taskfold

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taskfold — effectively infinite context for your coding agent.

Keep long AI coding sessions fast, cheap, and readable: finished work is folded into a short summary, and the full original content is always one call away.

For DeepSeek Harness (DSH).

Why you want it

Long sessions drown in their own history: every request re-sends hours of finished work — old tool outputs, debug logs, abandoned attempts. Costs climb, the model gets distracted, and eventually the context window fills up.

taskfold fixes this the way a good notebook does. While working, the agent wraps each task with task_begin("fix the login bug"). When the task is done, task_fold closes it and replaces the entire back-and-forth with a short titled summary:

Before:  [800 messages of raw debugging…]
After:   "fix the login bug" — summary: what was tried, what failed and why,
          what changed, what the user decided. (~1 screen)

The conversation stays readable, every request gets cheaper, and the model keeps the lessons without dragging the transcript along.

Nothing is lost. Every fold saves the exact original messages to a file, and fold_recall({ fold: N }) can regenerate it at any time. Fold first, look later — like closing a book you can reopen.

How it works (plain words)

• Named tasks. The agent opens a task before starting work and closes it when done. Open tasks survive restarts; closing is well-ordered (innermost first), and a failed close never corrupts anything — just retry.
• Folding = closing + summarizing in one call. The summary is written once, while the original span is still in context, so it's accurate — not a "summary of a summary".
• Summaries keep what matters. The summarizer is instructed to preserve user decisions and feedback (verbatim where wording matters), pitfalls and why things failed, what changed, and the outcome.
• Gentle guardrails. If the agent forgets the discipline, a one-line reminder appears in its context until it complies — no noise when the flow is healthy.
• Cheap on the cache. Folding only rewrites a middle chunk of history; the stable prefix (system prompt, tools, earlier context) stays cache-friendly.

What it adds

Four agent tools (plus the reminders above):

Tool	One-liner
task_begin({ name })	Open a named task.
task_fold({ name })	Close it and fold its whole span into one titled summary.
list_folds	List all folds (number, size, title).
fold_recall({ fold })	Bring back any fold's original content on demand.

Install

dsh plugin --profile <your-profile> add github:yindf/taskfold

Restart dsh — every session on that profile gets the tools.

Supported dsh versions

• Known to work: 0.1.2-alpha.5 (the version this plugin is developed and tested against; dsh, dsh-compaction-basic, and dsh-llm ship version-locked, so one number covers the whole surface).
• Minimum: 0.1.2-alpha.5. No older version has been tested; older alphas differ in the compaction-engine internals this plugin builds on.
• Upper bound: untested, not enforced. dsh does not yet expose host-version negotiation to plugins, so nothing rejects an incompatible host automatically — on an incompatible dsh, folds degrade (tasks still close, unfolded) rather than corrupt. After each dsh upgrade, re-check this section and update it with test results.

For maintainers

• Layout: plugins/ (the two plugin files), scripts/release.mjs, test/ (node test/*.test.mjs), CHANGELOG.md.
• Releasing: node scripts/release.mjs draft → review the CHANGELOG entry → node scripts/release.mjs release (CHANGELOG is the single source of truth for versions). If this release changes which dsh versions are supported, update the "Supported dsh versions" section in both READMEs before releasing — the release script reminds you.
• Design decisions and history live in CHANGELOG.md and the design notes in the source repo.

License

MIT. Developed against the DeepSeek Harness (@deepseek-ai/*, MIT) public packages.