Shapes turns action-first: action leads, steps numbered, state restated. Use for ADHD-friendly output. Do not use to trim tokens; use response-compression.
中文简介正在准备中。当前显示原文说明。
Export a research session into knowledge-intake compatible markdown. Use after a research session to hand findings to memory-palace.
中文简介正在准备中。当前显示原文说明。
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Turn a finished research session into a file knowledge-intake can read
without reformatting.
After a research session has findings and you want them stored rather than merely reported.
Skill(tome:research)
first, since an export of an empty session emits only frontmatter.Skill(tome:synthesize), which
produces the narrative form with coverage and gaps.Load the session and render it:
from pathlib import Path
from tome.session import SessionManager
from tome.output.export import export_for_memory_palace
session = SessionManager(Path.cwd()).load_latest()
markdown = export_for_memory_palace(session)
Path(f"docs/research/export-{session.id}.md").write_text(markdown)
SessionManager resolves its store relative to the path it is given, so
run this from the repository root or the session will not be found.
To export a specific session, use load(session_id) instead of
load_latest().
YAML frontmatter carrying topic, domain, session_id, date,
finding_count, channels, and type: research-export, followed by
findings grouped by channel. Each finding renders its source, URL,
relevance, summary, and channel-specific metadata.
An empty session emits the frontmatter and a line stating that no findings were recorded, which is deliberate. A silent empty file would read as a successful export of nothing.
The output is an external resource, not a corpus entry. Feed it to
Skill(memory-palace:knowledge-intake), which owns evaluation, routing,
and storage. This skill does no scoring.
export_for_memory_palace was called on a loaded sessiontype: research-exportfinding_count in the frontmatter matches the session's findingsSkill(memory-palace:knowledge-intake) or
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Shapes turns action-first: action leads, steps numbered, state restated. Use for ADHD-friendly output. Do not use to trim tokens; use response-compression.
中文简介正在准备中。当前显示原文说明。
Inverts burden of proof for code additions. Use when reviewing PRs, planning refactors, or running unbloat to challenge every addition's necessity.
中文简介正在准备中。当前显示原文说明。
Tracks per-agent token usage and flags waste in parallel dispatch. Use when evaluating parallel agent efficiency or after a multi-agent run.
中文简介正在准备中。当前显示原文说明。
Coordinates Claude agent teams via filesystem protocol. Use when orchestrating parallel agents with task dependencies. Do not use for single-agent tasks.
中文简介正在准备中。当前显示原文说明。
Evaluates API surface design, consistency, and exemplar alignment. Use when reviewing public API changes or before releasing a new API surface.
中文简介正在准备中。当前显示原文说明。
Selects architecture paradigm via research before scaffolding. Use when architecture is undecided and the choice needs justification and documentation.
中文简介正在准备中。当前显示原文说明。