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curator_run

Destructive

Archive stale agent-created skills using activity windows and tier-based adjustments. Dry-run mode previews changes before applying.

Instructions

Move stale agent-created skills to archive.

Lifecycle: active → stale when last activity > stale_after_days stale → archived when last activity > archive_after_days (also moves primary directory to .archive/)

Tier-aware adjustments (the discrete trust signal trumps raw activity): • tier='validated' skills are NEVER stale-aged or archived — proven load-bearing knowledge stays alive regardless of recency. • tier='hypothesis' skills age faster — half the stale_after window (default 15d instead of 30d). Unproven skills don't get to linger. • tier='observed' uses the standard windows.

NEVER touches: • foreground (user-authored) skills — provenance check • pinned skills — opt-out flag • validated tier — proven externally • skills with no created_by_origin set (unknown provenance — be safe)

dry_run=True (default) reports what would change without writing. Set False to apply.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dry_runNo
stale_after_daysNo
archive_after_daysNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already indicate destructiveness (destructiveHint=true). The description adds valuable context: the full lifecycle (active -> stale -> archived), tier-aware adjustments (validated never aged, hypothesis ages faster), and exclusions. Dry_run behavior is also disclosed.

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?

The description is well-structured with bullet points and sections, front-loading the main action. It is informative without being overly verbose, though it could be slightly more concise.

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?

Given the tool's complexity (lifecycle, tiers, exclusions, dry_run) and the presence of an output schema, the description covers most needed context. It explains the behavior fully, though the output is not described (but that's acceptable since output schema exists).

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 0%, meaning the description does not explicitly describe each parameter. However, it does provide context for 'dry_run' (reports without writing) and indirectly for 'stale_after_days' and 'archive_after_days' through the lifecycle explanation. This adds meaning beyond the schema but could be more explicit.

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 the tool's purpose: 'Move stale agent-created skills to archive'. It uses a specific verb ('move') and resource ('skills') and distinguishes from sibling tools like curator_review by detailing the archiving lifecycle.

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

Usage Guidelines4/5

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

The description provides explicit guidance on when to use the tool (for archiving stale agent-created skills) and when not to (never touches foreground, pinned, validated, or unknown provenance skills). It also mentions the dry_run default for safe testing. However, it does not explicitly name alternative tools for different scenarios.

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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