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zzhang82

Agent Memory Bridge

by zzhang82

recall

Retrieve matching memory entries or poll for new coordination signals by filtering on metadata like namespace, tags, actor, or session.

Instructions

Recall matching entries or poll for new signals from the bridge.

Use this tool to search durable memory, filter by metadata, or poll for fresh coordination signals. For issue-like work, prefer project and domain recall before external search. For workflow polling, pass since, an empty query, and kind="signal".

Empty-query Signal recall returns a next_since cursor for the next polling cycle; other recall modes return next_since=null. The cursor tracks later insertions, not status changes to older Signals.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoOptional type filter. Use `memory` for durable knowledge recall and `signal` for coordination or polling flows.
actorNoOptional actor filter for entries written by a specific agent or user.
limitNoMaximum number of entries to return. Smaller values keep context tighter.
queryNoOptional text query for full-text recall. Leave empty to use filter-only retrieval or polling.
sinceNoOptional cursor for polling only entries newer than a previously seen same-namespace entry id used as a Signal polling anchor. Requires an empty query and `kind="signal"`.
tags_anyNoOptional OR-style tag filter. Any matching tag is enough for an entry to qualify.
namespaceYesNamespace to search or poll, such as `project:<workspace>`, `domain:<name>`, or `global`.
session_idNoOptional session filter to narrow results to one conversation or run.
signal_statusNoOptional status filter for signals. Useful when you want only pending handoffs, currently claimed work, or already-acked coordination events.
correlation_idNoOptional correlation filter to recall entries linked to the same workflow, handoff, or task.
evidence_contextNoOptional caller-declared evidence labels. Only `model`, `harness`, and `chat_template` are accepted; signed receipts contain bounded SHA-256 digests, never raw values. These labels are not authenticated and do not affect retrieval order or feedback identity.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Despite no annotations, the description fully explains behavioral traits: distinguishes between memory and signal modes, specifies that empty-query Signal recall returns a `next_since` cursor while other modes return null, and clarifies that the cursor tracks insertions, not status changes. This covers the essential behavioral aspects without contradiction.

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?

Three well-organized paragraphs: purpose, usage guidelines, and behavioral nuance. Each sentence earns its place, front-loading critical info and avoiding redundancy. No unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 11 parameters, two distinct use cases, and an output schema, the description provides complete operational context. It covers both retrieval and polling modes, parameter combinations, cursor behavior, and even suggests workflow preferences. The output schema handles return value detail, so the description does not need to reiterate it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, but the description adds significant usage context beyond the schema. For example, it explains that `since` requires an empty query and `kind='signal'`, and describes the meaning of `next_since` cursor. This enriches parameter understanding beyond the schema field descriptions.

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's dual purpose: recall entries from durable memory and poll for new signals. It differentiates from siblings like 'store' and 'forget' by being retrieval-focused, and gives explicit guidance on when to use each mode.

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?

Provides explicit when-to-use guidance: 'Use this tool to search durable memory, filter by metadata, or poll for fresh coordination signals.' Includes specific instructions for workflow polling with `since`, empty query, and `kind='signal'`. Also advises preferring project/domain recall for issue-like work, offering clear alternatives.

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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