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Assert facts into a knowledge base for logical reasoning and querying. Supports expiration, confidence scoring, and configurable conflict resolution. Facts persist until retracted or expired, enabling persistent knowledge storage.

Instructions

Assert a fact into the knowledge base. Stores knowledge queryable via logical reasoning. Supports TTL expiration, confidence scoring, and configurable conflict resolution. Side effects: mutates state (additive) — stored facts persist until retracted or expired. Auth: requires X-Tenant-ID header for tenant isolation; FACT_WRITE permission when auth is enabled. Rate-limited per principal. Errors: VALIDATION_ERROR on bad args, CONFLICT_ERROR on contradictions when conflictStrategy=REJECT.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
predicateYesThe relationship or property name (e.g., 'parent', 'likes', 'located_in')
argsYesThe entities involved (e.g., ['alice', 'bob'] for 'alice is parent of bob')
scopeNoOptional isolation scope for partitioned reasoning (e.g., 'session_123', 'hypothesis_a')
negatedNoSet true to store the explicit negation of this fact (distinct from NAF)
ttlNoAuto-expire after this many milliseconds
validUntilNoEpoch ms when this fact stops being valid
confidenceNoConfidence score 0.0–1.0 (e.g., 0.9 = high confidence from LLM extraction)
conflictStrategyNoHow to handle contradictions: REJECT (default — error on duplicate), NEWEST_WINS, CONFIDENCE (highest wins), KEEP_BOTH
Behavior4/5

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

Discloses side effects (mutation, persistence), auth requirements (X-Tenant-ID, FACT_WRITE permission), rate limiting, and error conditions (VALIDATION_ERROR, CONFLICT_ERROR). No annotations provided, so description carries full burden and does well.

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?

Concise at 6 sentences, front-loaded with main purpose. Each sentence adds value with no redundancy.

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?

Covers purpose, side effects, auth, rate limiting, errors, but lacks description of return values (e.g., success signal or fact ID) despite no output schema. Could be more complete.

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 mentions TTL, confidence, conflict resolution at a high level but does not add significant detail 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?

Description clearly states the tool asserts facts into a knowledge base for logical reasoning. It uses specific verb 'Assert' and resource 'fact', and distinguishes from siblings like 'ask', 'recall', 'forget'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Describes when to use (to store knowledge) but lacks explicit guidance on when not to use or alternatives, especially given siblings like 'bulk_assert' for batch operations.

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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