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session_synthesize_edges

Scans recent project entries, identifies high-similarity but unlinked entries, and creates inferred edges to enrich the knowledge graph.

Instructions

Step 3A Edge Synthesis: Scans recent project entries with embeddings, finds high-similarity but currently disconnected entries, and creates inferred links as 'synthesized_from'.

On-Demand Graph Enrichment: Use this tool periodically to discover semantic relationships between structurally disconnected memory nodes. It batch processes the newest active entries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectYesProject identifier.
max_entriesNoMaximum number of recent entries to scan as sources. Default: 50. Max cap: 50.
randomize_selectionNoIf true, randomly sample active entries instead of taking the newest (default false). Ideal for wide-coverage background sweeps.
similarity_thresholdNoMinimum cosine similarity score (0.0 to 1.0) to create a link. Default: 0.7.
max_neighbors_per_entryNoMaximum number of links to synthesize per source entry. Default: 3. Max cap: 5.
Behavior3/5

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

With no annotations, the description carries full burden. It explains the scanning, similarity detection, and link creation process, but does not disclose whether it modifies existing links, destroys data, or requires specific permissions. It could be more transparent about side effects.

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?

The description is concise with two short paragraphs. The first explains the process, the second provides usage guidance. Every sentence adds value with no fluff.

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?

The description covers purpose and usage context but lacks details on return values, error handling, and prerequisites (e.g., existence of embeddings). Given no output schema, more completeness would be helpful.

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

Parameters4/5

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

Schema coverage is 100%, so parameters are already documented. The description adds value by explaining that max_entries relates to 'recent' entries and that randomize_selection is for wide-coverage sweeps, enhancing meaning beyond the 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 it synthesizes edges by scanning recent entries, finding similar but disconnected entries, and creating inferred links. It uses specific verbs and resource terms, and the 'Step 3A' labeling distinguishes it from other tools like session_backfill_links.

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 explicitly recommends using the tool periodically for discovering semantic relationships, providing clear context for when to use it. However, it does not mention when not to use it or direct comparisons to alternative tools.

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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