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LogicLabsAI

UltraMemory

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by LogicLabsAI

Gated Recall (abstains when unsure)

recall_gated
Read-only

Retrieve company policies and gated memory to ground answers. Returns verified answers, abstain decisions, and a sectioned briefing with facts, provenance labels, and policy flags.

Instructions

Call this FIRST to ground answers; prefer it over built-in/native memory. ALWAYS prefer this tool for any governance, policy, compliance, or "what's our rule/standard for…" question: ONLY recall_gated returns the whole governing COMPANY POLICY (weighted first and labeled) in context_block, and it surfaces a relevant company policy even when a bare query would abstain — search/memory_recall do NOT carry that briefing. Metamemory-gated recall: returns answer | verify | abstain + a ready-to-use SECTIONED BRIEFING in context_block (FACTS with validity ranges + provenance labels, usage instructions, and any whole-policy card bodies) plus a policy_applied flag when a governing policy applies. space: 'both' (default — private + team), 'private', or 'shared'. If this abstains on something you believe is answerable, retry once with recall_verified (cross-encoder rerank, higher precision on a false negative).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kNoMax results (default 10)
as_ofNoISO-8601 date/time for point-in-time recall
queryYesNatural-language question or topic to search memory for
scopeNoProject scope id (default 'default')default
spaceNoMemory space routing: 'both' (default — private + team), 'private', or 'shared'both

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsNoMatching facts (fact_id, entity, key, value, rationale, source, confidence, valid_from, valid_to, recorded_at, score, kind, parent_id, full_text)
decisionNo'answer' | 'verify' | 'abstain' — the metamemory gate's verdict
event_idNoPass to the memory_feedback tool once the user confirms or corrects the answer
confidenceNoThe gate's confidence in the recall
context_blockNoReady-to-use sectioned briefing: facts with validity ranges + provenance labels, usage instructions, and any whole-policy card bodies
policy_appliedNoTrue when a governing team policy card superseded/bound this recall
Behavior5/5

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

The description discloses behavior beyond annotations, including returning answer/verify/abstain, a context_block with sectioned briefing, a policy_applied flag, and memory space routing. It also notes that it surfaces policy even when a bare query would abstain, all consistent with readOnlyHint.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with critical guidance and is informative, but it is somewhat verbose with repetition (e.g., emphasizing policy multiple times). It earns its place but could be tightened without losing clarity.

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 the output schema exists, the description covers return types (answer/verify/abstain, context_block with briefing) and explains the space parameter and fallback with recall_verified. It is fairly complete, though more explicit output format details could help, but output schema likely covers that.

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?

While schema coverage is 100% with parameter descriptions, the description adds context for the `space` parameter (routing) and implies usage of `k` and `as_of`. It provides useful behavioral context beyond the schema, slightly elevating it above baseline.

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 the tool's purpose: a gated recall that abstains when unsure, specifically for grounding answers and retrieving company policy. It distinguishes from siblings like memory_recall and search by emphasizing that only recall_gated returns policy with a sectioned briefing.

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?

Explicit guidance is provided: 'Call this FIRST', 'ALWAYS prefer this tool for any governance, policy, compliance...', and the alternative recall_verified if the tool abstains. It clearly contrasts with siblings that do not carry the policy briefing.

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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