977 … 2000
   

   Every later turn in the session pays for 370 characters instead of 8,893 — the saving compounds each request.

3. Nothing is lost, and the model recovers on its own. The full text spills to .dsh-funnel/ and the notice carries the path. In testing, the model missed a middle line in the curated view, searched the spill file itself, and answered correctly — curation is pagination, not deletion. The spool doubles as an audit trail of what the agent actually saw.
4. Long tasks hold up better. Smaller context means cheaper turns, later compaction, and less attention dilution — the agent stays sharp deeper into a session instead of degrading as junk accumulates.
5. Tune it to your workflow. Threshold, kept lines, keyword patterns (add your project’s own failure markers), per-tool aggressiveness, spill on/off.

Boundaries: error results are never touched (they are short and load-bearing); this complements compaction rather than replacing it.

How it works

dsh-funnel wraps the tools/execute extension point (the seam the official timeout guard uses) and curates the canonical value of successful results: the registry re-projects model-facing content from value, so the curated view is exactly what the model sees and what the session log records. Long string fields inside value — stdout, stderr, fetched pages, file contents — are replaced in place; error results are never touched.

Install

dsh plugin add github:YuanyuanMa03/dsh-funnel

Works on every tool that returns text — bash, file reads, web fetch, search.

Configuration

All fields optional; set them under the plugin entry in your profile:

- id: dsh-funnel
  name: 'dsh-funnel'
  config:
    maxChars: 4000        # results at or below this length pass through untouched
    keepHead: 15          # lines kept verbatim from the head
    keepTail: 25          # lines kept verbatim from the tail (errors usually live here)
    keepPatterns: [error, warn, fail, fatal, exception, assert, denied, panic]
    maxLineChars: 1000    # single oversized lines (minified/JSON) are capped
    spill: true           # write the full text to disk and reference it
    tools:                # per-tool overrides
      web_fetch: { maxChars: 2000 }

Safety properties

• Error results are never touched — they are short and load-bearing.
• Lossless at the disk level — spilling keeps the full text; the model re-reads on demand.
• Model-visible ⟺ logged — the curated view replaces the result at the tool seam, so the session log records exactly what the model saw.
• Byte-identical passthrough — results under maxChars return as the same object; zero allocation when idle.

Status

v0.1.0 — verified end-to-end in a real headless session: a 2001-line bash result was curated to 40 lines in model view and log, and the model recovered the omitted middle by reading the spill file (its own words: “the tool curates long output for display … verified against the complete saved output”). Unit tests cover the curation logic and the plugin wrapper. Planned: session-level savings accounting (“this session: N tokens avoided”).

License

MIT