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node_history

Retrieves the full history of a node across Veris runs for forensic analysis—showing risk score changes, execution results, and modification events to verify reliability.

Instructions

Returns the full timeline for a specific node across every Veris run persisted in .veris/state.db: risk score over time, execution attempts (pass / fail / flaky / skipped per tier), and the runs in which it was added, modified, or removed. Use this for forensic analysis — 'this function broke prod, what does its Veris history look like?' — or to verify that a high-risk node has accumulated enough successful executions to lower its risk weighting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nodeIdYesFull node identifier. Format: 'absolute-path::SymbolName' or 'absolute-path::Class::method'.

Implementation Reference

  • Queries the 'executions' table (not node_history table) filtering by nodeId, returning execution history across all runs
    public executionsForNode(nodeId: string): ExecutionRecord[] {
        if (!this.db) return [];
        return this.db.prepare(`
            SELECT run_id as runId, node_id as nodeId, workflow_id as workflowId, tier, directive,
                   result, detail, duration_ms as durationMs, executed_at as executedAt
            FROM executions WHERE node_id = ? ORDER BY executed_at DESC
        `).all(nodeId) as ExecutionRecord[];
    }
  • DDL for the node_history table storing risk/blast_radius per node per run
    `CREATE TABLE IF NOT EXISTS node_history (
        node_id TEXT NOT NULL,
        run_id TEXT NOT NULL,
        risk REAL,
        blast_radius INTEGER,
        ts TEXT NOT NULL,
        PRIMARY KEY (node_id, run_id)
    )`,
Behavior4/5

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

Describes return data comprehensively and mentions data source (state.db). No annotations provided, so description carries full burden. It implies read-only but doesn't explicitly state no side effects. Still, sufficient for a history tool.

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, no fluff. First sentence defines the output, second provides use case. Very efficient and front-loaded.

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 return data well despite no output schema. Mentions multiple data types. Could mention if there are any limits or pagination, but not critical for a single node query.

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 description adds little beyond what schema provides. The description restates the format but doesn't enrich meaning significantly.

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 returns a full timeline for a specific node, listing specific data types (risk score, execution attempts, history of changes). It distinguishes from siblings like confidence_history by focusing on node history across all Veris runs.

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?

Explicit usage example provided ('this function broke prod...'), but no explicit when-not-to-use or comparison to alternatives. However, the context is clear enough for an agent to decide.

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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