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prepare_wrap

At session wrap, generate a compression package with episodes, continuity file, pattern warnings, and a wrap token to verify save_continuity.

Instructions

Prepare a compression package for session wrap. Call this at session boundaries — when work is ending, the user says to wrap up, or the session is getting long. Returns all episodes since the last wrap, the current continuity file, stale pattern warnings, Hebbian association context (which episodes have been thought about together before), and compression instructions. Marks a wrap as in-progress and mints a session-handshake token (shown as 'Wrap token: ' at the end of the response) — round-trip that token to save_continuity's wrap_token argument so the save call can verify it matches the in-progress wrap and catch stale tokens. After calling, follow the returned instructions to compress episodes into an updated continuity file, then save with save_continuity. The compression step is where the real thinking happens — patterns emerge that weren't visible in the raw episodes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_charsNoMaximum size of the continuity file in characters. Omit to derive a schema-aware default (20000 for the standard schema, larger for a richer schema like FLOW_SCHEMA).
staleness_daysNoDays without validation before flagging patterns as stale. Default 7.
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Despite no annotations, the description fully discloses behavior: returns data, marks wrap in-progress, mints a token, and explains that compression reveals patterns. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is somewhat lengthy but every sentence adds value. Front-loaded with purpose and usage. Slightly verbose in explaining the token and follow-up, but still focused.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Complete for a complex tool without output schema: explains return values, side effects, and necessary follow-up action (save_continuity). Covers all operational aspects.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so description adds extra context beyond schema: explains default derivation for max_chars and default value for staleness_days.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the verb+resource: 'Prepare a compression package for session wrap.' Distinguishes from siblings like save_continuity and record by focusing on session boundaries.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly specifies when to call: 'at session boundaries — when work is ending, the user says to wrap up, or the session is getting long.' Also describes the follow-up action with save_continuity and the token round-trip.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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