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Graph Weaken

graph_weaken
Idempotent

Decrease an edge's weight when correcting a recalled fact. Use when user corrects a fact from the graph, reducing its importance.

Instructions

Decrease an edge's weight when the user corrects a recalled fact. Call this when the user says 'no', 'that's wrong', or corrects something from the graph. Persists immediately; weight clamps at 0.0. Returns an error if the edge doesn't exist — use graph_delete to remove an entity outright. To replace a fact rather than weaken it, prefer graph_relate with the new fact and SUPERSEDES.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
from_nameYesSource entity name or ID
to_nameYesTarget entity name or ID
relationYesRelationship type
amountNoWeaken amount (default: 0.3)
reasonNoWhy weakening

Implementation Reference

  • Registration of the graph_weaken tool on the MCP server with its input schema (from_name, to_name, relation, amount, reason) and handler.
    server.registerTool("graph_weaken", {
      title: "Graph Weaken",
      description:
        "Decrease an edge's weight when the user corrects a recalled fact. Call this when the user says 'no', 'that's wrong', or corrects something from the graph. Persists immediately; weight clamps at 0.0. Returns an error if the edge doesn't exist — use graph_delete to remove an entity outright. To replace a fact rather than weaken it, prefer graph_relate with the new fact and SUPERSEDES.",
      inputSchema: {
        from_name: z.string().describe("Source entity name or ID"),
        to_name: z.string().describe("Target entity name or ID"),
        relation: z.string().describe("Relationship type"),
        amount: z.number().optional().default(0.3).describe("Weaken amount (default: 0.3)"),
        reason: z.string().optional().describe("Why weakening"),
      },
      annotations: { idempotentHint: true },
    }, async (args) => {
      try {
        const tenantId = currentTenant();
        const fromId = (await client.findEntityIdByName(tenantId, args.from_name)) ?? slugify(args.from_name);
        const toId = (await client.findEntityIdByName(tenantId, args.to_name)) ?? slugify(args.to_name);
        const result = await client.weaken(tenantId, fromId, toId, args.relation as RelationshipType, args.amount);
        return toolResult({
          previous_weight: result.previous_weight,
          new_weight: result.new_weight,
          edge: { from: fromId, to: toId, type: args.relation },
          pruned: result.new_weight <= 0.05,
        });
      } catch (err) {
        return toolError(`graph_weaken failed: ${err instanceof Error ? err.message : String(err)}`);
      }
    });
  • Handler function for graph_weaken: resolves entity IDs by name, calls client.weaken() to reduce edge weight, and returns previous/new weight plus whether the edge was pruned.
    }, async (args) => {
      try {
        const tenantId = currentTenant();
        const fromId = (await client.findEntityIdByName(tenantId, args.from_name)) ?? slugify(args.from_name);
        const toId = (await client.findEntityIdByName(tenantId, args.to_name)) ?? slugify(args.to_name);
        const result = await client.weaken(tenantId, fromId, toId, args.relation as RelationshipType, args.amount);
        return toolResult({
          previous_weight: result.previous_weight,
          new_weight: result.new_weight,
          edge: { from: fromId, to: toId, type: args.relation },
          pruned: result.new_weight <= 0.05,
        });
      } catch (err) {
        return toolError(`graph_weaken failed: ${err instanceof Error ? err.message : String(err)}`);
      }
    });
  • Neo4jClient.weaken() method that executes the Cypher query to decrement edge weight, clamps at 0.0, and returns old/new weight values.
    async weaken(
      tenantId: string,
      fromId: string,
      toId: string,
      type: RelationshipType,
      amount?: number,
    ): Promise<{ previous_weight: number; new_weight: number }> {
      const config = getConfig();
      const weakenAmount = amount ?? config.weights.weaken_on_correct;
      const rows = await this.run(
        `
        MATCH (a:Entity {tenant_id: $tenantId, id: $fromId})-[r:\`${type}\`]->(b:Entity {tenant_id: $tenantId, id: $toId})
        WITH r, r.weight AS old_weight
        SET r.weight = CASE WHEN r.weight - $amount < 0.0 THEN 0.0 ELSE r.weight - $amount END,
            r.last_confirmed = datetime()
        RETURN old_weight, r.weight AS new_weight
        `,
        { tenantId, fromId, toId, amount: weakenAmount },
      );
      const row = rows[0];
      if (!row) throw new Error(`Edge not found: ${fromId} -[${type}]-> ${toId} in tenant ${tenantId}`);
      return {
        previous_weight: Number(row["old_weight"]),
        new_weight: Number(row["new_weight"]),
      };
    }
  • Default weaken amount (0.3) defined in the config schema under weights.weaken_on_correct.
      weaken_on_correct: 0.3,
      project_context_boost: 0.1,
    },
Behavior4/5

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

Annotations only provide idempotentHint. Description adds persistence, clamping at 0.0, and error on missing edge. Provides useful behavioral context beyond annotations.

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?

Four sentences, front-loaded with core action. Every sentence is necessary and concise. No unnecessary repetition.

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, usage, behavioral traits, and error condition. Missing success return value, but overall fairly complete for a 5-parameter tool without output schema.

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 coverage is 100%, so baseline is 3. Description adds minimal extra parameter meaning beyond schema descriptions (e.g., mentions amount default but schema includes it).

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?

Clearly states the verb (decrease) and resource (edge weight). Distinguishes from siblings like graph_delete and graph_relate by specifying alternative actions.

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?

Explicitly states when to call (user corrections like 'no', 'that's wrong') and provides alternatives for deletion (graph_delete) or replacement (graph_relate with SUPERSEDES).

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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