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ArkaAiAdmin

Agentic Memory

by ArkaAiAdmin

memory_extract_skills

Trigger skill extraction from a specific memory or run full pass across all memories. Use dry run to preview without writing.

Instructions

Manually trigger skill extraction.

P0 fix #5: lets the operator re-run the lower-threshold extractor on a specific memory (memory_id="lessons/foo") or on every memory when memory_id is empty. Uses the cron implementation so the same code path runs in both places.

Args: memory_id: when non-empty, extract a skill from just this single memory. When empty, run the full extraction pass (same as cron_skill_extraction.py). dry_run: when True, count what would be extracted without writing to the DB.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dry_runNo
memory_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It mentions that extraction uses the cron code path and that dry_run prevents writes, but it does not state whether the operation is destructive, idempotent, or requires specific permissions. The internal P0 fix comment adds developer context but does not help the agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

The description is structured with an Args block, but it includes a developer-oriented note ('P0 fix #5') that is irrelevant for an AI agent. This noise reduces conciseness. The first sentence is clear, but the internal reference should be removed.

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?

With an output schema present, the description does not need to detail return values. However, it lacks information about prerequisites, error conditions, or side effects beyond the dry_run flag. For a simple two-parameter tool, the description is adequate but not thorough.

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

Parameters5/5

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

Schema description coverage is 0%, meaning no parameter info in the schema. The description compensates fully by explaining both parameters: memory_id determines scope (specific vs all) and dry_run controls writing. This adds essential meaning beyond the raw 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 the tool's action ('Manually trigger skill extraction') and specifies the two modes of operation (single memory or full pass). This verb+resource combination is unambiguous and distinguishes it from sibling tools like memory_list_skills or memory_compile_skill.

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 clear guidance on when to use each parameter: memory_id for a specific memory or empty for full extraction, and dry_run for testing without writing. However, it does not explicitly state when not to use this tool or mention alternatives.

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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