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backlog_consolidation_candidates

Identify clusters of episodic memories ready for consolidation into durable knowledge, returning bundles to process into narratives.

Instructions

List clusters of episodic memories that are ripe for consolidation into durable knowledge. Consolidator workflow: (1) call this and take ripe bundles; (2) per bundle, read members (backlog_get on MEMO- ids for depth), then write ONE narrative memory via backlog_remember({ layer: "semantic"|"procedural", derived: true, entity_refs: [member MEMO- ids + key source entities], context }) — a self-contained story, not fragments; (3) retire the members via backlog_forget({ ids }) so they stop appearing here while staying auditable; (4) track your progress with a backlog_remember state_key like "consolidation.watermark.".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
min_countNoMinimum bundle size to be ripe. Default: 3.
min_age_daysNoMinimum age (days) of the oldest member. Default: 7.
min_demandNoRecall-demand threshold — bundles recalled this often (30d) are ripe regardless of age. Default: 3.
contextNoRestrict to one context (e.g. "FLDR-0001").
limitNoMax bundles, ripe first. Default: 10.
max_digestsNoMax digest lines per bundle. Default: 10.
Behavior4/5

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

No annotations are provided, so the description must carry the behavioral burden. It explains that the tool lists bundles without modifying state, but does not explicitly state it is non-destructive. The detailed workflow implies no side effects, but a more explicit statement would be ideal.

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 fairly lengthy but well-structured with a numbered workflow. It provides necessary detail for the complex functionality, though some sentences could be streamlined without losing clarity. Overall, it is efficient for the content it conveys.

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 no output schema and no annotations, the description covers the purpose, workflow, and parameter usage well. However, it lacks explicit details about the output format or fields of the returned bundles. The workflow implies structure but does not specify it, leaving some gap.

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?

All six parameters have descriptions in the schema (100% coverage), so the baseline is 3. The description adds no additional meaning beyond the schema's parameter descriptions, which are already clear. It does not compensate or enhance parameter understanding.

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 that the tool lists clusters of episodic memories ripe for consolidation into durable knowledge. It uses specific verbs and resources, and the purpose is distinct from sibling tools like backlog_get or backlog_forget.

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?

The description provides a step-by-step Consolidator workflow (1-4) that explicitly states when to use this tool, how to use it in conjunction with other tools, and what actions to take afterwards. This gives clear guidance on context and 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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