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slowave-ai

slowave

Official
by slowave-ai

slowave_recall

Retrieve relevant memories and procedures from the active session using a natural-language query, providing historical context for mid-task decisions.

Instructions

Semantic retrieval: bring relevant memories into working memory. Use for deliberate mid-task lookups when you need specific historical context beyond what activate surfaced. Recall is explicitly bound to the active session and matching scope. Args: query: natural-language query; omit when continuing a frozen result. session_id: active session returned by slowave_activate. scope: required retrieval boundary; must match the session. task_context: optional context update for this sub-question. evidence: references (default) or full; budget and policy are server-owned. continue_from: opaque cursor returned by activate or recall. The cursor is bound to this session and scope and replays a frozen tail. Returns: retrieval_id: pass to slowave_feedback after using memories. memories: canonical direct/associated memories with stable pathways. procedures: canonical procedures, including their ID, goal, summary, context, steps, caveats, outcome, outcome_summary, created_at, aggregate evidence, and recent contributions; no ranking scores. evidence: bounded records with evidence_id, source_kind, recorded_at, occurred_at, and source_ref; full mode also returns content and per-record truncated. evidence_mode: the applied references or full mode. evidence_truncated: whether evidence records exceeded the response budget. more_available: whether a frozen continuation page is available. continue_from: opaque continuation cursor, present only when more_available. accessible_field: bounded orientation for unreturned candidates; contains extra_candidates, kinds, and approx_extra_tokens, never content.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNo
scopeYes
evidenceNoreferences
session_idYes
task_contextNo
continue_fromNo
semantic_contextNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.20.3

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden. It goes beyond the schema by disclosing session/scope binding, server-owned budget and policy, frozen continuation semantics, truncation behavior, and that accessible_field never contains content. It does not state whether the operation modifies state or what authentication is required, but the disclosed contract is detailed and useful.

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?

Purpose and usage are front-loaded, and the Args/Returns structure is methodical with no filler. It is long, but for a 7-parameter tool with no annotations most lines add value; the exhaustive return enumeration is the main risk of duplicating information already available in the output schema.

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?

For a complex retrieval tool with no annotations, it gives enough context to call correctly: required session/scope, query rules, evidence modes, continuation and truncation, and the retrieval_id handoff to slowave_feedback. The missing semantic_context explanation and lack of error-case guidance are the notable gaps, but the output schema plausibly covers return shapes.

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?

Schema coverage is 0%, so the description must compensate, and it largely does: it explains query omission when continuing a frozen result, session_id provenance, scope matching, task_context purpose, evidence modes, and continue_from cursor semantics. However, semantic_context appears in the input schema but is never described, leaving one parameter unexplained.

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 first sentence names a specific verb and resource: 'Semantic retrieval: bring relevant memories into working memory.' The second sentence immediately distinguishes it from slowave_activate by framing it as a deliberate mid-task lookup for context 'beyond what activate surfaced,' so an agent can tell which sibling to use.

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?

The description explicitly says to use it for 'deliberate mid-task lookups when you need specific historical context beyond what activate surfaced,' naming the main alternative and the condition that selects this tool. It also reinforces the binding requirement to the active session and matching scope, which is a crisp usage constraint.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.