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Recall prior work across all projects

ygg_recall
Read-onlyIdempotent

Search across all projects to find prior solutions, decisions, and lessons. Use before solving any non-trivial problem to reuse past work.

Instructions

Search durable memory ACROSS ALL projects for prior solutions, decisions, and lessons to reuse. Use BEFORE solving any non-trivial problem ("have I handled this before?"); for one known project use ygg_bootstrap to load its context or ygg_search for a targeted query instead. Ranks by relevance and past usage — lexical by default, semantic when embeddings are enabled.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jsonNoReturn raw JSON instead of formatted text (default false). Set true to parse fields programmatically.
typeNoOptional filter to one memory category. Omit to recall across all types.
limitNoMaximum number of memories to return (default 5).
queryYesNatural-language description of the problem or topic to find prior work for, e.g. "token refresh before opening socket".
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint. Description adds ranking behavior (relevance and past usage, lexical vs semantic). No contradictions, but could detail more about ranking mechanics.

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, front-loaded with the core action. Every sentence provides distinct value (purpose, usage guidance, ranking note). No wasted words.

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?

Covers purpose, when to use, alternatives, and ranking. No output schema exists, but description doesn't explain return format. However, for a search tool, this is nearly complete.

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 covers 100% of parameters with descriptions. Description provides context for the query and mentions memory categories but doesn't add significant meaning beyond schema. Baseline 3 is appropriate.

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?

Description explicitly states the tool searches durable memory across all projects for prior solutions, decisions, and lessons. The verb 'search' and resource 'durable memory' are specific, and it distinguishes from siblings like ygg_bootstrap and ygg_search.

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?

Provides clear guidance: 'Use BEFORE solving any non-trivial problem' and explicitly gives alternatives for other scenarios (ygg_bootstrap for one project, ygg_search for targeted query).

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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