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prune_cluster

Remove paper notes from a cluster based on their frontmatter label, either archiving or deleting them, to clean up after fit-check labeling.

Instructions

Archive or delete paper notes in a cluster whose frontmatter carries label.

Cluster cleanup operation that acts on the label sidecars written by apply_fit_check_to_labels (e.g. deprecated, off_topic, low_relevance). Moves matching paper notes to the cluster's _archive/ subfolder by default, or deletes them outright if delete=True. Pairs with apply_fit_check_to_labels as a two-step "decide → act" workflow: that tool labels papers based on fit-check sidecars; this tool acts on the labels.

When to use:

  • After running apply_fit_check_to_labels (or manually labelling papers), you want to physically move the off-topic notes out of the active cluster folder.

  • You want to keep an audit trail (default archive=True) so the moves are reversible.

When NOT to use:

  • You want to ADD labels, not act on them; use apply_fit_check_to_labels instead.

  • You want to delete the entire cluster (not just labelled papers); use research-hub clusters delete (CLI) instead.

  • You want to rebind orphans to a different cluster, not archive them; use cluster_rebind instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cluster_slugYesCluster whose papers are scanned.
labelNoFrontmatter label string to match (e.g. ``"deprecated"``, ``"off_topic"``). Papers without this label in their frontmatter are skipped. Defaults to ``"deprecated"``.deprecated
archiveNoWhen ``True`` (default), move matched papers to ``hub/<slug>/_archive/`` rather than deleting them. Set to ``False`` only when paired with ``delete=True``.
deleteNoWhen ``True``, permanently delete matched papers instead of archiving. Defaults to ``False`` (safer). Has no effect when ``archive=True``.
dry_runNoWhen ``True`` (default), report what WOULD be affected without touching the filesystem. Pass ``False`` to execute the moves/deletes.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations provided, but description fully discloses behavioral traits: defaults for archive, delete, dry_run; two-step workflow; audit trail reversibility. 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.

Conciseness5/5

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

Description is well-organized with bullet points for usage guidelines. Every sentence adds value, no fluff. Appropriate length for complexity.

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?

Given 5 parameters and output schema exists, description is complete: covers purpose, usage, parameter behavior, sibling relationships, and workflow. No major gaps.

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%, baseline 3. Description adds value beyond schema by explaining parameter interactions (delete has no effect when archive=True), defaults, and expected label values. Not quite 5 because schema already does heavy lifting.

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?

Description clearly states verb 'Archive or delete paper notes in a cluster whose frontmatter carries label', specifying resource and condition. It distinguishes from siblings by naming related tools (apply_fit_check_to_labels, cluster_rebind).

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?

Provides explicit 'When to use' (after apply_fit_check_to_labels) and 'When NOT to use' (adding labels, deleting entire cluster, rebinding orphans), with named alternatives (apply_fit_check_to_labels, CLI, cluster_rebind).

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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