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Run Auto Prune

run_auto_prune
Destructive

Trigger pruning and cleanup to evaluate entry importance, archive old entries, and permanently remove stale soft-deleted ones; use dry run to preview counts.

Instructions

Manually trigger the autonomous pruning and cleanup routines. This evaluates entry importance, archives old entries, and hard-deletes stale softly-deleted ones.

Input Schema

NameRequiredDescriptionDefault
dry_runNoIf true, simulates the pruning process and returns the counts without making actual changes.
use_test_dbNo
importance_thresholdNoOverride the importance score threshold (0.0 - 1.0) below which entries are eligible for pruning.
prune_older_than_daysNoOverride the number of days before archived entries are soft-deleted.
archive_older_than_daysNoOverride the number of days before active entries are archived.
hard_delete_older_than_daysNoOverride the number of days before soft-deleted entries are permanently removed.

Output Schema

NameRequiredDescriptionDefault
codeNoError code (e.g. VALIDATION_ERROR, INTERNAL_ERROR)
errorNoHuman-readable error message
dryRunNo
detailsNoAdditional error context
successNo
categoryNoError category (validation, query, connection, internal)
backupFileNo
suggestionNoSuggested fix for the error
prunedCountNo
recoverableNoWhether the error is recoverable
archivedCountNo
hardDeletedCountNo
aggregated_errorsNoDetails of individual errors in a multi-step operation

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv9.0.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true and readOnlyHint=false, so the safety profile is covered. The description earns credit beyond that by disclosing exactly what is destroyed (hard-deletes stale softly-deleted entries) and that pruning is multi-stage, which is more specific than a bare 'destructive' flag. It stops short of stating irreversibility or that the process may touch many records at once.

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?

Two sentences, no filler, and the action is front-loaded in the first clause. The second sentence exists purely to add behavioral detail that the first omits, so every sentence earns its place.

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

Completeness4/5

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

With six optional parameters, 83% schema coverage, and an output schema handling return values, the description does enough to explain the pipeline and its effects. The remaining gap is that it never connects the override parameters to the stages it describes, but nothing essential to calling the tool correctly is missing.

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

Parameters3/5

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

Schema coverage is 83%, so the schema already documents the threshold and day-count overrides, and the description adds no syntax or default guidance for them. At high coverage the baseline of 3 is appropriate; the description's process list loosely maps to importance_threshold and the age overrides but adds nothing new.

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

Purpose4/5

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

States a specific verb ('manually trigger') and resource ('pruning and cleanup routines'), then enumerates the three concrete operations performed: importance evaluation, archiving, and hard-deletion of soft-deleted entries. It is clear what the tool does, though it never names a sibling to differentiate itself from (e.g., delete_entry, cleanup_backups).

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

Usage Guidelines3/5

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

'Manually trigger the autonomous...routines' implies you use it to force a prune now instead of waiting for the automatic schedule, which is useful context. But there is no explicit when-not guidance and no reference to the manual alternatives (delete_entry, batch_delete_entries, restore_entry) with which it competes; usage must be inferred.

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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