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session_synthesize_edges

Analyze project entry embeddings to discover semantic relationships between disconnected nodes and synthesize inferred links, enriching the knowledge graph with hidden connections.

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

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

With no annotations provided, the description carries full burden. It discloses the creation of 'synthesized_from' links and batch processing behavior, but omits critical mutation details: whether the operation is idempotent, reversible, or if duplicate runs create duplicate edges. Missing safety profile for a write operation.

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 tightly constructed paragraphs with zero waste. The first sentence front-loads the core mechanism (scanning embeddings to create links), while the second provides usage cadence guidance. Every clause conveys distinct operational or contextual information.

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 high schema coverage and the tool's specific scope, the description adequately covers the graph synthesis concept and batch processing nature. Minor gap: no mention of relationship to similar sibling session_backfill_links or behavior when no high-similarity matches exist.

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%, establishing baseline 3. The description adds domain context by referencing 'cosine similarity' (aligning with similarity_threshold), 'newest active entries' (context for max_entries), and 'Step 3A' workflow positioning, enriching raw parameter definitions without redundancy.

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 explicitly states the tool 'Scans recent project entries with embeddings, finds high-similarity but currently disconnected entries, and creates inferred links as synthesized_from', providing specific verbs (scans, finds, creates), resources (entries, links), and distinguishing this graph-mutation function from sibling search/retrieval tools like session_search_memory.

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?

Provides clear context with 'Use this tool periodically' and 'On-Demand Graph Enrichment' indicating when to run it (for discovery of semantic relationships), but lacks explicit 'when-not-to-use' guidance or named alternatives (e.g., contrast with session_backfill_links).

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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