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pbs_datastore_prune

Prunes every backup group in a datastore or namespace tree based on a retention policy. Run with default dry-run mode to preview deletions, or set confirm to true to permanently remove snapshots.

Instructions

MUTATION: prune EVERY backup group in a datastore/namespace tree per a retention policy — the WHOLE-DATASTORE prune, schema-distinct from the single-group pbs_prune (which scopes to one backup-type+backup-id and cannot recurse namespaces).

dry_run=True (this tool's default — a deliberate flip of the schema's own false default, same as pbs_prune's) → RISK_LOW preview; dry_run=False → RISK_HIGH: PERMANENTLY DELETES snapshots across every group in scope; with NO keep_* set, ALL prunable snapshots are candidates. Dry-run-PLAN by default; confirm=True executes (POST /admin/datastore/{store}/prune-datastore, async — UPID; a null return records "ok"); the prune decisions land in the task log (pbs_tasks_list). GC afterward reclaims the space. Needs PROXIMO_PBS_* config.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nsNoNamespace to scope the prune to; omit for the root namespace.
storeYesPBS datastore name.
confirmNoFalse (default) returns a dry-run PLAN only; True executes (which, with dry_run=True, still deletes nothing).
dry_runNoTrue (THIS TOOL'S default — the schema's own default is false): report what would be pruned without deleting. Set False to actually delete.
keep_lastNoNumber of backups to keep (>=1).
max_depthNoNamespace recursion depth 0-7; omit for automatic full recursion.
keep_dailyNoNumber of daily backups to keep (>=1).
keep_hourlyNoNumber of hourly backups to keep (>=1). NOT available on the single-group pbs_prune — this endpoint alone exposes it.
keep_weeklyNoNumber of weekly backups to keep (>=1).
keep_yearlyNoNumber of yearly backups to keep (>=1).
keep_monthlyNoNumber of monthly backups to keep (>=1).
proximo_targetNoWhich configured Proxmox target to run this call against — a target name from your multi-target config (a specific PVE/PBS/PMG/PDM box). Omit to use the single/default target from the environment; the selection applies only to this call.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, the description fully carries the burden. It discloses mutation risk, dry-run preview vs actual deletion, async nature (UPID), task log results, GC recovery, and default flips. Comprehensive and precise.

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?

Information-dense paragraph with all caps emphasis. Could be better structured with bullet points, but it's concise and includes no fluff. Slightly messy but effective.

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 12 parameters and a complex mutation operation, the description covers safety, async behavior, prerequisites, sibling distinction, and parameter interactions. Extremely thorough and sufficient for agent invocation.

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. The description adds value by explaining default flips (dry_run), confirm/dry_run interaction, and uniqueness of keep_hourly. Adds meaningful context beyond schema.

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?

The description clearly states it prunes EVERY backup group in a datastore/namespace tree, distinguishing itself from the single-group sibling pbs_prune. Specific verbs and resources are used, making the purpose unambiguous.

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 contrasts with pbs_prune, explains dry_run behavior and confirm interaction, and mentions the required PROXIMO_PBS_* config. Provides clear when-to-use and when-not-to-use guidance.

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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