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crystal_prune

Permanently delete selected crystals or archived cold storage data by retention policy, cascading entity and artifact removals to prevent orphaned context.

Instructions

Permanently prune a crystal or cold storage archives by retention policy (with entity and artifact cascade).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
allNoBatch prune all archived crystals in cold storage (default: false)
forceNoForce deletion/pruning without confirmation prompt (default: true for single crystal delete, false for batch prune)
dry_runNoPreview candidates and cascade impact without deleting (default: false for batch prune)
crystal_idNoCrystal identifier to delete (active or archived)
older_thanNoBatch prune archived crystals inactive for duration (e.g. '30d', '2w', '3m')
archive_onlyNoRestrict deletion strictly to cold storage (default: true for batch prune)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.2.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully flags that the operation is 'permanent' (irreversible) and that deletion cascades to entities and artifacts, which is genuinely important context for a destructive tool. It omits, however, any statement of permissions/auth requirements, confirmation behavior, or scope differences between single-crystal and batch modes.

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?

A single sentence that front-loads the destructive nature and the resource. It is efficient, though the phrasing 'a crystal or cold storage archives' is slightly awkward and mixes singular/plural scope.

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

Completeness3/5

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

For a destructive, zero-annotation, no-output-schema tool, the description conveys permanence and cascade but leaves gaps around batch-vs-single semantics, safety parameters, and how it relates to sibling archive/melt tools. The 100% schema coverage compensates for parameter detail, keeping this at minimum viable.

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 description coverage is 100%, so all six parameters are already documented in the schema, and the baseline is 3. The description's 'retention policy' and 'cascade' phrasing loosely maps to older_than and the cascade behavior but adds no syntax, format, or interaction detail beyond the schema.

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 (prune) plus resource (crystal / cold storage archives) and mechanism (retention policy with entity/artifact cascade). However, it does not distinguish itself from close siblings like crystal_melt, crystal_archive, or crystal_unarchive, which an agent would need to tell apart.

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

Usage Guidelines2/5

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

There is no explicit when-to-use or when-not-to-use guidance, and no alternative tool is named despite several plausible siblings (crystal_melt, crystal_archive). The retention-policy phrasing implies a scenario but leaves the agent to infer selection criteria.

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